Digital Marketing – Digital Nomads HQ

Google Ads Opens Travel Campaigns to Tours and Events

Benjamin Paine — Thu, 09 Jul 2026 01:29:53 +0000

Do you sell tours, attraction tickets or event tickets?

Google Ads just gave you a new campaign type to test.

On July 8, 2026, Google announced that its Search campaigns for Travel beta now covers two new verticals: Things to Do and Events.

Here’s what changed and how to test it properly.

What’s changed?

Quick backstory.

In May 2026, Google launched Search campaigns for Travel at Google Marketing Live.

It bundles the travel ad formats (Travel Promotion Ads, Booking Links and travel feeds) into one Search campaign type, powered by AI Max.

One campaign. One budget. One view of performance.

No more juggling separate formats and splitting budgets between them.

At launch, it was built for traditional travel advertisers (think hotels and flights).
Now Google has extended the beta to Things to Do and Events.

That covers attractions, guided tours, experiences and event tickets.

It’s an open beta, but availability is limited.

Google hasn’t published eligibility rules yet.

Why Google picked these verticals

Think about what selling tour spots or event tickets actually looks like.

Prices change. Availability changes daily. And every purchase is tied to a specific date and place.

That’s exactly how hotel rooms and flights work. Which is why Google built automated travel campaigns for them in the first place.

Until now though, if you sold tours or tickets, you had two options: standard Search campaigns or Performance Max.

Neither was designed for date-based, availability-driven inventory.

This campaign type is.

What you get

Because it runs inside Search campaigns, you get tools the old travel formats missed out on

Full Search bidding suite: Including true target ROAS across all your travel assets.

Keyword and search term reporting: See exactly what people searched before they clicked.

Data-driven attribution: Plus a single performance view across the whole results page.

What’s still unknown

Google announced this in a five-post thread on X.

Not a full blog post.

So plenty of details are missing: eligibility criteria, which countries can use it, feed requirements, and which bidding and reporting features apply to the new verticals.

Expect things to change during the beta.

How to approach it

Don’t rip up your existing campaigns.

Here’s the smarter play:

Check your Google Ads account (or ask your agency) to see if the beta is available to you

Set aside a small test budget

Run it alongside your current Search and Performance Max campaigns

Compare bookings and ticket sales, not just clicks

If the numbers beat your existing mix, scale it. If not, you’ve lost nothing.

Our take

Tourism and events businesses have spent years advertising date-based inventory with generic campaign tools.

This is Google admitting that gap exists.

The beta is limited, details are thin, and features will shift.

But if you sell tours, experiences or tickets, getting in early means you learn the format while your competitors wait for the official rollout.

Want to know if your business is eligible, or need help structuring the test?

Talk to the DNHQ team.

Google Ads 2026 Bidding & Budgeting Updates Explained

Benjamin Paine — Sat, 27 Jun 2026 10:01:53 +0000

Google just changed how its bidding works.

And one part of it has a deadline.

Here is the short version: from 17 August, some of your best Google Ads campaigns could quietly start costing more. Not because you did anything wrong.

Because Google is closing a gap you have probably been benefiting from without realising.

If you run Google Ads, or pay someone to, this is the one to understand before August.

Let us break it down.

The change with a deadline: Bidding Target Optimisation

This is the one main aspect to act on… so let’s start here.

Right now, loads of budget-capped campaigns quietly beat their targets.

You set a Target CPA of $50.

But because the campaign is limited by budget, it has actually been pulling leads in at $30.

You have been getting a better result than you asked for.

You might not have even noticed.

From 17 August, Google is closing that gap.

For campaigns marked “Limited by budget” that use Target CPA or Target ROAS, performance will line up more closely with the target you set.

Google calls it more consistent and predictable.

Here is the catch.

If your capped campaigns have been over-delivering, your cost per lead could climb, or your ROAS could slip, back toward the number sitting in your settings.

It hits Search, Shopping, Performance Max, Demand Gen and Travel campaigns.

And one thing to be clear on: Google will not touch your targets or budgets for you.

The shift happens automatically.

What you do about it is on you.

What to do about it

Before 17 August, go through every campaign that is Limited by budget and running Target CPA or Target ROAS.

For each one, you have three honest options.

Lock in the better result. If a capped campaign has been over-delivering and you want to keep that, lower the target to match what it is actually doing.

Set the Target CPA to the $30 it is really hitting, not the $50 you typed in six months ago. For most over-delivering campaigns, this is the move.

Keep your targets as they are. Happy to trade a bit of efficiency for the consistency Google is offering? Do nothing. Just make it a decision, not an accident.

Turn the budget up. A capped campaign that is beating its target is usually telling you there is more profitable volume out there. Lift the budget and go get it at your stated target, instead of leaving it boxed in.

Google is rolling out a Bid Target Adjustment Tool from 6 July to help, you will get a notification in your account.

It shows each campaign’s history and lets you apply new targets in a few clicks. That is your window. This kind of account hygiene is exactly what we handle as part of Google Ads management.

The other two changes are upside, not homework

The rest of the announcement is good news, no deadline attached.

Smart Bidding Exploration, expanded

This one lets you set a ROAS tolerance so your campaigns can chase conversions from searches they are not currently catching.

A controlled way to find new, profitable demand.

As of 15 June it is live in all Performance Max campaigns without product feeds, globally, with a beta rolling out to Shopping and feed-based PMax. Google says campaigns using it see an 18% lift in unique converting query categories and 19% more conversions on average. If growth is the goal, test it.

Promotion Mode (beta)

Got a sale, a launch, a peak season?

Promotion Mode lets you temporarily loosen your ROAS tolerance and add budget for that window, then ease back, without rebuilding the campaign. It is in beta for Search and Performance Max.

For retailers and anyone with seasonal spikes, this is a genuinely handy way to lean in hard when it counts.

And a name change

Small one. “Maximise conversions with a Target CPA” is now just Target CPA. “Maximise conversion value with a Target ROAS” is now Target ROAS. Same behaviour, clearer names. Update your reports if they still use the old labels.

Our take

Google is selling the big change as consistency. For some accounts, fair enough, that is welcome.

But be clear-eyed. If your capped campaigns have been over-delivering, this can quietly hand back some of that efficiency unless you act.

The worst outcome is sleepwalking into higher costs because nobody checked the targets before 17 August.

And here is the deeper bit.

All of this, the target optimisation, the exploration tolerance, the promotion boosts, is only as good as the conversion data underneath it. Automated bidding optimises toward the signals you feed it.

So clean tracking and accurate targets are what turn these changes into a win instead of a cost.

The accounts that come out ahead in August will be the ones that were actually managed. Not set and forgotten.

Want us to review your campaigns before 17 August, or just take the bidding off your plate? Talk to our Google Ads team, or see how we run performance marketing end to end.

Frequently asked questions

What is changing in Google Ads on 17 August 2026?

For campaigns that are Limited by budget and use Target CPA or Target ROAS, Google will deliver performance that lines up more closely with the target you set. Many of those campaigns currently beat their targets, so this can push cost per lead up, or ROAS down, toward your stated number unless you adjust.

Will Google change my targets or budgets automatically?

No. The performance shift is automatic, but Google will not change your targets or budgets for you. You decide: lower targets to lock in current performance, keep your targets, or lift the budget to scale.

What is the Bid Target Adjustment Tool?

A tool rolling out in Google Ads from 6 July 2026, flagged by a notification in your account. It shows each campaign’s history and lets you review and apply updated targets fast, ahead of 17 August.

What should I actually do before 17 August?

Go through every Limited by budget campaign on Target CPA or Target ROAS. For each, decide whether to lower the target to keep the better performance it has been delivering, keep the target, or raise the budget to scale. Do not leave it to chance.

What are Smart Bidding Exploration and Promotion Mode?

Two opportunity features from the same announcement. Smart Bidding Exploration lets you set a ROAS tolerance to catch new converting queries (now in PMax without feeds, with a beta for feed-based campaigns). Promotion Mode lets you temporarily boost ROAS tolerance and budget for peaks like sales, in beta for Search and Performance Max.

How Much Does Digital Marketing Agency Cost in Australia?

Benjamin Paine — Thu, 11 Jun 2026 00:33:56 +0000

Digital marketing in Australia typically costs between $1,000 and $4,000 per month per channel for small to medium businesses, based on DNHQ’s June 2026 audit of 140 Australian agencies.

Published entry prices for full-service agencies start around $500/month for SEO, $495/month for social media management, $400/month for Google Ads management, and $1,295 for a website project, but most agencies charge considerably more, and 78% don’t publish their prices at all.

Service	Average advertised entry	Median advertised entry	Typical SME range (advertised)	Upper-tier published solutions
SEO (monthly retainer)	$1,496/mo	$1,470/mo	$1,200–$2,500/mo	$5,000+/mo
Google Ads management	$1,391/mo	$1,250/mo	$1,200–$3,500/mo + ad spend	$6,000+/mo
Web design (project)	$8,404	$4,975	$2,500–$15,000	$50,000+
Social media management (organic)	$1,219/mo	$960/mo	$950–$2,500/mo	$7,500+/mo
Paid social marketing (ads mgmt)	$1,221/mo	$1,200/mo	$1,200–$2,500/mo + ad spend	$3,500+/mo

Benchmarks exclude ultra-budget productised offers (SEO under $500/month; ads and social under $400/month; websites under $1,000). Those exist from as little as $99 – $330/month but are a different product class: templated, volume-delivered, and minimally customised. See methodology.

Source: DNHQ Australian Digital Marketing Price Index, published pricing of 140 Australian agencies audited June 2026. Prices AUD; GST treatment varies (see below).

Why you can't find this answer anywhere else

Here’s the uncomfortable truth our research uncovered: of 411 agency service lines we audited across 140 Australian agencies, 78% publish no pricing whatsoever.

Only 8% publish a genuine rate card.

The rest gate their prices behind “free strategy sessions”, budget-bracket enquiry forms, and downloadable brochures that ask for your email first.

That’s why every “how much does digital marketing cost” article you’ve read is vague.

The data didn’t exist, so we built it.

This article is based on the published pricing and published inclusions of 140 Australian agencies across SEO, Google Ads, web design and social media, collected June 2026.

The methodology is at the bottom; the numbers are real, recent, and Australian.

How much does SEO cost in Australia?

SEO in Australia costs an average of $1,496 per month at published entry level (median $1,470/month), with advertised retainers spanning $500 to $5,000 per month across the 38 qualifying monthly from-prices in our audit.

Most full-service agencies advertise entry prices of $1,200–$2,500 per month.

Ultra-budget productised SEO exists from $200–$499/month but is a different product (capped keywords, templated content, volume delivery).

Notably, the cheapest published prices cluster in regional Australia, while capital-city agencies are the most likely to publish nothing at all.

What the published market actually looks like:

Tier	Monthly price	What’s typically included (where stated)
Budget / productised	$549–$999	Up to 10–30 keywords, 2–4 blogs/mo, basic links, monthly report
Standard SME	$1,500–$2,500	40–75 keywords tracked, content optimisation, link building, GBP/local, monthly report + strategy session
Growth	$2,500–$4,000	75–100 keywords, more content + stronger links, technical work, dedicated specialist
Competitive/enterprise	$5,000+	Custom scope; most agencies at this level publish nothing

Three things the price tags don’t tell you:

The same dollar buys wildly different amounts. Among agencies that publish both prices and quantities, a tracked keyword costs anywhere from $30/month to $99/month. Always ask what the number includes.

Hours are almost never disclosed. Only a handful of Australian agencies state how many hours of work your retainer buys (where stated: roughly 12–15 hours at ~$1,900/mo).

If an agency won’t tell you the hours, you can’t compare quotes.

AI/GEO optimisation is now claimed by half of Australian SEO agencies, and quantified by none. 49% of the SEO providers we audited now sell some form of AI-search optimisation.

Not one attaches a defined deliverable to it. If you’re paying for it, ask what “it” is.

How much does Google Ads management cost in Australia?

Google Ads management in Australia costs an average of $1,391 per month at published entry level (median $1,250/month), with qualifying fees spanning $400 to $6,000+ per month, plus your ad spend (always billed separately).

Most published SME packages sit between $1,200 and $3,500 per month.

Setup fees, where charged, run $499–$2,000.

Flat-fee budget operators exist from $290–$330/month; at that price expect a capped campaign count and minimal optimisation hours.

The four fee models you’ll encounter (only 48% of agencies disclose which one they use):

Flat monthly fee: the most common disclosed model ($550–$6,000+/mo)
Weekly fee tiers: e.g. $249–$499/week pegged to minimum daily ad spends
Percentage of ad spend: typically appears at higher spend levels (e.g. 15% of spend)
Unit/hours-based: pre-purchased blocks (e.g. ~$135/unit, 10 units/month)

The number that matters more than the fee: minimum ad spend.

Only 22% of agencies state one, but where stated they range from $500/month to $500/day ($15,000+/month). Your real monthly cost is fee + spend: an advertised “$300/month” management fee on a $3,000/month spend requirement is a $3,300/month commitment.

Buyer’s checklist from the data: ask the fee model, ask the minimum spend, confirm you own the ad account (some agencies build in theirs), and confirm whether ad creative is included.

Landing pages are excluded from most base packages and sold at up to $1,000/page.

How much does a website cost in Australia?

A professionally built website in Australia costs an average of $8,404 at published entry level, but the median is $4,975, because a handful of premium builds ($15,000–$50,000+) drag the average up.

Qualifying advertised projects run $1,295 to $50,000+, and below the $1,000 line sits a separate template/subscription market ($499–$995 builds, $25–$399/month website subscriptions).

If you’re a typical small business, the median is your better benchmark.

The clusters in the published data:

Tier	Project price	What defines it
Budget template	$499–$1,299	Template design, 5–15 pages, hosting bundled, client provides content
Small business	$2,500–$5,400	Kit/theme-based, ~4–7 pages, basic SEO setup, some training
Mid-market custom	$5,000–$15,000	Custom design, CMS (usually WordPress/Shopify), copywriting optional
Premium custom	$15,000–$40,000+	UX research, user testing, custom code, accessibility standards
Enterprise	$50,000+	Headless/DXP platforms, integrations, milestone delivery

The two questions that cause every web project dispute (and that almost nobody answers up front): how many pages (stated by just 11% of agencies) and how many revision rounds (stated by 29%; quantified by a handful at 2–3 rounds).

Get both in writing before you sign.

Also budget for the after-launch reality: care/maintenance plans run $49–$300+/month at the SME level (and up to $2,200 – $9,900/month for managed performance retainers), and “12 months free hosting” style inclusions exist but are rare.

How much does social media marketing cost in Australia?

Social media management (organic posting, content and community) in Australia costs an average of $1,219 per month at published entry level (median $960/month), running $495–$2,450 per month depending on posting volume.

Paid social marketing (Meta/TikTok ads management) averages $1,221 per month (median $1,200), running $695–$2,500 per month plus ad spend.

These are different products with different price logic and most agencies sell them separately, though a small hybrid market bundles posting and ads into one $650–$900/month fee.

Below the $400 line sits a productised feed market ($99–$300/month for templated posting), which is a different product class. Fewer agencies publish social pricing than any other service.

What the posting-cadence tiers look like in the published data:

Posts per week	Typical monthly price	Notes
~3 posts/wk (12–13/mo)	$275–$1,440	Cheapest tiers reuse one post across 2 platforms
4–5 posts/wk (16–20/mo)	$469–$2,700	Mid tiers add stories/reels, more platforms
Paid social mgmt	$300–$2,500 entry	Creative often costs extra; check minimum spends

The catch most buyers miss: community management (actually responding to comments and messages) is almost never included.

Only ~1 in 3 agencies even mention it, and at several it’s a paid add-on. If “managing our socials” means answering your customers, confirm it’s in scope.

Same for photo/video: usually an add-on or top-tier perk, and several agencies require a separate “boosting” budget of $300–$500/month paid by you.

The hidden costs nobody puts on the pricing page

From auditing 88 agencies, the recurring traps:

GST ambiguity. Fewer than 1 in 10 agencies state whether prices include GST. Where stated, prices are almost always exclusive, so add 10% to everything you see. (Every price in this article is as published; ask every agency “inc or ex GST?”)
Setup fees ($499–$1,999 for ads; $550+ onboarding; $900 campaign setup), often revealed only at proposal stage.
“No lock-in” with an asterisk. “No lock-in contracts” is the most-published commercial term in Australian marketing: more agencies publish their contract stance than their price. But look closer: “no lock-in” frequently coexists with a 3-, 6- or 12-month “initial period”, “sprint” or “recommended minimum”. One agency we audited displays a “No Lock-In Contracts” badge on the same site as a 3-month-minimum FAQ.
Media spend is never included. Ad budgets go to Google/Meta on top of every management fee quoted here.
The $X/day decoy. “$5–10/day” figures on agency pages are your ad spend, not their fee. Three agencies in our audit present platform costs where buyers would expect pricing.

What should YOUR business budget?

Pulling the channels together, realistic all-in monthly budgets (fees + minimum viable ad spend, ex GST):

Local service business, one channel: $1,500–$3,000/mo (e.g. local SEO, or Google Ads with modest spend)
Established SME, two channels: $3,000–$6,000/mo (the bracket most full-service agencies design for, and consistent with what agencies themselves recommend: several audited agencies state $2,000–$5,000/mo working minimums)
Growth-stage, multi-channel: $6,000–$15,000/mo
One-off website: $2,500–$15,000 project + $50–$300/mo care

Worth knowing as you budget: our companion research found Australian search demand fell 32–44% across every capital city in 2026 while AI Overviews now appear on ~37–38% of results, which means every dollar should be working both classic search and AI visibility. See the State of AI Search →

Agency vs in-house: what does each actually cost?

The comparison most businesses run in their head (“for that retainer I could just hire someone”) deserves real numbers.

A single in-house digital marketing specialist costs roughly $105,000 – $130,000 a year all-in: a $85,000–$100,000 salary (SEEK’s 2026 average for the role), plus 12% superannuation, leave loading, payroll on-costs, recruitment, and the tool stack agencies amortise across clients (SEO platforms, reporting software and ad tools run $300–$800+/month on their own). That’s $8,700–$10,800 per month for one generalist, before any ad spend.

Against the benchmarks in this article, the same money buys two to four specialist channel retainers (e.g. SEO at ~$1,500/mo + Google Ads at ~$1,250/mo + paid social at ~$1,200/mo ≈ $4,000/mo) with senior specialists in each discipline, no leave or turnover risk, and tools included.

The honest counterpoints: an in-house hire gives you dedication, brand immersion and unlimited iterations that no retainer matches, and one generalist can’t be a senior technical SEO, media buyer, designer and copywriter at once, which is the actual trade. The pattern that works for most SMEs in the data’s $3,000–$6,000/month bracket is hybrid: a marketing coordinator in-house owning brand and approvals, with channel execution bought as specialist retainers.

What we charge

We’ve spent this entire article telling you 78% of agencies won’t publish prices. Here’s ours:

Service	DNHQ pricing
SEO	from $1,797/mo*
Google Ads management	from $1,497/mo*
Social media marketing	from $1,497/mo*
Website builds	from $5,000*

*Starting prices: your exact fee depends on scope, competition and inclusions, and is itemised line-by-line in every proposal. No lock-in contracts.

Methodology

Pricing data: published prices, packages and inclusions from the websites of 180 Australian digital marketing agencies across SEO, Google Ads/PPC management, web design and social media marketing, collected June 2026 (DNHQ Australian Digital Marketing Price Index). The transparency statistic (78%) is computed on a 140-agency representative sample drawn from independent directories and roundups across 20 Australian cities; price benchmarks additionally include a 40-agency oversample of price-publishing agencies found via search. Benchmark figures exclude ultra-budget productised offers (SEO under $500/month entry; ads and social under $400/month; web projects under $1,000) as a distinct product class; their existence and price points are noted in the text. Figures are advertised/published entry prices, not invoices. Quotation permitted with attribution to DNHQ Research.

Content Marketing Strategy: 2026 Guide + Free Builder

Benjamin Paine — Mon, 08 Jun 2026 06:52:40 +0000

Most content marketing guides are still teaching the old playbook.

Publish, rank, collect the clicks.

The trouble is the clicks are drying up.

We tracked more than 80 service keywords across six Australian markets and 21 industries, month by month.

Demand climbed through 2024, peaked in late 2025, then fell 38% in 2026. None of the six markets escaped it.

That fall tracks almost exactly with Google rolling out AI Overviews across Australian search.

The answer now sits at the top of the results, so the questions people used to type, read and click on get handled on the spot.

Which means a content marketing strategy in 2026 has to do two things at once. Earn attention when the click never comes, and become the source the AI quotes.

This guide gives you a nine-step framework to do both, plus a free template and a tool that drafts your strategy in minutes.

What is a content marketing strategy?

A content marketing strategy is your documented plan for using content to reach a specific audience and hit a business goal. In 2026, add one more job to the list: staying visible when AI answers the search for you.

Three terms get used as if they mean the same thing.

They do not.

Content marketing strategy is the why. Who you help, how, and why you are the one to do it.

Content strategy is the what and how. Creating, organising and governing the content itself.

Content plan is the when and who. The calendar, and the people who own each piece.

You do not need a 40-page document.

A strategy people actually use covers five things: a clear goal, a defined audience, a position (what you can say that nobody else can), the content and channels to deliver it, and a way to measure it.

Why you need a content marketing strategy in 2026

The old reasons still apply.

A documented strategy ties content to revenue instead of guesswork.

It wins buy-in from the people who hold the budget.

It stops you publishing for the sake of publishing.

Study after study finds the same thing: teams with a documented strategy outperform the ones working on instinct, and feel less stretched doing it.

Then there is the reason nobody was talking about two years ago.

Visibility no longer equals traffic.

When an AI Overview answers a question, you can be cited inside that answer.

You get seen, credited and trusted, with no click attached.

And if you are not the source the model pulls from, you are invisible even when you technically rank on page one.

A 2026 strategy is built to win the citation, not just the position.

The 2026 shift: AI search, GEO and the content that gets eaten

Before the how-to, look at the ground you are building on, because it has shifted under everyone. Two pieces of our own Australian research show how far.

In our State of AI Search study we captured 116,918 live search results across 18 industries and six cities. 37.8% of commercial Australian searches now trigger a Google AI Overview.

More than a third of the time, the answer shows up before anyone clicks a result, and across the study that came to roughly 387,000 AI citations.

Our Australian Search Demand study tells the second half.

Local-service search volume fell 38% in 2026, and the categories that fell hardest were the research-heavy ones: lawyers down 56%, mortgage brokers 47%, web design 40%. Those are exactly the questions an AI Overview can settle in a single box.

This is where it gets uncomfortable for content marketers.

The classic how-to article, the ultimate guide, the what-is-X explainer: that is exactly the content AI now absorbs and summarises. Publish it in 2026 and you have mostly written training data for the answer box. You have not given anyone a reason to visit you.

So the bar has moved, and it moved fast.

Content that an AI can summarise in two lines is now a waste of budget.

What earns its place is the content AI cannot fully replace or has to cite: first-hand experience, original data, a genuine point of view, and the transactional or local searches where someone still has to click.

That is the thinking behind generative engine optimisation (GEO), and it runs through every step below. The rule is simple enough: publish less, and publish what only you can.

How to build a content marketing strategy (9 steps)

1. Set SMART goals

Start with the one outcome that matters most, and make it Specific, Measurable, Achievable, Relevant and Time-bound. “Grow organic leads 30% by Q4” beats “get more traffic”, because every later decision then has to earn its place.

Common goals, with a number attached: brand awareness (branded-search volume up 50% in six months), lead generation (40 qualified enquiries a month), authority (cited in AI answers for your 10 priority queries), sales (25% year-on-year revenue from organic), retention (cut churn 15%).

Pick one primary goal and at most two to support it. Everything cannot be the priority.

2. Research your audience and map the buyer journey

Go deeper than age, location and job title. In an AI-search world the questions your audience asks are the product, because those questions are what the engines now answer. Build one or two researched personas with real roles, real pains, the actual words they use, and where they look. Pull from your sales-call transcripts, your analytics and customer interviews, not assumptions.

Then map content to the buyer journey, because a strategy that serves one stage only leaks revenue:

Top of funnel (awareness): the problem-aware searcher. Guides, explainers, original research, short video.
Middle of funnel (consideration): comparing options. Comparisons, case studies, webinars, how-tos.
Bottom of funnel (decision): ready to act. Service pages, pricing guidance, testimonials, demos.

Most businesses over-invest at the top and starve the middle and bottom.

Fix that on purpose.

3. Define your positioning, brand story and voice

This is the step most tactical guides skip, and it is the one that decides whether your content is forgettable.

Before a single topic, decide what you can say that competitors cannot: your point of view, your proof (data, results, credentials) and the through-line that makes your content recognisably yours.

It matters more under AI search, not less.

Generative engines cite sources they understand and trust as entities, so a clear and consistent voice, a real named author, and demonstrable first-hand experience, the signals behind E-E-A-T, are now ranking and citation factors.

Anonymous, me-too content is the first thing a model skips.

4. Choose your 3 to 5 content pillars

Pillars are the core themes you want to be known for.

Pick three to five, no more, where your expertise, your audience’s interests and your commercial goals overlap.

For a digital agency, pillars might be SEO, AI search, paid media, and web or CRO. Each pillar becomes a hub, with cluster content answering the specific questions beneath it, all interlinked.

There is a reason for this beyond tidiness.

Google now reads content as topic clusters, not isolated pages.

Depth across an interconnected set of pages signals real authority, and that same interlinking improves your odds of being cited in AI answers. Pillars are how you build authority on purpose instead of by accident.

5. Do topic and keyword research by intent

Find the specific topics under each pillar.

Use a keyword tool (Semrush, Ahrefs or Google Keyword Planner) to gauge search volume, difficulty and intent, meaning what the searcher actually wants: to learn, to compare, or to buy.

Then add the 2026 filter most guides miss. Ask which queries an AI Overview already answers in full, and which still need a click.

With AI Overviews on 37.8% of commercial searches, this is now the single most important call you make.

Weight your calendar toward the click-worthy topics (transactional, local, opinion-led and experience-driven) and toward topics where you have first-hand data to add.

6. Choose your content types and formats

Match formats to your audience and your goal. The core menu: blog posts and guides, video (still the highest-engagement format in 2026 across YouTube, Reels and LinkedIn), email, podcasts, webinars, case studies, infographics and social.

Then add the two modern types that actually survive AI search:

Answer content. Pages built as direct, citable answers: the question as a heading, the answer in the first sentence or two, real numbers to back it. This is how you get pulled into AI Overviews instead of summarised out of them.
Original research. Your own data. It is the single best asset for earning links and AI citations, and almost none of your competitors have it.

Do not spread across ten formats.

Pick the two or three your audience actually consumes, and do them properly.

7. Plan distribution and promotion

Great content that nobody sees is not a strategy. It is a diary. Plan how each piece reaches your audience across three buckets:

Owned: your site, email list and SEO. The foundation, because it compounds.
Earned: digital PR, guest articles, podcast appearances, and the backlinks original research attracts. For most Australian businesses this is the biggest under-used lever, and the one that earns the authority AI engines reward.
Paid: Google Ads, Meta and LinkedIn to put your best pieces in front of the right audience faster.

Match channels to where your audience already is. Pick two and go deep. Six shallow ones will not move anything.

8. Build your calendar, workflow and team

Put your prioritised topics into a calendar with an owner, content type, status and due date.

Consistency beats sporadic bursts.

But a calendar on its own is not a system.

Define the engine behind it: who briefs, writes, edits, optimises and publishes, and to what standard.

Set your cadence honestly.

Promise two strong pieces a month and deliver them.

That will do more than eight thin ones you abandon by March. Document the strategy and share it, so freelancers, in-house staff and any agency are working to the same brief.

9. Audit, measure and optimise

A strategy does not end at “publish”.

Track your goal metric, organic traffic and conversions.

Then add the measurement the old playbooks omit: are you being cited in AI Overviews and AI answers for the queries that matter?

Classic rank tracking no longer sees what happens above the organic results, so treat AI citation as the new page one.

Tie content to pipeline and revenue with attribution in GA4 and Search Console so you can defend the budget.
Set KPIs by goal.

Awareness maps to branded search and impressions, leads to conversions and cost per lead, authority to citations and backlinks.

Run a content audit twice a year: find your winners and refresh them (recency is now a real AI-citation signal), prune or consolidate the dead weight, and repurpose the best pieces into video, social and email so one strong idea earns its keep five times over.

Then re-baseline your demand assumptions, because the curve is still moving.

Common mistakes to avoid

Publishing the content AI eats. How-to explainers and “ultimate guides” are exactly what AI Overviews absorb. Lead with citable answers, real numbers and first-hand experience instead.
Optimising for demand that no longer converts. Forecasts built on 2025 volumes are too high. Plan against the current curve.
Skipping distribution. If you spend 80% on creation and 20% on promotion, flip it.
No pillars, no owner, no measurement. A strategy that is not structured and run is just a document.
Treating AI search as a future problem. It is already on 37.8% of commercial Australian results. It is a now problem.

Build your strategy with DNHQ

We build content marketing strategies for Australian businesses designed for how search actually works in 2026: content that gets cited, not just ranked. If you would rather not start from a blank page, see our Content Marketing Services and AI SEO work, or book a free strategy session.

Frequently asked questions

What is a content marketing strategy?

A documented plan for using content to reach a specific audience and achieve a business goal, and in 2026, to stay visible in AI search. At minimum it covers your goal, audience, positioning, content pillars, channels and measurement.

How do I create a content marketing strategy?

Set SMART goals, research your audience and map the buyer journey, define your positioning, choose three to five content pillars, research topics by intent, choose your content types, plan distribution, build a calendar and team, then audit and measure, including your AI visibility.

What are content pillars?

Three to five core themes you want to be known for. Each becomes a hub with cluster content beneath it, all interlinked, which builds topical authority and improves your odds of being cited in AI answers.

Is content marketing still worth it if search demand is falling?

Yes, but the goal shifts from clicks to citations. Australian search demand fell 38% in 2026 as AI answers scaled, and 37.8% of commercial searches now show an AI Overview, so the businesses that capture the attention that remains are the ones cited in those answers.

How long does a content marketing strategy take to work?

Most businesses see traction in three to six months. Original research and answer-led content can be picked up and cited faster.

Is there a free content marketing strategy template?

Yes. Use our free one-page template and 90-day calendar, or generate a tailored strategy with the interactive tool on the page.

AI Max for Search: What It Is and When to Use It (2026)

Benjamin Paine — Sun, 07 Jun 2026 07:15:39 +0000

Google is pushing AI Max for Search harder than anything since Performance Max.

If you run Google Ads, you have seen the prompts: switch on AI Max, get more conversions, one click. From September 2026, some of it stops being optional.

Here is the honest version, from actually running it.

AI Max is not a new strategy.

It is reach extension for broad match, dressed up as an upgrade, and the early results, ours included, are underwhelming.

But there is a twist…

Google is folding Dynamic Search Ads into AI Max, so for a lot of accounts the question is no longer whether you use it, only when and how it is configured.

This is what it actually is, why Google wants you on it, who it genuinely helps, and how to run it for our Google Ads clients without losing control.

What AI Max for Search actually is

AI Max for Search is a bundle of three automation features you switch on inside a normal Search campaign:

Search-term matching. Finds queries beyond your keywords, using broad match expansion and keywordless matching. This is the engine of the whole thing.
Text customisation. Google generates and rewrites your headlines and descriptions to suit each query.
Final URL expansion. Sends the click to whichever page on your site Google decides fits best, not just the landing page you chose

Turn the suite on and Google also folds in what used to be separate:

Dynamic Search Ads, automatically created assets, and campaign-level broad match.

From September 2026 DSA campaigns still running those legacy features are being auto-upgraded to AI Max, with your existing URL controls preserved.

14% 27%

Google’s claim is up to 14% more conversions at a similar cost per acquisition, rising to 27% for accounts still leaning on exact and phrase match.

Worth knowing, with two caveats: the 14% figure excludes retail, and these are Google’s numbers, not independent ones.

Strip away the branding and it is broad match, extended

Here is the part the launch material skates over.

The core of AI Max, search-term matching, is an expansion mechanism. It is broad match plus keywordless matching, reaching searches your keywords would never have caught.

That 27% figure is the giveaway… the upside is biggest for exact and phrase-match accounts precisely because AI Max opens up query volume they were not previously bidding on.

So the right mental model is not “AI Max, the smarter campaign.” It is “broad match, pushed further.”

That is genuinely additive for a disciplined account with untapped query volume, and a fast way to waste money on everything else.

Why we believe Google is pushing it so hard

Be honest about the incentive.

Automated systems like AI Max improve with usage.

The more advertisers switch it on, the more data Google has to refine the matching, the bidding and the copy.

Adoption is the roadmap.

You can see it in how the controls are being released.

Brand inclusions and exclusions, the settings that stop your ads showing on the wrong branded queries, are now locked behind AI Max. If you want that brand safety, you have to opt in.

That is not a coincidence, it is a nudge.

None of it is sinister, it is how platforms grow features, but it means the default “turn it on” prompt is built for Google’s benefit first and your account second.

Why it matters regardless

This is the part that overrides the “is it any good” debate.

Google has confirmed Dynamic Search Ads is being deprecated and folded into AI Max, and from September 2026 campaigns using DSA, automatically created assets and campaign-level broad match are being auto-upgraded automatically.

For a large share of accounts, AI Max is not a decision you get to avoid. It is arriving on a schedule, and the only real choices are timing and configuration.

The worst outcome is letting it switch on by default, unconfigured, and finding out later.

What we are seeing in real accounts

We manage Google Ads for more than 250 businesses, with 98% client retention, across $10m+ in managed ad spend.

We have started moving and testing accounts onto AI Max ourselves.

So far, the results are underwhelming…

Outside a specific account profile, the expansion pulls in looser, lower-intent traffic that needs heavy negative-keyword work, and the conversion lift does not reliably show up.

It will probably improve as the system gathers data, which is the whole reason for the push.

But “it will likely get better later” is not a reason to hand over your budget now.

Who it actually helps, and who it burns

The profile that benefits is consistent, and in our experience it is worth testing when:

Your campaigns are exact and phrase-match heavy with untapped query volume. This is the profile behind the 27% claim, because there is genuinely new high-intent search to find.
You have 100+ conversions a month, so the system has enough signal to learn from.
You have a real budget, around 15x your target CPA per day, roughly $750/day, not Google’s $50 floor, which produces a technically enabled but practically hobbled campaign.
You have a team that will actually audit the search-term report, because that is where this is won or lost.

It is likely to inflate cost when:

You run retail or ecommerce at scale (Google’s 14% benchmark explicitly excludes retail).
You do lead generation without offline or CRM conversion tracking. Without that data feeding back, AI Max optimises for form volume, not lead quality, so cost per lead can improve on paper while cost per qualified lead gets worse.
You are on a low budget, below that 15x-CPA threshold.
Your account is already saturated with broad match, DSA and Performance Max, so there is little new ground for AI Max to find.

How to run it without losing control

If you do test it, or you get auto-upgraded, these are the guardrails:

Run it as a 50/50 Experiment, not a wholesale switch. Google’s own Experiments feature lets you measure AI Max against your existing setup instead of trusting a blended number.
Start with search-term matching only. Turn the three features on one at a time so you can isolate what is actually driving any change.
Exclude Search Partners from day one. In our accounts, Search Partner traffic converts far worse than Google Search, so cut it before it drains the test.
Build your negative keywords before launch, not after. With expansion turned on, the negatives are the brakes, and you want them on first.
Set brand inclusions and exclusions, and lock your copy. Use the brand controls so you are not expanding onto off-brand queries, and protect your headlines from text customisation rewriting them badly.

Judge it on a business metric, not blended CPA. Cost per qualified lead, or revenue per customer. The conversions AI Max finds tend to carry lower order values, so a flat CPA can hide a real drop in quality. This sits alongside Performance Max as another automation layer that rewards tight control and punishes set-and-forget.

The Bottom Line

AI Max for Search is a reach lever, not a revolution, and with DSA being folded into it, it is coming to most accounts whether you like it or not.

So configure it deliberately rather than let it default on.

In the right profile, an exact and phrase-match account with untapped volume, real budget and a team watching the search terms, it is worth a controlled test.

In the wrong profile it quietly inflates cost.

For most of our service-business and lead-generation clients, the caveat that bites is offline conversion tracking.

If Google cannot see which leads actually became customers, AI Max will happily buy you more of the cheap, low-quality ones. Fix the tracking first, then test.

Want to know whether AI Max is right for your account, or whether your September auto-upgrade is about to cost you? Get a free Google Ads audit, or talk to our team.

Frequently Asked Questions

Is AI Max replacing Dynamic Search Ads?

Yes. Google is deprecating Dynamic Search Ads and folding the technology into AI Max. From September 2026, campaigns using DSA, automatically created assets and campaign-level broad match are being auto-upgraded to AI Max, with your legacy URL controls preserved.

Does AI Max actually work?

Google claims up to 14% more conversions at a similar CPA, rising to 27% for exact and phrase-match-heavy accounts, with retail excluded from the 14%. In practice it is more mixed: it performs for that specific profile and tends to inflate cost outside it, and in our own accounts so far the results have been underwhelming.

When is AI Max worth testing?

When your campaigns are exact and phrase-match heavy with untapped query volume, you have 100+ conversions a month, a budget around 15x your target CPA (roughly $750/day, not Google’s $50 minimum), and a team that will audit the search-term report.

Can I opt out of AI Max?

Yes. You can toggle off the whole suite, or opt out of individual features (search-term matching, text customisation, final URL expansion) one at a time. With the September auto-upgrade coming, decide deliberately rather than letting it default on.

What is the biggest risk for lead-gen businesses?

Conversion tracking. Without offline or CRM data feeding back to Google, AI Max optimises for form submissions regardless of quality, so your cost per lead can fall while your cost per qualified lead rises. Get offline conversion import in place before you test.

About the figures: the 14% and 27% claims and the September 2026 auto-upgrade are Google’s own announcements, worth confirming at publish time since this area is moving fast.

The thresholds, recommendations and performance observations here come from Digital Nomads HQ’s own account management.

Google Ads Audits in 2026: The Checklist Everyone Else Is Still Using Is Wrong

Benjamin Paine — Thu, 04 Jun 2026 02:01:24 +0000

TL;DR

Most Google Ads audit checklists were written for a platform that no longer exists.

They check keywords, Quality Score, and ad extensions while missing the things that actually cost you money in 2026: broken consent infrastructure, AI campaigns burning budget on irrelevant queries, attribution models that inflate your ROAS, and signal architecture that starves the algorithm of the data it needs. We audit over 250 Google Ads accounts across Australia. Here is what a real audit looks like now.

Most Google Ads Audits Are Sales Pitches Disguised as Strategy

Search “Google Ads audit checklist” and you will find 50 articles that all say the same thing. Check your keywords. Review your match types. Look at your Quality Score.

Make sure you have ad extensions. Optimise your bids.

That advice was fine in 2022. It is dangerously incomplete in 2026.

Google Ads is not the same platform it was two years ago.

The matching system runs on Gemini. Smart Bidding makes decisions using signals you cannot see. Performance Max blends five channels into one black box.

AI Max is rewriting your ads and expanding your queries in real time. And from June 15, your consent infrastructure determines how much data the algorithm even has to work with.

An audit that checks surface metrics while ignoring the data layer underneath is not an audit. It is a comfort blanket.

We’ve managed over 500+ Google Ads accounts across Australia.

We audit new client accounts every week, if not every day!

Here is what we actually look for and why the standard checklist misses the expensive problems.

Why "Free Google Ads Audits" Are Almost Always Useless

Let us be direct about this. The “free Google Ads audit” that most agencies offer is a lead generation tool. Not a diagnostic one.

Here is what a typical free audit checks:

Click-through rate against industry benchmarks
Whether you have sitelink extensions
Keyword count and match type distribution
Quality Score averages
Budget utilisation percentage
Basic conversion tracking presence

These are surface metrics.

They tell you something is happening but not why.

A doctor who only checks your temperature and blood pressure is not giving you a full health assessment. Same principle.

The problems that actually cost Australian businesses money are underneath the surface.

They live in your consent configuration, your attribution model, your conversion action hierarchy, your signal density, and the quality of the data your automated campaigns are learning from.

A real audit takes 4 to 8 hours of expert analysis.

It costs money. And it should.

If someone is offering to audit your account for free, they are looking for easy wins to sell you on, not doing the deep diagnostic work that matters.

Our take:

We still offer a complimentary account review for prospective clients. But we are honest that it is a review, not a full audit. A proper audit goes deeper and costs accordingly. The distinction matters because the things that cost you the most money are the things a quick review will never catch.

What Changed: Auditing in 2024 vs 2026

Two years ago, you controlled Google Ads directly.

You chose keywords, set bids, wrote ad copy, and picked landing pages. The audit framework matched that control: check each lever, see if it is set correctly.

In 2026, you do not control most of those levers anymore. You influence them.

Google’s Gemini models now decide what queries your ads show for.

Smart Bidding decides what you pay.

AI Max rewrites your headlines and descriptions.
Performance Max chooses which channels to run on.

Your job has shifted from operating the machine to feeding the machine the right data and setting the right guardrails.

This means the audit has to shift too. Here is the difference:

The old audit caught easy problems.

The new audit catches expensive ones. Both matter.

But if you are only doing the first, you are leaving the big money on the table.

1. Consent Infrastructure Is Now the Foundation of Everything

This is the single most overlooked audit item in Google Ads right now.

And it is about to become urgent.

From June 15, 2026, Google Ads stops referencing Google Analytics settings for advertising data. It now relies exclusively on Consent Mode signals.

Specifically the ad_storage parameter.

If a user does not grant ad_storage consent through your Consent Management Platform, Google Ads collects no advertising data from that session.

Think about what that means for Smart Bidding.

The algorithm learns from conversions. If your consent banner is misconfigured and only 40% of users grant consent, Smart Bidding is learning from 40% of your data. It is making bid decisions based on an incomplete picture.

Here is what we check:

Is your CMP actually implemented correctly? We see consent banners that look functional but are not passing the right signals to Google Tag Manager. The banner exists but it does nothing.
What are your consent rates? Anything below 70% means significant data loss. Below 50% means your Smart Bidding is essentially guessing.
Is Enhanced Conversions enabled? This sends hashed first-party data back to Google and helps fill the gap that consent refusals create.
Is Google Consent Mode v2 deployed? Version 1 does not support the granular signals Google now requires. If you have not upgraded, you are running on the old framework and it will stop working properly.

Deadline alert:

June 15, 2026 is 11 days away. If your consent infrastructure is not ready, your Google Ads campaigns will start losing signal data. This is not optional. Check this now.

2. Signal Architecture: The Layer Most Audits Do Not Know Exists

This concept was best articulated by Jay Stampfl at Search Engine Land earlier this year.

The idea is straightforward: in 2026, you do not control Google Ads directly.

You control the signals that the AI uses to make decisions. The quality of those signals determines the quality of your results.

Signal architecture has three components:

Signal quality

Are you feeding the algorithm the right conversion data?

This is where we find the most expensive mistakes.

A lead generation client optimising for raw form fills is giving Google a terrible signal. Not all leads are equal. A tyre-kicker who fills out a form and never answers the phone is counted the same as a $50,000 contract.

Smart Bidding treats them identically. The fix is importing offline conversion data. Feed back which leads became qualified, which booked meetings, which closed. Journey-aware bidding is built specifically for this.

For ecommerce, the signal quality question is different. Are you passing accurate revenue values? Are returns and refunds being fed back? Is the revenue inclusive or exclusive of GST? Getting this wrong means your Target ROAS is based on inflated numbers.

Signal density

Google recommends 30 or more conversions per month per campaign for Smart Bidding to work effectively. In Australia, many businesses do not hit that threshold.

A niche B2B company spending $3,000 a month might generate 8 conversions.

Smart Bidding does not have enough data to learn.

In these cases, you need strategies to increase density: consolidating campaigns, using broader conversion actions as micro-conversions, or using portfolio bid strategies that pool data across campaigns.

We see accounts all the time where the previous agency has split campaigns so granularly that no individual campaign has enough data to optimise. Beautiful structure. Terrible performance.

Signal selectivity

This is about what data you exclude.

Brand search is the biggest culprit.

If your Performance Max campaign is capturing branded searches, your ROAS looks amazing. But those customers were already going to buy from you. The campaign is taking credit for demand it did not create. We see this constantly.

A PMax campaign reporting a 12:1 ROAS but half the conversions are brand queries that would have happened anyway.

A proper audit separates branded from non-branded performance. If you cannot see that split, you do not know what your campaigns are actually delivering.

3. AI Max and Performance Max: Auditing the Black Box

Google is pushing every advertiser toward automated campaign types. AI Max for Search launches with mandatory DSA migration in September 2026. Performance Max has been the default shopping campaign for two years. These campaigns work differently and they need to be audited differently.

AI Max query quality

AI Max uses Gemini to expand your queries beyond traditional keyword matching. In theory, it finds high-intent searches you would have missed. In practice, it sometimes matches your ads to queries that have no connection to your business.

We audit the search terms report for AI Max campaigns specifically looking for:

Relevance drift. Queries that are topically adjacent but not commercially relevant. A plumber showing for “how to fix a leaky tap DIY” is getting traffic that will never convert.
Competitor queries. AI Max will match you to competitor brand searches unless you explicitly exclude them.
Informational intent. Queries where the user is researching, not buying. These burn budget fast on broad topics.

The fix is not to turn AI Max off. It is to set proper brand exclusions, add negative keywords aggressively, and review the search terms report weekly during the first 30 days.

Performance Max placement quality

PMax runs across Search, Shopping, Display, YouTube, Gmail, and Discover. The problem is that it does not tell you how much it spends on each channel by default.

Here is what we check:

Channel distribution. Go to Reports, then Other, then Performance Max Placements. If more than 10-15% of spend is going to Display, investigate. Display within PMax often serves ads inside mobile games and apps where accidental clicks drive up costs with zero conversion intent.
Asset group performance. Are any asset groups rated “Low” or “Poor”? These drag down the entire campaign.
Brand traffic cannibalisation. Is PMax eating your brand searches? Add brand exclusions at campaign level. This is the single most impactful PMax optimisation most accounts are missing.
Search theme alignment. Are your search themes actually aligned with what you sell, or are they leftover from initial setup and never updated?

What we find:

Across our client base, roughly 6 in 10 Performance Max campaigns we audit have no brand exclusions set. This means the campaign is silently capturing branded traffic and reporting inflated ROAS. When we add brand exclusions, reported ROAS drops but actual incremental revenue stays the same or improves because the budget shifts to prospecting.

4. Attribution: Your ROAS Is Probably Wrong

Google moved every account to data-driven attribution as the default model.

This was the right decision. But it created a comparison problem.

If you are comparing this month’s performance to the same month last year, and you were on last-click attribution then, the numbers are not comparable.

Data-driven attribution distributes credit across touchpoints. It makes campaigns that assist conversions look better and campaigns that close conversions look worse compared to last-click.

What we audit:

Attribution model consistency. Are all conversion actions using the same model? We regularly find accounts where the primary conversion is on data-driven but secondary conversions are still on last-click. The data is contradictory.
Cross-platform reconciliation. If you are running Google and Meta together, their attribution models disagree. Google uses data-driven. Meta uses click-through plus the new engage-through window. Both platforms will take credit for the same conversion. If you add up both platforms’ reported conversions, you will overcount.
Incrementality. The hardest question in advertising: would this conversion have happened without the ad? Brand search campaigns, retargeting, and PMax all tend to capture demand rather than create it. A real audit examines whether your campaigns are driving new business or just taking credit for existing demand.

For businesses running across multiple platforms, proper attribution setup is not optional anymore. It is the difference between knowing what is working and guessing.

5. Australia-Specific Considerations Nobody Else Covers

Most Google Ads audit content is written from a US perspective. The Australian market has specific dynamics that affect how you should audit.

GST and your actual ROAS

Google charges 10% GST on all ad spend in Australia. If your business is registered for GST, you claim this back on your BAS. If you are not, that 10% is a direct cost increase.

But here is what matters for auditing: your ROAS calculation needs to account for this. If your account reports $10 in revenue for every $1 in spend, your actual ROAS is closer to 9:1 after GST on spend. If you are also selling GST-inclusive products, you need to back out GST from revenue too. We see ROAS figures that look strong until you apply real accounting.

Smaller market, different thresholds

Australia has 26 million people. The US has 330 million. Search volumes are proportionally smaller. This has practical implications.

Smart Bidding needs 30 conversions per month to learn effectively. In a US metro, hitting that threshold on a $5,000 monthly budget is easy. In an Australian regional market, the same budget might generate 12 conversions. The algorithm does not have enough data.

We audit for this specifically. If a campaign is below the learning threshold, we either consolidate campaign structure, broaden targeting, or use portfolio bid strategies that pool data. Running granular campaigns with insufficient data is one of the most common mistakes we see in AU accounts.

Location targeting traps

Default location targeting in Google Ads is set to “presence or interest” which means your ads can show to anyone who shows interest in your target area, not just people physically there.

For a local trades business targeting the Sunshine Coast, this means you might be paying for clicks from people in Sydney who searched something mentioning the Sunshine Coast.

We check every account for this. The fix takes 30 seconds but most agencies leave it on default.

6. Lead Gen and Ecommerce Are Two Completely Different Audits

We work across both lead generation and ecommerce clients. The audit framework is fundamentally different for each.

Lead generation audit priorities

Conversion quality, not quantity. Raw form fills tell you nothing. You need to know which leads became customers. Are you importing offline data back into Google Ads? If not, the algorithm is optimising for volume, not value.
Search term pollution. Broad match in lead gen pulls in job seekers, support queries, and competitor research. The search terms report is your first stop.
Call tracking. If phone calls drive revenue and you are not tracking them as conversions, your campaign data is missing half the picture.
Landing page friction. Lead gen landing pages need to qualify and convert simultaneously. Too much friction and you lose volume. Too little and you get junk leads.

Ecommerce audit priorities

Product feed quality. This is your most important asset. Missing attributes, incorrect categories, thin descriptions. Google’s AI-powered Shopping Ads are built on your feed data. Bad feed, bad ads.
Revenue accuracy. Are purchase values correct? Are refunds being tracked? Is revenue GST-inclusive or exclusive? Getting this wrong makes every ROAS calculation meaningless.
Shopping vs PMax split. Standard Shopping gives you more control and visibility. PMax gives you reach. The right mix depends on your catalogue size, margins, and competitive landscape.
Cart abandonment retargeting. Is your remarketing actually reaching cart abandoners with specific products, or is it showing generic brand ads to everyone?

7. What to Ask Your Agency (Or What to Ask Yourself)

Whether you are auditing your own account or evaluating whether your agency is doing its job, these are the questions that matter:

“What conversion action are our campaigns actually optimising for?” If the answer is “all conversions” or they do not know, that is a red flag. Campaigns should optimise for the conversion that represents actual business value.
“Can you show me branded vs non-branded performance separately?” If they cannot split this out, they cannot tell you whether your campaigns are creating new demand or capturing existing demand.
“What is our marginal CPA at current spend?” Your first 50 leads might cost $40 each. The next 50 might cost $120. Are you spending past the point of diminishing returns?
“What percentage of our PMax spend goes to Display?” If they do not know, they have not checked the placement report. That is a problem.
“Is our Consent Mode configured for the June 15 changes?” If they do not know what you are talking about, you have a bigger problem.
“What happens to our bidding when we scale spend 30%?” A good agency can tell you where the diminishing returns curve starts. A bad one just says “we will monitor it.”

The standard:

A good agency should be able to answer all six of these questions for your account right now. If they cannot, they are managing your spend but they are not auditing your performance.

The Bottom Line

The Google Ads audit checklist is not dead. But the 2020 version of it is. The platform has changed faster in the last 18 months than in the previous five years. Consent Mode, AI Max, Performance Max, data-driven attribution, signal architecture. These are not edge cases. They are the foundation.

If your last audit did not check your consent infrastructure, did not separate branded from non-branded PMax performance, did not evaluate your conversion action hierarchy, and did not assess whether your signal density supports Smart Bidding, then your last audit missed the expensive stuff.

We run audits for businesses across Australia every week. If you want to see what a 2026 audit actually looks like for your account, get in touch. We will tell you what is working, what is wasting money, and what needs to change.

Google AI Max: Most Agencies Will Get the Migration Wrong

Benjamin Paine — Tue, 26 May 2026 23:08:42 +0000

TL;DR

Google is collapsing the matching, copy, and landing page selection layers into Gemini. AI Max does it on paid. AI Mode and AI Overviews do it on organic.

From September 2026, DSAs and broad match get force-migrated to AI Max. Whether the algorithm performs in your account comes down to three inputs you control: landing page quality, exclusion architecture, and measurement that holds up when last-click reporting doesn’t. Get these right before September and AI Max produces the lift Google describes. Get them wrong and it spends your budget on competitor terms, irrelevant queries, and the wrong pages. The window to fix this isn’t quarters. It’s months.

On 15 April, Google confirmed that from September 2026, Dynamic Search Ads, automatically created assets, and campaign-level broad match will all be force-migrated to AI Max for Search.

From the same date, advertisers will lose the ability to create new DSA campaigns altogether. Google Ads, Ads Editor, and the API will all stop offering it as a campaign option.

Plenty of trade press coverage of the migration and plenty of how-to guides on what carries over.

Almost no one asking the question that actually matters.

If Google can absorb the keyword-targeting, copy-generation, and landing-page-selection layers into a single AI system, what exactly is the agency selling?

The signal layer

The real shift sits underneath the AI Max announcement, and it’s bigger than one product change.

For the last two decades, paid and organic search worked because there was a translation layer between user intent and what Google chose to deliver.

Agencies made their money inside that translation layer. Keyword research. Match type strategy. Ad copy testing. On-page optimisation. Bid management.

All of it was the work of converting raw business goals into the specific instructions Google needed to decide what to show.

Google has now collapsed that translation layer into Gemini.

AI Max is the paid-side version.

AI Mode and AI Overviews are the organic-side version.

The mechanism is the same in both cases: Google’s models read your content, infer the intent of the query, and decide what to surface. The advertiser or publisher supplies inputs and guardrails. Gemini does the matching.

That is not an incremental change. It is an inversion.

Paid and organic are now the same problem

We’ve been writing for a while about the two-hop citation model, where AI Overviews and ChatGPT pull from a narrow set of cited sources, and those sources in turn pull from a deeper set.

The whole thing works because the inference layer sits between the user and the original content.

The user no longer sees the SERP. The model summarises it for them.

AI Max is the same architecture applied to paid.

Your keyword list becomes a starting signal, not a boundary.

The system expands beyond it using broad match and keywordless matching.

Headlines and descriptions are generated from your landing page content (remember this!)

Final URL expansion picks the destination page. The “campaign” is no longer a set of instructions you give Google.

It’s a set of inputs the system uses to make its own decisions.

So with this being said… If Gemini generates the headlines, why is the agency billing hours for headline testing.

If keywordless matching reads the landing page, why is the agency billing for keyword research the system is going to override anyway.

What we're actually seeing

Google’s launch around the AI Max numbers got some press.

A 14% conversion lift on average.

27% for accounts heavy on exact and phrase match.

L’Oréal doubling conversion rate.

MyConnect cutting cost per lead by 13%.

Aritzia reporting an 80% sales gain.

All real, all from Google’s own reporting, and all from accounts where the conditions were already right for AI Max to work.

The lived reality across client accounts is that the foundations are often a lot messier…

The pattern we’ve seen since AI Max moved out of beta is a wide variance in outcomes that correlates almost entirely with the inputs going in.

Accounts with high conversion volume, strong landing page content, mature negative keyword lists, and clean conversion tracking produce something close to the lift Google describes.

Accounts missing any one of those produce the noise.

Search terms that don’t make sense for the business.

Ad copy that mismatches user intent.

Traffic sent to landing pages that aren’t equipped to convert it.

ROAS that goes backwards before it goes anywhere… and so on!

The specific failure modes are predictable enough to list.

AI Max bids aggressively on competitor brand terms by default, which inflates spend on traffic that was never going to convert at scale.

It leans on Search Partner inventory in a way the previous keyword-match logic didn’t, which dilutes traffic quality. Auto-generated ad copy drifts away from brand voice in ways that take a human eye to catch. Made in USA headlines paired with queries about overseas products.

Generic shop-now phrasing where the brand has a deliberate tone.

Claim language that doesn’t match what the page actually offers.

Final URL expansion sends traffic to whatever page Google decides is most relevant, including outdated pages an account team would never have run paid spend to.

And the reporting itself is unreliable.

AI Max attributes impressions misleadingly, so a chunk of what looks like AI Max lift in the dashboard is actually attribution shifting from existing match types. The lift Google describes and the lift you can actually book to the campaign are often different numbers.

AI Max isn’t broken.

It’s a delivery layer whose output quality is bounded by input quality. Strong landing pages, mature conversion tracking, clean exclusion architecture, and enough conversion volume to give the algorithm something to learn from produce the lift Google describes.

Weak inputs produce the competitor-bidding, irrelevant-query, wrong-landing-page failure modes.

In a keyword-driven world, an agency could compensate for weak inputs through better targeting.

In an AI Max world, the targeting layer is now AI. The only place to compensate is by improving the inputs themselves. The work didn’t get easier. It moved.

Where the work moved

The work didn’t disappear. It moved. Three places, specifically.

Landing pages.

Both paid and organic now read the page as the primary signal. The copy, the structure, the entity coverage, the topical depth, the schema.

All of it has more weight than it did six months ago, and this I believe will continue!

A poorly written landing page used to cost you conversion rate. Now it costs you matching quality too, because Gemini reads it to decide who you appear for. The landing page is simultaneously a paid input and an organic input. Treating them as separate disciplines is now a structural mistake.

Exclusion architecture.

AI Max is, by design, a reduced-control product.

The AI decides which queries trigger your ads. Your control sits in negative keyword lists, brand exclusions, URL exclusions, and ad group structure. Building and maintaining these well is a higher-skill task than building keyword lists ever was, because the system is more aggressive than broad match ever was.

Agencies without a real method for this will burn client budget on queries that look related and aren’t.

Measurement.

With AI Max and Performance Max blending channels and queries, last-click attribution is less honest than ever. Incrementality testing, marketing mix modelling, and qualified conversion modelling become the only credible way to know what’s working. Google announced Meridian integration into Analytics 360 at GML 2026 precisely because the measurement problem has worsened, not improved.
None of these three are jobs an account manager moving sliders inside Google Ads can do.

What expert looks like now

Setting up an AI Max campaign is trivial.

Any junior media buyer can launch one in an afternoon. The barrier to entry has collapsed.

Running an AI Max campaign that performs to an expert standard requires three skill sets that used to live in different teams.

A conversion specialist who understands the landing page as a paid input. Not “is the form working” CRO.

Page structure that maps user intent cleanly enough for the algorithm to read it.

Copy that gives Gemini something useful to extract.

Information architecture that holds up when the system picks the destination URL itself. Closer to content strategy than to traditional CRO.

A data specialist who understands the feedback loop.

Conversion tracking that captures actual outcomes, not just clicks.

Offline conversion imports for lead-gen accounts. Audience signals that strengthen Gemini’s matching. The discipline to read the search term report with enough nuance to know what to exclude and what to leave alone. Most agencies don’t have this person. They have a media buyer who occasionally checks search terms.

A marketing strategist who lays the foundation before the algorithm starts spending.

What the brand is for.

Who it’s for.

What the value proposition actually is in five words.

AI Max is brutally honest about positioning. If the strategy is woolly, the algorithm reflects it back as mismatched queries, generic copy, and budget spent on traffic that was never going to convert.

The paid ads specialist becomes a commodity. The three people behind them become the value.
For agencies, the implication is direct. If your team is structured around channel specialists, you’re staffed for the world that ended in 2025. The teams that perform under AI Max are integrated, with CRO, data, strategy, and paid sitting in the same room on the same brief, because the inputs cross domains and the feedback loops do too.

For clients running their own AI Max campaigns, the implication is harsher.

They’ll get campaigns live easily.

They’ll see the spend going out and some conversions coming in and assume the system is working. The question they won’t think to ask is what it would have looked like if the inputs had been right from the start. That gap is invisible from inside the account.

The positioning question

It runs paid and organic together, not as separate departments.

The landing page is now a paid input and an organic input at the same time. If the SEO team and the SEM team don’t talk to each other, the landing page work happens twice, badly, with different assumptions baked in.

It has proprietary intelligence, not just access to the same Google tools every other agency has. If Gemini is doing the matching, the only edge left is knowing things about the search environment that Google doesn’t surface in its own reporting.

Citation patterns in AI Overviews. Query-level performance inside AI Mode.

Real-time search demand at the suburb level. Brand sentiment inside Gemini conversations. The agencies that built this kind of intelligence in-house are about to have an unfair advantage. The agencies that didn’t are about to look interchangeable, because the underlying Gemini layer they’re all operating on is the same.

It charges on outcomes, not on hours.

Once Gemini absorbs the execution layer, the hours line item is hard to justify. What’s left is strategy, guardrail design, measurement, and landing page quality. High-impact, low-hours work. Agencies still selling time will get squeezed. Agencies selling results will be fine.

It is selective about which clients it takes on.

The new model rewards landing page quality and brand strength. Agencies dragging weak brands with thin websites through paid spend are about to get caught out, because the system now reads those weaknesses and prices them in. You can’t fix a poor brand with bid adjustments anymore. The system has read the page and made up its mind.

What this looks like in practice

We’ve been planning a launch campaign for a new venue opening later this year.

The brief, if it had landed twelve months ago, would have looked familiar. Build keyword lists. Structure ad groups by service line. Write three or four ad variants per ad group. Set up conversion tracking. Optimise bids. Standard agency work.

The brief now looks different.

Build a landing page architecture that signals intent clearly enough for AI Max to match correctly.

Write base copy that Gemini can pull from to generate variants without losing the brand voice. Construct an exclusion list that catches the obvious mismatches before they burn budget.

Set up incrementality testing so we can measure what Meta and Google are actually contributing, versus what would have converted anyway. Once those inputs are right, the campaign largely builds itself.

The hours are lower. The thinking is heavier. The cost of getting the thinking wrong is higher.

The migration playbook

Three things to do between now and September.

Audit DSA exposure across every account

Migrate before September and you choose the experiment. Migrate in September and you spend the next month firefighting search terms you didn’t choose. Same work either way. The difference is whether you do it before or after the algorithm has started spending money on the new logic. Enable AI Max account-wide rather than in a single test campaign. Partial adoption muddies the reporting.

Treat the landing page audit as the highest-impact work of the next ninety days

AI Max reads pages to decide who you appear for and what copy it generates. AI Mode and AI Overviews are doing the same on organic. A page that’s vague about what it sells, who it’s for, and what action it wants will pull mismatched queries on paid and lose citation eligibility on organic. Most agencies won’t touch landing pages during a DSA migration because they aren’t a “PPC deliverable” in the old org chart. That’s the gap to close.

Stop running last-click as the primary measure

With AI Max and Performance Max overlapping queries and channels, last-click overstates paid one month and understates it the next. The Meridian integration into Analytics 360 is Google admitting last-click is broken inside their own product. Move clients to incrementality testing and marketing mix modelling now, even a rough first version. The alternative is answering uncomfortable questions about why reported ROAS doesn’t match the revenue line.

The September deadline isn’t a deadline for a Google migration. It’s a deadline for restructuring how you work.

The closing point

There’s a line from a senior Google executive at GML 2026 worth taking seriously. The pitch to agency partners was that they’d be able to service 50 clients with the team that used to be stretched thin across 10.

It’s a true statement, in the sense that the execution layer no longer needs human hours. It’s also a trap, because 50-client agencies running on the same Gemini outputs will all produce the same results.

The interesting agencies, two years from now, will be the ones that built proprietary intelligence underneath the Gemini layer, so their inputs are better than everyone else’s. That’s the only place an edge can come from when the matching, the copy, and the destination are all being decided upstream by the same model.

The September DSA deadline is the small story. The signal layer collapse is the big one. Most agencies haven’t noticed yet, which means there’s still time for the ones that have.

Google I/O 2026: What Just Changed and What We Are Telling Our Clients

Benjamin Paine — Wed, 20 May 2026 02:12:01 +0000

TL;DR

Google I/O 2026 just confirmed what we have been warning clients about for two years. Google is no longer just a search engine – It is an AI assistant that answers questions, builds tools, and processes transactions without users ever leaving Google. AI Mode has 1 billion monthly users. AI Overviews appear on 48% of queries. Google just launched AI agents that search for you in the background, a Universal Cart coming to Australia allowing purchases to happen without clients even visiting your website, and AI-generated interactive tools that replace the kind of content most businesses rely on for traffic (how-to’s, what Qs etc.). This is not a future problem… this is happening. Here is what we are doing about it for our clients and what you should be doing too.

Biggest update to search in 25 years

I do my best to watch every Google I/O keynote, despite the horrible alignment with the AEST timezone. Every time the announcements are incremental, whether everyone agrees or not, the innovation, better models, faster loading, shinier features… they are great.

Often, we take note, adjust a few things, and move on.

This year hits a little different.

The 2026 Search announcements are not incremental.

They represent a fundamental shift in what Google is and how people will interact with it. And if you run a business that depends on search traffic, paid ads, or e-commerce in Australia, you need to understand what just changed.

I am not going to recap every announcement.

I am going to focus on the ones that directly affect our clients and what we are doing about each one.

1 Billion People Now Use AI Mode. We Saw This Coming.

AI Mode has passed 1 billion monthly users with queries more than doubling every quarter. Gemini 3.5 Flash is now the default model powering it globally.

One in eight people on the planet used AI Mode last month. That is not a beta. That is not an experiment. That is a primary interface – Crazy numbers.

This month we analysed 116,918 Australian Google search results and found that AI Overviews were triggering on 37.8% of domestic queries, well above the global average at the time.

We said then that this was going to accelerate and the global data shows AI Overviews are now on 48% of all queries. AI Mode usage is growing faster than any Google product since Gmail.

We have been rebuilding our SEO campaigns around this reality for the last 12 months and if your agency is still optimising purely for traditional organic rankings and measuring success by “keywords on page one,” they are solving last year’s problem.

Search Agents Are the Biggest Shift Since Mobile

This is the announcement I am most focused on.

Google is launching Search agents – AI agents you create inside Google Search that run in the background 24/7.

So, simply… give them a task – They scan blogs, news, social media, shopping data, and more in real time. When something matches, they notify you.

The examples Google gave were consumer-focused.

An rental hunting agent.

A sneaker drop agent.

But think about what this means for B2B.

A procurement manager sets up an agent to monitor pricing changes across suppliers.

A marketing director creates an agent to track competitor announcements.

A business owner has an agent watching for regulatory changes in their industry.

This is crazy!

Search stops being something you do… it becomes something that runs for you.

Why This Should Change How You Think About Your Website

Every business I talk to thinks about their website from a human perspective. How does it look? Is the copy compelling?

Does the navigation make sense? Those things still matter. But AI agents do not care about your hero image or your brand story.

An AI agent scanning on behalf of a user is going to check structured data. Product specs. Pricing. Availability. Location. Opening hours.

Service descriptions in machine-readable formats. If that information is not in your schema markup, your product feeds, and your structured data, the agent will skip you and surface a competitor who made it easy.

We have been pushing structured data implementation across all of our SEO clients for years. Most businesses treat it as a “nice to have” technical SEO task. After this announcement, it is the foundation of being discoverable in the next generation of search.

Honest take: Most Australian business websites we audit have incomplete or missing structured data. Basic stuff – LocalBusiness schema, product schema, FAQ schema, service schema. It takes a few hours to implement properly. But without it, an AI agent cannot read your website. You are invisible to the fastest-growing way people will discover businesses. We are running structured data audits for all managed clients this month. If you are not a client, you should be doing this yourself or getting someone to do it for you.

Universal Cart Is Coming to Australia. This Changes E-Commerce.

Google launched Universal Cart, a shopping cart powered by Gemini that works across merchants, across Search, YouTube, Gmail, and Gemini.

A customer adds a product while watching a YouTube video. Adds another while browsing Search. The cart tracks price history, finds deals, alerts to restocks, and handles checkout across multiple merchants in one place.

The infrastructure behind it is called the Universal Commerce Protocol (UCP). And Google confirmed it is expanding to Australia in coming months.

I want to be direct about what this means. Google is building itself into the middle of every online transaction.

The customer discovers, compares, and buys without ever visiting your website.

Your Shopify store, your WooCommerce site, your custom e-commerce build – they become fulfilment backends while Google owns the customer relationship.

That sounds alarming.

And for businesses that are going to do nothing… it should be!

But for businesses that integrate early, it is an opportunity.

You get a buy-now button inside AI Mode, YouTube, and Search. Your products become purchasable in the moment of discovery, not after a customer clicks through, loads your site, creates an account, and goes through checkout. The friction drops dramatically.

What we are doing: For our e-commerce clients, we are already auditing Google Merchant Centre feeds, product data accuracy, and structured data readiness for UCP integration. When it launches in Australia, we want our clients ready on day one. The pattern here is identical to Google Shopping feeds. The businesses that connected their feeds early dominated the Shopping tab. The ones that waited 12 months were playing catch-up while competitors took their market share. Do not make the same mistake twice.

The Agent Payments Protocol Is Worth Watching

Google also announced AP2 (Agent Payments Protocol), which lets AI agents make purchases on behalf of users within guardrails – spending limits, category restrictions, approval requirements. The user sets the rules, the agent shops and buys.

This is early days. But picture this in 18 months: a customer tells their Google agent “reorder my usual supplements when they drop below $40” or “book the cheapest direct flight to Melbourne for the second Friday of June.”

The agent monitors, finds the match, and completes the transaction.

The businesses that show up in that agent’s scan are the ones with clean product data, competitive pricing, and UCP integration.

Everyone else does not exist in that transaction.

Google Now Builds Tools Inside Search Results. This Kills a Content Category.

Google is putting code generation directly into Search through a system called Antigravity.

You search for something that would benefit from an interactive tool, and Google builds it for you on the spot.

A wedding planning checklist with venue recommendations from Google Maps, weather data for your date, and local vendor reviews.

A moving budget calculator with real rental data and cost estimates for your area. A fitness tracker that pulls in your data. Custom, interactive, built in seconds. Free for everyone this summer.

I will be honest… this worries me for a category of content we have helped clients produce for years.

Think about the tools and resources businesses publish to attract organic traffic. Budget calculators. ROI estimators. Comparison checklists. “How much does X cost” guides with interactive elements.

If Google can generate a better, more personalised, data-rich version of that tool directly in the search result, the user has no reason to visit your website.

We have already started shifting our content strategy recommendations away from tool-based and template-based content toward content that cannot be generated on the fly:

Original research with proprietary data (like our 116,918 SERP analysis)
Real client case studies with specific numbers and context
Expert opinion that takes a clear position based on experience
Industry-specific observations from practitioners who manage real campaigns
Contrarian takes that challenge the conventional wisdom with evidence
Generic how-to content is going to get eaten alive by Antigravity.

But content that comes from doing the work? That is harder to replicate.

An AI can build you a budget calculator. It cannot tell you what we saw happen to a client’s CPA when they restructured their Google Ads account last quarter.

Personal Intelligence Changes the Retargeting Playbook

Google is rolling out Personal Intelligence globally – 200 countries, 98 languages, no subscription required.

You connect your Gmail, Google Photos, and soon Calendar to AI Mode.

Then you can ask things like

“what was that hotel I stayed at in Melbourne?”

“what did I order from that skincare brand last month?”

and Google searches your personal data to find it.

From a marketing perspective, this is subtle but important.

Traditional retargeting is built on the assumption that people forget. They visit your site, leave, and you need to remind them through display ads, remarketing lists, and email sequences.

But if a customer can just ask Google “what was that thing I was looking at?” and Google pulls it from their email receipts and browsing history, the retargeting function partially moves to Google. The user does not need to see your remarketing ad. They do not need to remember your brand name. They ask their AI assistant and it finds you.

This does not mean remarketing is dead.

We still see strong performance from first-party remarketing lists, Customer Match, and server-side tracking. But it does mean the landscape is shifting. Your transactional emails, your order confirmations, your receipts – these become discoverable content that Google can surface to bring a customer back. Making sure your email communications are clear, well-structured, and contain proper product information matters more than it used to.

The Search Box Redesign Changes How Queries Form

The search box itself has been rebuilt. It dynamically expands, accepts images, files, videos, and browser tabs as inputs, and uses AI-powered suggestions that go beyond autocomplete.

You can flow from an AI Overview directly into a conversational AI Mode exchange with your context carrying through.

This matters for keyword strategies in both paid and organic optimisation.

The queries people type are getting longer (long-tail), more specific, and more conversational. Multi-modal queries where someone takes a photo of a product and asks “where can I buy this in Brisbane” are going to become common.

For paid search, this means traditional keyword-based campaign structures need to evolve. We have written about AI Max for Search and how Google is pushing toward intent-based matching rather than keyword matching.

The search box redesign accelerates this. If a user is having a conversation with Google about a purchase decision, the traditional model of bidding on exact match keywords does not capture that interaction.

Campaign structures need to account for conversational, multi-step, multi-modal queries.

For SEO, it reinforces the importance of entity-based optimisation and topical authority over individual keyword targeting. Google is not matching queries to pages anymore. It is understanding intent, context, and conversation. Your content needs to answer the full scope of a topic, not just target one keyword variation.

The Pattern Across Everything Google Is Doing

Step back and look at every major Google announcement this year.

AI Max for Search. Performance Max expansion. Journey-aware bidding. AI Overviews at 48%. Search agents. Universal Cart. Antigravity. Personal Intelligence.

They all point in the same direction.

Google is moving from being a platform that sends people to websites to a platform that keeps people inside Google. It wants to answer the question, complete the task, and close the transaction. Your website becomes the backend. Google becomes the interface.

This is not inherently good or bad. It is a reality you need to build around.

The businesses that will thrive in this environment are the ones that:

Own their audience directly through email lists, CRM databases, and customer communities that do not depend on Google sending traffic
Have clean, structured data that AI agents and Google’s systems can read, understand, and surface
Invest in genuine expertise that produces content, research, and insights an AI cannot generate on its own
Integrate with Google’s commerce infrastructure so they are present in Universal Cart, AI Mode, and YouTube commerce surfaces
Feed their ad platforms quality data because automation is getting smarter but it is only as smart as the data you give it
Build brand strength because branded search is the most insulated channel from AI disruption – people searching for you by name still land on your website

None of this is new advice. We have been saying every one of these things for the last two years. Google I/O 2026 just made it undeniable.

What We Are Doing for Our Clients Right Now

Here is the specific action we are taking across our managed client accounts in response to I/O 2026:

Structured data audits across all SEO clients.
We are checking schema markup (though there isn’t strong correlations to organic SEO performance as of yet with this… it’s future proofing), product feeds, LocalBusiness data, FAQ schema, and service schema. If an AI agent cannot read it, it needs to be fixed.
UCP readiness for e-commerce clients.
Auditing Merchant Centre feeds, product data accuracy, pricing feeds, and checkout integration readiness for when UCP launches in Australia.
Content strategy pivots.
Shifting production away from generic informational content toward original research, case studies, expert commentary, and opinion pieces. If an AI can generate it, we are not writing it.
SEO reporting evolution.
Adding AI Overview citation tracking, brand search volume monitoring, and entity visibility to our standard SEO reporting alongside traditional rankings and traffic.
Paid search campaign reviews.
Making sure campaigns are configured for AI Mode ad placements (Sponsored Stores, Direct Offers) and conversational search surfaces. Reviewing AI Max migration readiness and journey-aware bidding prerequisites.
First-party data infrastructure.
Pushing CRM integration, offline conversion imports, and Customer Match setup for every client that does not already have it. The competitive advantage across every platform in 2026 is data quality, not campaign cleverness.
Client education.
Sending this article to every client. Having conversations about what these changes mean for their specific business and what needs to shift.

The Uncomfortable Truth and the Opportunity

Here is the uncomfortable truth. If your business relies entirely on Google to send you customers, you are building on rented land and the rent is going up.

Organic traffic from Google will keep declining. The cost of paid traffic will keep rising as ad inventory shifts from traditional search to AI surfaces. The middleman is getting more powerful, not less.

But here is the opportunity. Most businesses are not going to do anything about this. They are going to read articles like this one, nod, and go back to whatever they were doing before. That creates an enormous advantage for the businesses that actually move.

Everything Google announced at I/O 2026 reinforces those fundamentals. The businesses that are built on them have nothing to worry about. The ones that are not should start now.

Journey-Aware Bidding: What Google’s New Lead Gen Update Means (2026)

Benjamin Paine — Tue, 19 May 2026 06:31:24 +0000

TL;DR

Google just launched journey-aware bidding in beta. It lets Search campaigns on Target CPA learn from your full sales pipeline – not just the front-end form fill. If you have been importing offline conversions and connecting your CRM, this is the payoff. If you have not, you are now locked out of the best bidding innovation Google has shipped for lead gen in years.

The Problem Every Lead Gen Advertiser Knows

If you run lead generation on Google Ads, you already know this pain.

You set a Target CPA. You tell Google to get you leads at $50 each. Google does exactly that. It finds people who fill in forms. It optimises beautifully for the conversion event you gave it.

But Google has no idea what happens after the form. It does not know that 80% of those leads never answer the phone. It does not know that leads from certain keyword themes close at half the rate of others. It cannot see that the cheap leads from mobile at 11pm are almost always junk, while the expensive ones from desktop at 2pm on a Tuesday turn into $30,000 contracts.

Google thinks it is doing a great job.

Your CPA looks healthy.

Your sales team disagrees…

This is the fundamental problem with lead gen bidding – The algorithm optimises for whatever you tell it to optimise for. If you tell it to optimise for form fills, it gets very good at finding people who fill in forms. That is a completely different thing from finding people who become customers.

What Journey-Aware Bidding Actually Does

Journey-aware bidding, which entered beta on May 7, 2026, changes the way Smart Bidding learns for lead generation campaigns.

Here is the core idea.

Instead of the algorithm only seeing your primary conversion action (the form fill, the phone call, whatever you are bidding on), it now learns from your entire lead-to-sale journey.

Every stage you track – form submission, marketing qualified lead, sales qualified lead, proposal sent, deal closed – feeds into the model as a learning signal.

The important distinction: Google still only optimises toward your primary biddable conversion. It is not going to start counting MQLs as conversions or inflating your numbers.

But it uses those non-biddable stages to build a more accurate prediction of which clicks are most likely to reach the end goal.

Think of it this way.

Before, Google could see the first step and the nothing.

Now it can see the first step, the second step, the third step, and the outcome. It still only charges you for step one. But it uses the full picture to decide which step-ones to chase.

How This Differs from Value-Based Bidding

Value-based bidding (Target ROAS) has been available for years.

It lets you assign dollar values to different conversions so Google can prioritise higher-value outcomes.

So in theory, it solves the same problem…

However, in practice, most lead gen accounts cannot use it!

Target ROAS requires roughly 90 conversions in a 30-day window to function properly.

You need to assign monetary values to every conversion event.

And you need those values to be accurate and consistent, which means your CRM data has to be clean, your pipeline stages have to be standardised, and your sales team has to be disciplined about updating records.

So… problem, most lead gen businesses do not meet these requirements.

Not because they are bad at marketing… But, because they are normal-sized businesses with normal-sized pipelines and 15 to 40 leads a month, not 90.

Journey-aware bidding has a lower bar… perfect!

It works on Target CPA campaigns, which most lead gen accounts already run.

It needs 30 conversions in 30 days, not 90… Plus, it does not require you to assign dollar values.

It infers the relationship between journey stages and outcomes.

This is the key and meaningful difference.

It opens up smarter bidding to a much wider range of lead gen advertisers.

What You Need to Use It

Journey-aware bidding is not something you switch on in a menu. It requires a data foundation that most accounts do not have. Here is what is needed.

1. Offline Conversion Imports

This is the non-negotiable. You must be importing offline conversion data from your CRM back into Google Ads.
This means connecting HubSpot, Salesforce, Zoho, Pipedrive, or whatever system your sales team uses, and sending conversion events with the original Google Click ID (GCLID) or hashed user data so Google can match the outcome back to the click.

Google supports native integrations through Data Manager, Zapier connectors, Salesforce direct integration, and the Google Ads API. The method matters less than the consistency. Google recommends uploading at least daily. If you cannot manage daily, a weekly upload on a consistent schedule is the minimum.

2. Pipeline Stages Mapped as Conversion Actions

You need to create conversion actions in Google Ads for each meaningful stage of your pipeline.

A typical setup looks like this:

Form submission – your primary biddable conversion (this is what you set your Target CPA on)
Marketing Qualified Lead (MQL) – marked as a secondary, non-biddable conversion action
Sales Qualified Lead (SQL) – non-biddableProposal or quotesent – non-biddable
Closed-won deal – non-biddable

The algorithm learns from all of these stages without optimising directly toward any of them except your primary goal. It is watching the patterns to predict which early-stage clicks are most likely to progress through the full journey.

3. Sufficient Data Volume

Google states a minimum of 30 conversions in a 30-day period for the algorithm to have enough signal. That is your primary conversion action, not your pipeline stages. If you are generating fewer than 30 leads a month from Google Ads, the system will not have enough data to learn effectively.

4. Extended Attribution Windows

If you sell something with a long consideration period (B2B services, financial products, education, healthcare), set your click-through attribution window to 90 or 120 days and your view-through window to 30 to 60 days. The default 30-day click window will miss conversions that take longer to close, and the algorithm will learn from incomplete data.

Note: The biggest blocker we see is not technology. It is CRM discipline. If your sales team is not consistently updating lead stages, if your pipeline definitions are vague, if “qualified” means something different to every rep, then the data you send back to Google will be noisy. Journey-aware bidding will learn from that noise. Garbage in, garbage out still applies.

Who This Is Actually For

Journey-aware bidding is not relevant for every advertiser.

Here is where it matters and where it does not.

Strong Fit

B2B services and SaaS with multi-stage sales processes, longer sales cycles, and clear pipeline stages in a CRM
Professional services (law firms, accounting, consulting) where a lead and a client are separated by weeks of qualification
Financial services where compliance and qualification stages create natural pipeline milestones
Healthcare and allied health where enquiry-to-appointment-to-patient has distinct stages
Higher education where enquiry, application, enrolment, and commencement are trackable steps

Not a Fit (Yet)

E-commerce – you already have direct conversion value data. Standard Target ROAS bidding works. You do not need journey-aware bidding because the purchase IS the journey endpoint
Single-step lead gen – if your business model is “form fill equals customer” with no qualification process, there is no journey to model
Low-volume accounts – fewer than 30 conversions a month means insufficient signal for the algorithm to learn from

The Bigger Picture: Data Quality Is the New Competitive Advantage

Journey-aware bidding is part of a pattern that has been building across every major ad platform in 2026.

Google’s AI Max for Search is auto-migrating every DSA and broad match campaign in September. The algorithm controls keyword matching.

Meta’s Advantage+ has absorbed lookalike audiences and turned detailed targeting into a suggestion. The algorithm controls audience selection. And now journey-aware bidding lets the algorithm learn from your entire sales pipeline.

In all three cases, the automation is getting more powerful. But it is also getting more dependent on the data you feed it.

AI Max works better when your conversion tracking is accurate and your negative keywords are in place. Advantage+ works better when your Conversions API is connected and your customer lists are uploaded. Journey-aware bidding works better when your CRM data is clean, your pipeline stages are standardised, and your offline imports are flowing consistently.

The competitive advantage is no longer campaign structure, keyword strategy, or audience building. Those levers are being automated away.

The competitive advantage is data quality.

The businesses that invested in proper tracking infrastructure, CRM integration, and first-party data are the ones whose automation actually works. Everyone else is handing the keys to an AI that is driving blind.

We have been saying this to clients for two years. Journey-aware bidding is just the latest proof point.

Timeline and Rollout

Here is what we know about the rollout so far.

Late 2025: Closed testing begins with selected advertisers
May 7, 2026: Beta confirmed for Search campaigns using Target CPA
May 15, 2026 (Google Marketing Live): Google announces expansion to Performance Max campaigns with product feeds and Shopping campaigns in coming weeks
H2 2026: Broader rollout expected across campaign types

Google has also announced new demand-led budget pacing updates alongside journey-aware bidding, which automatically shift spend toward periods of predicted higher consumer demand. This is rolling out for Search and Shopping campaigns.

Bottom line: Journey-aware bidding is the most significant lead gen bidding update Google has shipped in years. It rewards advertisers who have done the foundational work of connecting their CRM, importing pipeline data, and maintaining clean records. If that describes your account, you are about to see better results from the same budget. If it does not, the gap between you and your competitors just got wider. The good news is that everything you need to do to prepare for journey-aware bidding is the same work that improves your Google Ads performance right now. There is no reason to wait for the beta to start.

10 Best CRM for Marketing: Generate Better Results

Digital Nomads HQ — Tue, 24 Feb 2026 03:59:07 +0000

Best CRM for Marketing

Marketing campaigns often fall short despite your best efforts.

From our agency’s experience across multiple industries, the common thread is usually the same – businesses struggling to track leads, measure campaign performance, and maintain consistent communication with their customer base.

This is where the right CRM makes a real difference.

A basic CRM can manage your contacts, but a specialised marketing CRM can elevate your campaigns significantly. In 2026, the gap between basic and best-in-class has widened further – largely thanks to AI.

Platforms like HubSpot, Salesforce, and ActiveCampaign have all rolled out AI tools that can generate campaign content, predict customer behaviour, and automate personalised journeys with minimal manual input. This is no longer a nice-to-have; it’s quickly becoming the standard.

We evaluated the top 10 CRM platforms that excel at marketing automation and campaign management, looking at pricing, AI capabilities, ease of use, and how well they scale as your business grows.

Whether you’re after an enterprise solution like Salesforce or an affordable all-in-one like Zoho CRM, here’s our guide to finding the right fit for your marketing needs in 2026.

10 Best CRMs for Marketing

1. HubSpot

Platform Information

Pricing

Free Plan Available

G2 Rating

4.4/5 Stars

Best for:

Campaign management
Lead generation
Multi-channel tracking

Overview

HubSpot continues to be a powerhouse in marketing CRM solutions in 2026.

The AI-powered platform remains the only marketing automation solution built right on top of a complete CRM system, and has made significant strides with the introduction of Breeze AI – a suite of AI tools embedded across the entire platform for content creation, campaign optimisation, and customer intelligence.

A major change to be aware of: HubSpot transitioned to a seat-based pricing model in March 2024, which is a shift from their previous contact-only model. This means your total cost now depends on both your number of marketing contacts and how many team members need access.

The platform also introduced Content Hub (formerly CMS Hub) and Data Hub (formerly Operations Hub), expanding its ecosystem further.

HubSpot Marketing Hub unifies customer insights through Smart CRM as an all-in-one marketing automation platform. Customers continue to report strong results, with HubSpot citing an average 134% traffic increase for properly onboarded users.

Pros

Built-in Breeze AI tools for content, prospecting, and customer agents
Complete campaign management system
Smooth integration with CRM
Easy-to-use drag-and-drop email builder
Advanced personalization capabilities

Cons

Higher learning curve for advanced features
Premium features limited to higher tiers
Costs escalate quickly with contact growth – contact-based pricing can cause sticker shock

Content Capabilities

Visual workflow builder for automated campaigns
Multi-channel campaign tracking
Custom reporting and analytics
Social media management integration
Smart forms and landing pages
Lead scoring automation
Behavioural event targeting
Dynamic content personalisation

2. Salesforce Marketing Cloud

Platform Information

Pricing

Free Trial Available
$35/ per user p/m for Starter Suite

G2 Rating

4/5 Stars

Best for:

Cross-channel campaign management
AI-driven personalisation
Journey builder

Overview

Salesforce Marketing Cloud has undergone a significant restructuring since our last review.

For businesses seeking enterprise-grade marketing CRM, the platform now centres around two main editions: Marketing Cloud Growth Edition and Marketing Cloud Advanced Edition, both priced per organisation rather than per user – a fundamental shift in how Salesforce charges for marketing tools.

The biggest headline is Agentforce, Salesforce’s AI agent platform that powers autonomous marketing campaigns. Agentforce can generate campaign briefs, segment audiences, create landing pages, and optimise content with minimal human intervention.

This represents a step change from the previous Einstein AI capabilities.

Marketing Cloud Growth Edition is built natively on Salesforce’s Data Cloud, giving teams a unified view across marketing, sales, service, and commerce.

For growing businesses, this means enterprise-grade AI and data unification are now more accessible than before – though still at a premium price point.

Note: Salesforce also still offers legacy products – Marketing Cloud Engagement (formerly ExactTarget) and Marketing Cloud Account Engagement (formerly Pardot) – which can cause confusion. The newer Marketing Cloud Growth is Salesforce’s primary offering going forward.

Pros

Agentforce AI for autonomous campaign creation and optimisation
Complete cross-channel campaign management
Deep integration with the Salesforce ecosystem
Resilient analytics and reporting
Enterprise-grade security features

Cons

Complex setup and learning curve
Higher price point than competitors
Technical expertise needed
Additional third-party integrators might be required

Content Capabilities

Live customer data unification
Predictive analytics and AI-powered insights
Custom reporting dashboards
Behavioural tracking and analysis
Cross-channel campaign orchestration
Journey builder with visual mapping
Automated workflow creation
Dynamic content personalisation
Email marketing studio
Social media management
Mobile messaging capabilities
Web personalisation

3. Zoho CRM

Platform Information

Pricing

Free trial + $18 per month per user

G2 Rating

4.1/5 Stars

Best for:

Campaign builder
Multi-channel execution
RFM segmentation

Overview

Zoho CRM remains one of the most detailed marketing automation solutions at a price point well below its competitors.

Our extensive testing shows it continues to deliver strong functionality for businesses that need both capability and affordability in 2026.

The standout update is the continued evolution of Zia AI, Zoho’s artificial intelligence engine. Zia now offers enhanced predictive analytics, anomaly detection across sales metrics, and AI-powered content suggestions for email campaigns.

Zoho has also deepened its integration with the broader Zoho ecosystem (Zoho One), making it even more appealing for businesses already using Zoho’s suite of 45+ applications.

Zoho CRM combines sophisticated marketing automation with powerful analytics capabilities. The platform handles everything from email campaigns to social media marketing and maintains a unified view of customer interactions.

2026 Key Updates

Zia AI significantly enhanced with predictive analytics, anomaly detection, and content suggestions

Deeper integration across the Zoho One ecosystem (45+ apps)
Improved Canvas design tool for custom CRM views

Enhanced CommandCenter for cross-functional process orchestration

Pros

Detailed marketing automation tools
Excellent value for money
Built-in RFM customer segmentation
Powerful campaign attribution tracking
Extensive third-party integrations

Cons

Interface feels less polished than competitors
Setup process can be complex
Learning curve for advanced features
Limited advanced features in lower tiers

Content Capabilities

Visual campaign builder
Multi-channel campaign execution
Immediate campaign analytics
Advanced segmentation tools
Email marketing automation
Social media management
Website behaviour tracking
Lead scoring and nurturing
Marketing attribution
ROI tracking
Custom dashboards
Performance analytics

4. ActiveCampaign

Platform Information

Pricing

Free trial + $15 per month

G2 Rating

4.5/5 Stars

Best for:

Email marketing
Automation builder
Predictive sending

Overview

ActiveCampaign has repositioned itself as an “autonomous marketing platform” in 2026, leaning heavily into AI-driven campaign execution.

The platform continues to deliver customised customer experiences through intelligent automation, and now features Active Intelligence – their AI engine that powers goal-aware automations across email, SMS, and WhatsApp.

A significant development is the introduction of AI Agents that can run entire marketing campaigns through simple prompts. This marks ActiveCampaign’s evolution from a sophisticated automation tool to a more hands-off, AI-first platform.

However, it’s worth noting that ActiveCampaign has faced criticism for substantial price increases over recent years, with some long-term users reporting near-100% increases over three years. The platform now operates across four tiers – Starter, Plus, Pro, and Enterprise – and costs scale steeply as your contact list grows.

Pros

Industry-leading email deliverability (89.6% average rate)
Active Intelligence AI with goal-aware automations and AI Agents
Detailed segmentation options
AI-powered content optimisation
Extensive integration options (900+ apps)

Cons

No free plan available
Learning curve for advanced features
Prices rise substantially with contact growth
Some advanced features limited to higher tiers

Content Capabilities

Visual automation builder with 900+ pre-built recipes
Behavioral-based targeting
Predictive sending optimisation
Multi-channel campaign orchestration
Dynamic content customisation
Advanced segmentation capabilities
A/B testing for campaigns and automations
Up-to-the-minute data analysis and reporting
SMS marketing integration
Landing page builder (Plus plan and above)

5. EngageBay

Platform Information

Pricing

Free plan + $12.99 per user per month

G2 Rating

4.6/5 Stars

Best for:

Multi-channel campaigns
Visual workflow builder
Site messaging

Overview

Small businesses looking for an economical yet powerful marketing CRM will find EngageBay continues to be a standout solution in 2026.

The platform has grown significantly since our last review, now serving over 150,000 businesses worldwide – a substantial jump from the 46,000 reported previously.

EngageBay has introduced AI-powered features including AI email and campaign generation, AI deal scoring, and smart recommendations to boost productivity.

While these AI tools are more basic compared to enterprise platforms like HubSpot or Salesforce, they add genuine value at EngageBay’s price point.

The platform combines advanced automation with an accessible interface, which makes it ideal for growing businesses that need sophisticated marketing tools without complexity or the steep costs of platforms like HubSpot (where Professional plans can quickly exceed $1,000/month).

Pros

Detailed all-in-one marketing platform
Exceptional value for money
Free onboarding sessions
Accessible drag-and-drop campaign builder
Strong automation capabilities

Cons

Extra email purchases can get pricey
Some features are still under development
Limited workflow automation in simple plans
Fewer customisation options than enterprise solutions

Content Capabilities

Visual workflow builder
Multi-channel campaign execution
Site messaging and push notifications
SMS marketing integration
Social media automation
Email sequence automation
Behavior-based triggers
Lead scoring and segmentation
Web engagement tracking
Landing page builder

6. Freshworks CRM

Platform Information

Pricing

Free trial + $11 per user, per month

G2 Rating

4.5/5 Stars

Best for:

AI-powered tools
Multi-channel communication
Campaign tracking

Overview

Freshsales by Freshworks excels with its AI-powered marketing and sales automation.

The platform turns complex processes into efficient, automated systems through Freddy AI – Freshworks’ artificial intelligence assistant that has been significantly expanded in 2026.

A key distinction to understand: Freshworks now offers its products as separate tools – Freshsales (CRM/sales), Freshmarketer (marketing automation), and Freshsales Suite (combined sales + marketing).

If you need full marketing automation alongside CRM, you’ll want to look at Freshsales Suite or pair Freshsales with Freshmarketer.
Freshsales offers a unified suite that combines customer data, engagement tools, and automation capabilities.

Freddy AI now analyses sales data to score leads, predict deal outcomes, and suggest next actions – learning from your historical data to improve recommendations over time.

The platform’s strength lies in its ability to enhance customer interactions through built-in phone, email, chat, and messaging while keeping all customer information centralised.

Pros

Easy-to-use interface with quick setup
Built-in multi-channel communication tools
AI-powered marketing automation
Detailed campaign tracking
24/5 premium support

Cons

Limited advanced customisation in lower tiers
Some features require higher-tier plans
Mobile app functionality needs improvement
Advanced automation features take time to master

Content Capabilities

Contact scoring and prioritisation
Automated lead assignment
Predictive contact insights
Smart workflow automation
Multi-channel campaign orchestration
Live engagement tracking
Individual-specific experiences
Advanced segmentation tools
Campaign performance metrics
ROI tracking and analysis
Custom report generation
Behavioural analytics

7. Monday.com

Platform Information

Pricing

Free trial + $15 per seat/ month

G2 Rating

4.6/5 Stars

Best for:

Visual workflow builder
Campaign tracking
Content calendar

Overview

Monday.com’s unique approach to CRM customisation continues to make it stand out in 2026. The platform brings campaign management, team collaboration, and customer tracking together in one highly visual, unified system.

A major development: Monday.com separated its CRM product pricing from its Work Management product in 2024. Previously, buying Monday CRM included Work Management access at no extra cost – that’s no longer the case. Each product is now priced individually, which has increased the total cost for teams using both. Additionally, all paid CRM plans require a minimum of 3 seats, which means solo users or very small teams will be paying for seats they don’t use.

On the positive side, Monday CRM has added meaningful AI capabilities in 2026, including AI-powered email generation, data enrichment for contacts, and smarter automation suggestions. The platform continues to adapt to any marketing workflow with powerful no-code automation, now supporting up to 250,000 actions per month on higher plans.

Pros

Highly customisable with 20+ column types
Visual workflow builder with drag-and-drop interface
Detailed campaign tracking templates
Live collaboration features
Advanced automation capabilities (up to 250,000 actions)

Cons

Complex automations take time to learn
Advanced marketing features need higher-tier
Costs increase with more users
Plans have overlapping features

Content Capabilities

Content calendar view for campaign planning
Campaign Gantt charts with dependencies
Custom marketing automations
Advanced reporting dashboards
Digital asset management
Marketing request forms
Automated workflow triggers
Custom integration recipes
Email sequence automation
Social media scheduling
Lead capture forms
Performance tracking

8. Pipedrive

Platform Information

Pricing

Free trial + $14 per month/ seat

G2 Rating

4.3/5 Stars

Best for:

Email campaign builder
Lead qualification
Marketing analytics

Overview

Pipedrive continues to bridge the gap between sales and marketing teams in 2026, with its unique approach of turning activity-based selling into powerful marketing channels. The platform handles deal management for users globally and helps achieve significant improvements in pipeline performance.

The standout addition is an enhanced AI Sales Assistant that now predicts deal outcomes and suggests daily priorities based on your pipeline data. In testing, the AI demonstrated approximately 75% accuracy in predicting which deals were likely to close after just two weeks of data.

Pipedrive’s marketing CRM capabilities remain spread across the core product and add-ons. Email marketing requires a separate add-on (Campaigns), and features like web visitor identification (Prospector) and LeadBooster are additional purchases. While this modular approach keeps the base price low, the total cost can add up for teams needing full marketing functionality.

2026 Key Updates

Plans renamed: Essential → Lite, Advanced → Growth, Professional → Premium, Power → Ultimate

AI Sales Assistant enhanced with deal outcome predictions (~75% accuracy)

Integration count increased to 400+ tools

Improved automation builder with more triggers and actions
Enhanced contact data enrichment features

Pros

Accessible email marketing campaign builder
Powerful lead qualification automation
Immediate marketing analytics
Smooth integration with 300+ tools
Advanced contact data enrichment

Cons

Limited advanced marketing features in lower tiers
Email marketing needs a separate add-on
Higher learning curve for automation features
Marketing capabilities spread across add-ons

Content Capabilities

Visual email campaign builder
Automated lead qualification flows
Immediate engagement tracking
Smart contact data enrichment
Web visitor identification
Custom workflow automation
AI-powered sales assistant
Automated lead scoring
Smart contact segmentation
Behavioral tracking
Multi-channel campaign orchestration
Performance analytics dashboard

9. Microsoft Dynamics 365

Platform Information

Pricing

Free plan + $65 per user/ month

G2 Rating

3.8/5 Stars

Best for:

AI-driven optimisation
Customer journey orchestration
Event management

Overview

Microsoft Dynamics 365 stands out as a powerhouse in AI-driven marketing automation in 2026, and has received perhaps the most significant AI upgrade of any platform on this list with the integration of Microsoft Copilot.

Copilot is embedded across the Dynamics 365 ecosystem, allowing marketers to generate content, create audience segments, build customer journeys, and analyse campaign performance using natural language prompts.

This is a meaningful advantage for organisations already in the Microsoft ecosystem – Copilot works seamlessly with Teams, Outlook, Excel, and Power BI.

Pros

Advanced AI-powered campaign optimisation
Smooth integration with the Microsoft ecosystem
Immediate customer journey arrangement
Complete event management tools
Built-in Power BI analytics

Cons

Complex implementation process
Steeper learning curve
Higher price point than competitors
Technical expertise needed for full utilisation

Content Capabilities

Customer journey arrangement
Predictive analytics
Automated lead scoring
Immediate personalisation
Smart content recommendations
Multi-channel campaign execution
Event management integration
Landing page builder
Email marketing automation
Social media integration
Custom channel support

10. Insightly

Platform Information

Pricing

Free trial + $29 per user, per month, billed annually

G2 Rating

4.2/5 Stars

Best for:

Journey builder
Multi-touch capabilities
Prospect scoring

Overview

Insightly’s unified approach to marketing CRM continues to impress, with its seamless integration of marketing automation and core CRM functionality on a single platform.

A notable development: Insightly is now part of Unbounce’s go-to-market solutions suite, which provides additional landing page and conversion optimisation capabilities within the broader ecosystem. The company positions itself as a modern, affordable CRM that teams love – designed to elevate the customer experience by aligning sales, marketing, and service.

In 2026, Insightly introduced AI-generated email reply capabilities, allowing users to draft professional responses faster with AI-powered suggestions. While not as advanced as the AI offerings from HubSpot or Salesforce, this practical feature speeds up day-to-day customer communication.

2026 Key Updates

Acquired by Unbounce — now part of Unbounce go-to-market solutions

AI-generated email replies feature launched (February 2025)

New AI tools for CRM adoption and buyer experience optimisation
Enhanced integration with Unbounce for landing page creation

2025 CRM Research Report highlights focus on reducing CRM underutilisation

Pros

Unified platform for sales and marketing arrangement
User-friendly builder with multi-touch capabilities
Advanced A/B and multivariate testing options
Complete prospect scoring and grading
Dynamic list segmentation capabilities

Cons

Advanced features take time to master
Lower-tier plans have limited functionality
Enterprise users get exclusive features
Setup can be challenging

Content Capabilities

Visual journey builder for multi-step sequences
Dynamic list segmentation for targeted campaigns
UTM tracking and multi-touch attribution
Prospect ID tracking for intent analysis
Health reporting and analytics dashboard
Email marketing with drag-and-drop builder
Landing page creation and management
Lead scoring and grading models
A/B and multivariate testing capabilities
Marketing journey automation
Social media integration

Final Thoughts

The CRM space for marketing has shifted significantly heading into 2026, with AI now playing a central role in how these platforms deliver value.

Every tool on this list has introduced meaningful AI capabilities – from Salesforce’s Agentforce running autonomous campaigns to HubSpot’s Breeze AI suite and Microsoft’s Copilot integration… its become a “must have” in a marketing CRM.

Choosing the right marketing CRM now isn’t just about features and price – it’s about how well the platform’s AI tools align with your team’s workflow.

HubSpot remains the strongest all-rounder, though its shift to seat-based pricing and steep contact scaling costs mean you need to budget carefully as you grow. Salesforce Marketing Cloud is the enterprise play – powerful but firmly suited to larger operations with dedicated technical resources.

For growing businesses, Zoho CRM and ActiveCampaign deliver strong results on value and automation respectively, though ActiveCampaign’s price increases over recent years are worth factoring in. Small businesses have solid free options in EngageBay (now serving 150,000+ businesses) and Freshsales (formerly Freshworks CRM) to get started before committing.

The right choice still comes down to your business size, budget realities (factor in how pricing scales with contacts and seats, not just the starting price), your team’s technical capacity, and integration needs with your existing tools.