A survey of 343 marketing decision-makers published this month by Fractl contains one finding that cuts through all the noise about what to call AI search optimisation: 81% of marketers still describe their AI search visibility strategy as SEO. Not GEO. Not AEO. Not LLM optimisation. Just SEO.

This matters, but probably not in the way the commentary usually suggests. The reaction from most of the industry has been to frame this as a problem – a gap between where search is heading and where practitioner vocabulary has got to. But the data tells a more nuanced story, and the practical implications for anyone managing digital marketing in 2026 are worth reading carefully.

What the data actually says

The headline number – 81% still calling it SEO – sits alongside several others that are worth considering together. Marketers are allocating an average of 24% of their total search or content budget to AI search visibility. Up to 82% have committed at least some budget to it. 43% are allocating more than 20%. This is not a situation where the vocabulary gap reflects an investment gap. The money is moving. The terminology hasn’t caught up.

The terminology gap is also unevenly distributed. Senior leaders use newer terms like GEO and AEO at roughly three times the rate of individual contributors. C-suite marketers are more likely to have encountered these acronyms in board decks or conference presentations and to have adopted them into their own language. The people actually doing the work – the SEO specialists, the content managers, the performance marketers – are largely still working within the SEO frame. That’s a meaningful distinction for anyone trying to have a coherent conversation about strategy across a mixed team.

Half of marketers surveyed said they had researched a term they didn’t know after seeing it used by a peer or competitor. Only 27% of marketing teams have formally adopted a term beyond SEO. 42% have actively decided against it. 31% haven’t decided. This is not the profile of an industry that has broadly accepted a new vocabulary. It’s the profile of an industry where the vocabulary is being imposed top-down and hasn’t bedded in.

What this means for how clients and internal teams behave

The most commercially useful finding in the research is about vendor credibility. When decision-makers evaluate a supplier or agency for AI search work, the credibility signals they trust are strikingly familiar. Case studies with measurable, verifiable results were the top signal, selected by 34% of respondents. Clear methodology came second at 22%. Team expertise and track record came third at 15%. Terminology fluency ranked at just 9%.

The red flag data is equally direct. The biggest single turnoff when evaluating a vendor was heavy use of buzzwords without a clear explanation of what each term means – cited by 36% of respondents. Another 21% pointed to a lack of case studies or trackable results. 20% flagged vague or unsubstantiated performance claims. And 16% specifically raised concerns about repackaged SEO services with new AI branding.

The practical implication is clear. Clients and internal decision-makers want to understand what has changed, what you are doing about it, and what happened as a result. The shift from rankings to recognition in how AI systems surface brands is a real and significant change. But calling it GEO in a pitch deck and not explaining what that means in practice is actively counterproductive. The acronym doesn’t do the work. The explanation does.

The platform prioritisation problem

Platform focus among marketing teams is currently fragmented in a way that reflects the broader unsettled state of the category. ChatGPT leads, with 34% of marketers naming it as their primary AI search visibility priority. Gemini is second at 16%. Claude is at 6%, Copilot and Bing AI at 5%. Only 1% named Perplexity, despite the significant attention it receives within SEO and AI professional circles. 14% of teams haven’t picked a target platform at all.

This matters in context of something we looked at earlier in the year: 91% of AI citations appear in only one engine. If you’re cited on ChatGPT, the odds are you’re not being cited on Perplexity or in AI Overviews. A single-platform AI visibility strategy is almost certainly leaving material gaps. But the research suggests most teams haven’t yet developed a multi-platform approach, and a significant minority haven’t even committed to a primary platform to focus on first.

The research authors’ advice is sensible here: avoid both extremes. Don’t dismiss AI search because your traffic hasn’t collapsed. But don’t overcorrect by chasing every new answer engine separately. Start by identifying where AI search is already influencing discovery in your category, then build outward from there.

The feedback loop that changes what visibility means for agencies

The most practically significant finding for agencies is buried toward the end of the research. Two thirds of marketing decision-makers said they had personally used an AI tool – ChatGPT, Perplexity, or Gemini – to research or evaluate a marketing vendor or agency. Adoption is highest among the groups most likely to influence search investment: SEO specialists (89%), performance marketers (84%) and C-suite leaders (81%).

This creates a feedback loop that redefines what agency visibility means. A prospective client may search Google, ask peers in a Slack community, and then prompt ChatGPT before they ever fill out a contact form. Those surfaces are not separate. They reinforce each other. If an agency is recommending AI search visibility to clients but is not itself visible in AI search answers about marketing agencies, that is a credibility problem that will compound over time.

The practical audit for any agency is to run the prompts your prospective clients are likely to run. Ask which agencies specialise in AI search visibility, which SEO firms have credible case studies, how a specific agency compares with competitors, and which vendors are trusted for this kind of work. Then look at the sources shaping those answers, and identify where you are and aren’t present.

The useful takeaway from the naming debate

The argument about what to call AI search optimisation has consumed a remarkable amount of industry energy for something the data suggests buyers largely don’t care about. The research is direct on this: vocabulary fluency ranked at 9% as a credibility signal, while case studies, clear methodology, and track record together accounted for 71%.

What the naming debate does reveal, though, is something more useful. The fact that 81% of practitioners still default to SEO is not just a vocabulary lag. It reflects a genuine continuity in what the underlying work involves. The content has to be specific and authoritative. The technical accessibility has to be right for crawlers and AI systems alike. Third-party credibility signals still matter. The entities – brand, people, place – need to be correctly understood and associated. These are things SEO has always been about. What has changed is where the work surfaces and how it gets measured.

The teams that are doing well in AI search are not necessarily the ones that adopted GEO terminology earliest. They are the ones that understood what changed in how AI systems decide what to cite, built their content and credibility accordingly, and can demonstrate the results. That is a methodology problem, not a naming problem. And it is the one worth spending time on.

Google Ads has quietly rolled out a new feature that gives advertisers a view of how their weekly spending and click performance compare to businesses it considers similar. Appearing in the account Overview section as a Spend Benchmarks report, it is one of those updates that sounds straightforward but deserves a little more scrutiny before you act on it. Used wisely, it can provide genuinely useful context. Used without that scrutiny, it could nudge you into spending decisions that do not actually reflect your business needs.

What the Report Shows

The Spend Benchmarks report sits within your Google Ads account Overview and compares your weekly ad spend and clicks against a peer group of businesses Google has grouped with yours. The comparison takes into account factors including your industry and the markets you advertise in. It is a simple enough concept: a snapshot of where you sit relative to comparable advertisers on the same platform.

Why the Context Matters

The limitation worth understanding is that similar businesses are not always comparable businesses. Two companies operating in the same industry and geography could have completely different margins, average order values, customer lifetime values and growth strategies. An advertiser spending less than the peer benchmark might be running a highly efficient account with strong returns. One spending significantly more might be chasing volume at the expense of profitability. The benchmark does not know which situation applies to you, and neither does the recommendation to increase spend that sometimes accompanies it. That recommendation is worth being aware of: a peer comparison that comes packaged with a prompt to spend more can easily start to feel like a target rather than a reference point.

How to Use It Properly

The Spend Benchmarks report is most useful as a prompt for questions rather than a directive for action. If your spend sits significantly below peers and your campaigns are constrained by budget, that is worth investigating. If your spend is higher but your returns are strong, the gap tells you very little. The metrics that actually determine whether your budget is right are your cost per acquisition, your return on ad spend, and whether incremental spend produces incremental profit at an acceptable level. Treat the benchmark as one piece of context alongside those figures, not as a measure of whether you are doing enough.

SEO is the process of optimising your website to improve online performance. SEO has multiple different branches that make up a holistic online strategy. In this article, we will go through what is the difference between on-page and off-page SEO, the key strategies that separate them and how they work together.

On-Page SEO

On-page SEO is using techniques to improve SEO performance directly on your webpage. This helps not only users but also search engines to understand your content better, so you can rank higher and gain more visibility online.  Some of the key principles of on-page SEO include;

Content – One of the first places to start when optimising on-page SEO is with the content. There are certain SEO principles that should be followed, including using keywords to target specific audiences, structuring your content clearly with headings and making sure your content is both helpful and original so that it gives your audience a fresh perspective; this means not using AI-generated or regurgitated content.

HTML – Another way on-page SEO can be improved is by improving the code of a site. Most sites use HTML as the main bulk of their code, and using page builders and various plug-ins, this code can often become bloated and make it hard for search engines to read the code on your site, slowing it down.

Internal Linking – By adding links into your content from other pages on your site, you are creating an internal link map which allows search engines to access different areas of your site, but also shows it which pieces of content are connected and which ones are the most important for users.

Schema Markup – Structured data that you can add to the code of your website. It tells search engines exactly what type of content is displayed on your webpage to help your rankings become more targeted.

Off Page SEO

Off-page SEO refers to techniques you can use to improve your website’s performance off your own site. One of the main strategies for improving off-page SEO is earning backlinks. Backlinks are links from other websites to your own. Gaining backlinks from sites that do well on search engines and have authority shows search engines that your website is legitimate and trustworthy, so you want to earn as many high-quality links as you can. You can do this by creating high-quality content but also engaging in digital PR and reaching out to strong-performing brands to try and earn backlinks.

For local businesses, setting up a Google My Business profile is also another way to improve digital performance by making yourself more visible on search engines and collecting customer reviews, which show your business in a positive light. Similarly, posting on social media can build up a customer base and a positive sentiment online, improving traffic to your website.

Using only on-page or off-page SEO strategies will not be enough to compete in today’s digital era; you need a well-rounded SEO plan that includes combining both techniques to maximise online scope and performance.

Google has quietly shipped one of the more useful additions to Search Console in recent memory. Platform properties, launched earlier this month, allow you to connect your Instagram, TikTok, X and YouTube accounts directly to Search Console and see how your content on those platforms is performing within Google Search. Not on those platforms. Within Google Search itself.

It sounds like a subtle distinction but it is a meaningful one. For any business that posts content on social or video platforms without knowing whether it is generating search visibility, this gives you the first direct window into that question. And given that recognition across multiple channels now drives downstream search behaviour in ways that standard analytics have never been able to capture, platform properties is a feature worth setting up properly.

What platform properties actually shows you

Once you have verified a platform property in Search Console, you get access to three types of reporting, each showing a different layer of how your social and video content surfaces in Google Search.

• Performance report. Total clicks, impressions and engagement metrics from your social content appearing in Google Search. You can filter by specific posts and sort by the search queries that are driving traffic to your accounts or content. The data is also exportable if you want to pull it into a separate reporting dashboard.
• Insights report. A higher-level view showing traffic trends, your top-performing posts and the mechanisms by which people discover your accounts in Google Search. Useful for a quick overview without drilling into individual query data.
• Achievements. Milestone tracking for growth in clicks from Google Search, measured in 28-day windows. Less analytical, but useful for demonstrating momentum to clients or stakeholders.

The rollout is gradual, so not every account will see platform properties immediately. Google has confirmed it is expanding access over the coming weeks. If you do not see the option yet, it is worth checking back rather than assuming it has been skipped.

How to set it up

Setting up platform properties requires you to verify each social account separately within Search Console. The process is the same for all four supported platforms and takes a few minutes per account.

• Open Search Console and go to the property selector dropdown, or navigate to the verification page directly.
• Click ‘Add property’ and select one of the four available platforms: Instagram, TikTok, X or YouTube.
• Follow the on-screen verification steps to authorise the connection. Google uses a secure authorisation flow rather than asking for login credentials.
• Once verified, the platform property appears alongside your standard web properties in Search Console and data begins populating, typically showing historical data going back several weeks.

For businesses managing multiple clients, you will need to verify each platform account separately. There is currently no bulk verification option, and each platform property sits in its own reporting view rather than being rolled up into a combined dashboard.

Why this matters more than it might initially appear

The reason this is genuinely useful rather than just a nice-to-have is that it closes a specific and long-standing measurement gap. Until now, if a business posted a video on YouTube or a set of stories on Instagram, there was no reliable way to know whether that content was generating impressions or clicks within Google Search. You could track traffic from Google to your social profiles in some analytics tools, but you could not see what search queries were triggering those results or which pieces of content were responsible.

Platform properties flips that. You are now looking at the data from the Google Search side rather than from the social platform side. That means you can see which search terms are surfacing your YouTube videos, which Instagram posts are appearing in Google Image Search, and which queries are driving traffic to your X profile from within Google. That is a different and more useful frame than social platform analytics provides on its own.

The timing of this feature is also worth noting. Recent data from Similarweb confirmed that more than half of the downstream traffic generated by AI recommendations arrives via branded search rather than direct AI referral clicks. Branded search lifts are increasingly a downstream signal of visibility across multiple channels, not just traditional SEO. Platform properties gives you the first standardised tool for measuring whether your social content is contributing to that broader search signal.

The practical implications for content and reporting

For most marketing teams, the immediate value of platform properties falls into three areas:

• Proving the SEO value of social content. This has historically been difficult to demonstrate in a way that satisfies sceptical stakeholders. Platform properties gives you direct click and impression data from Google Search for content posted on social platforms. That is a credible, source-backed number rather than an inferred relationship.
• Understanding which queries drive social discovery. Seeing the specific search terms that are surfacing your YouTube videos or Instagram posts in Google Search tells you something useful about the intent of people finding you through that route. If a dental clinic’s treatment videos are appearing for ‘how long does teeth whitening last’ in Google Search, that is content worth making more of. Without platform properties, you would not know those searches were leading to your video.
• Informing content decisions with actual search data. The performance report shows which specific posts are generating clicks and impressions in Google Search. That gives you a direct signal about which content formats, topics and posting approaches are earning Google search visibility rather than just social engagement. The two do not always correlate.

What to check once you have connected your accounts

Once the platform property data starts populating, the most useful starting point is the performance report filtered by query. Look for search terms that are driving impressions to your social content that you are not yet targeting with your main website. These represent keyword opportunities where Google is already surfacing your brand through social content, and where a corresponding page or article on your website could strengthen that visibility further.

The insights report is worth reviewing monthly rather than weekly – it is a trend indicator rather than a granular data source. The most commercially useful data is in the performance report, particularly for video content on YouTube where the correlation between Google Search impressions and watch time can help inform both SEO and content production decisions.

For businesses running YouTube channels alongside a website, the combination of YouTube platform property data and standard Search Console data in the same interface starts to give a more complete picture of how their content performs across Google’s various surfaces. That has never been possible before within a single tool, and it is worth taking the time to set it up properly rather than treating it as a nice-to-have.

What is brand recognition?

Brand recognition is a step beyond brand awareness; it is about when people can easily identify a brand based on elements like brand colours, jingles, logos and campaigns.

Achieving brand recognition is no easy feat, so when customers and non-customers alike can recognise your brand, it shows the effectiveness and impact your brand-awareness campaigns have had.

A key example of brand recognition is when your business is the first thought brand for that particular product or service. Leading against competitors and demonstrating the overall commercial impact that’s been had.

What is the value of brand recognition?

Brand recognition is incredibly valuable because it tends to make people feel more comfortable investing in a brand. When trust and familiarity are established through recognition, it can help reduce the perceived risk around trying new services or products. This is favourable, especially when weighing up the risk, because it is an expensive and important investment on the customer’s part.

As brand recognition is strengthened, it can help build customer loyalty. Customers with a pre-existing positive experience are more likely to return to a brand. Rather than seeking out potential alternatives. Customer recognition also increases the chances of recommendations and referrals.

Another strategic advantage of becoming a recognised brand is the ability to improve the effectiveness of marketing campaigns. The more familiar a brand is, the less effort is required to convey that.

Above all, brand recognition offers a competitive advantage, allowing brands to stand out in over-saturated markets. Increasing the difficulty for competitors to capture their audience.

Building brand recognition

The most effective way for businesses to increase their brand awareness is to repeatedly and consistently create opportunities for exposure. The more a brand creates instances to familiarise audiences, the more memorable they become.

Some of the keyways to build up brand recognition include:

• Creating content that adds value to prospects and existing customers. This can come in several forms, whether that be publishing blogs, videos, social media content, podcasts or helpful guides. The aim is to entertain or educate whilst ensuring visibility remains consistent, all while demonstrating expertise.
• Developing a consistent brand identity. This means using fixed logos, colour palettes, typography, design styles, imagery, social media profiles and marketing materials.
• Developing a strong online presence can be a particularly effective method. Regular activity, SEO and well-optimised websites help keep the brand relevant and useful. This can also help with visibility while reinforcing recognition over time.
• Maintaining a clear brand voice from the moment of establishing a brand is essential; consistent communication creates moments of familiarity and reinforces cues on brand personality.
• Promoting customers’ stories, whether that’s in reviews, testimonials, UGC or referrals.

Overall consistency with the recommended methods is the key. Brand recognition isn’t established in one day; it takes time and repeated interactions from customers to reinforce this. Every aspect of a strategy should reinforce how people remember the brand, which eventually results in getting new and returning customers.

Brand recognition is far more than simply being recognised by name or logo. It reflects the trust, familiarity and credibility a business has built with its audience over time. When customers can instantly identify a brand and associate it with positive experiences, they’re more likely to choose it over competitors and recommend it to others.

While building brand recognition requires patience and consistency, the long-term rewards make the investment worthwhile. By delivering valuable content, maintaining a cohesive brand identity and creating meaningful customer experiences, businesses can establish a recognisable presence that supports sustainable growth, strengthens customer loyalty and helps them remain competitive in an increasingly crowded marketplace.

If your Google Ads campaigns use Dynamic Search Ads, there is an important date you need in your diary. Google has confirmed that all remaining DSA campaigns will be automatically upgraded to its newer AI Max format starting February 2027, giving advertisers several more months than originally planned to prepare. What looked like a race against a September 2026 deadline, right in the middle of the crucial pre-Christmas advertising period, has been extended following widespread feedback from the advertising community. That breathing room is welcome, but it should not be mistaken for an indefinite stay of execution.

What Is Actually Changing and When

Google is retiring Dynamic Search Ads entirely and replacing them with AI Max, its newer AI-driven approach to search campaign management. Rather than relying on keywords alone, DSA campaigns have long worked by automatically matching ads to relevant searches based on your website content, making them particularly useful for large or frequently changing product catalogues. The transition away from this format happens in two stages: from January 2027, you will no longer be able to create new DSA campaigns. From February 2027, any campaigns still running will be automatically migrated to AI Max on your behalf, whether you have prepared for it or not.

Why the Extension Was Granted

The delay was not granted out of generosity. It came directly in response to advertiser pushback. One recurring concern is that AI Max routes specific product searches to generic landing pages, something DSA handled more precisely by matching searchers to the most relevant page within your site. That distinction matters commercially, particularly for retailers with large or structured product ranges. Independent analysis has also shown AI Max delivering lower returns on ad spend in some campaign types, which is why treating this migration as a routine update would be a mistake.

What You Should Do Now

The February deadline may feel distant, but the window for proper preparation is shorter than it appears, especially for businesses with Q4 peak trading periods where any campaign disruption carries real commercial risk. The time to review your DSA campaigns is now, not in December. Start by auditing which campaigns are still running on DSA and how they are currently performing. Then build in time to test AI Max before the forced migration kicks in, so you can identify and resolve any issues on your own terms rather than Google’s. If you are unsure where to begin, this is exactly the kind of transition where working with a specialist pays for itself.

AI overviews, FAQ blocks and AI mode are each increasingly being displayed across the search engine results page. We have to ask the question: is it diluting the quality of content, and is it dominating the SERP, making organic content increasingly harder to find?

We see a plethora of AI uses, ranging from AI-generated search experiences (where AI creates or summarises information) and AI-assisted search features (where AI helps rank, organise, or present content).

Places AI is currently used on search engines

Google, Bing and Yahoo

Google is known for leading the race with a staggering 91.27% of traffic in comparison to other well-recognised search engines. Recognised for its cutting-edge updates, its fine-tuned algorithm and vast catalogue of websites and content to serve searchers’ queries.

In its journey to be the best and largest of search engines, AI has become a key and defining feature. With a strong presence across various search results features, it’s absolutely reshaping the way Google works.

We’ve observed the same evolution across other search engines, including Bing and Yahoo. Those features include:

The Impact of AI on organic content

AI-generated content doesn’t need to fight to be spotted; now, the first positions across the SERP are completely dominated by AI results, pushing organic content further down and reducing the chance of discoverability and clicks.

The AI Zero-clickopalypse

One of the most harmful impacts of AI-generated results is the zero-click epidemic, where AI content steals the valuable clicks from organic content on the SERP. When users don’t need to click into content, because AI has borrowed and displayed it at the top of the SERP, it directly steals traffic from those cited sites.

Ultimately, AI features are pushing the higher-ranking organic pieces of content below the fold, shrinking visible organic listings.

The consequence for a zero-click search varies. For more established brands and sites, reduced clicks may be inconsequential, while smaller brands building their content portfolio are more likely to suffer as a result, seeing the following metrics affected:

• Organic traffic  
• Click-through rates
• Page sessions
• Average duration of engagement

Shifting approaches from SEO to AEO

The entire strategy for SEO needs to adapt to AI Engine Optimisation (AEO). This changes the style, nature and focus of content, as well as the perspectives marketers use to produce it. The impact then falls on human users, who are increasingly likely to encounter more generic, factual content that doesn’t necessarily offer a human experience or perspective.

Rather than allowing users to research and draw their own conclusions, AI is serving cookie-cutter, generic content that reinforces confirmation bias, reduces searchers’ critical thinking, and stunts what was once curiosity, replacing it with quick, low-value information retrieval.

Algorithms creating personalised SERP’s

 Previously in SEO, when your content ranked, it would be a specific keyword it ranked for, and that was applied to all other sites using the same keyword. Now, personalisation breaks down that method of ranking, with results based on contextual clues like gender and location.

Content now tends to be displayed based on location, not a national or global ranking. Google also takes context from search history, inferring intent and resulting in more tailored responses, with historical searches influencing the type of results shown. Ranking has transitioned from a fixed metric to essentially a range in which you can get a general idea of performance.

So, is AI diluting the quality of content on the SERP?

The short answer is yes, but it’s not quite that simple. AI is reshaping the SERP in ways that make organic content harder to find, harder to click, and harder to rank consistently. The zero-click reality, the shift from SEO to AEO, and the fragmentation of personalised results all point in the same direction: the traditional organic search landscape is shrinking.

But dilution isn’t the same as destruction. The opportunity now sits with content that AI can’t easily replicate original research, genuine human perspective, authoritative expertise, and experiences that feel lived rather than generated. If AI serves the generic, the specific becomes more valuable.

The question isn’t whether AI is diluting quality. It’s whether we’re willing to create content that stands apart from what AI can summarise.

With the advances in AI search over the last few years, being cited in AI chatbots is now more paramount than ever to a business’s presence in this ever-evolving digital age. Robots.txt is a plain text file generated by a website that lets search engine crawlers know which of your content it can and can’t index for users to view. LLMs.txt is the same concept but for chatbots, pointing Chatbots to your content to allow them to know which of your content it can rank. Or at least this is how people in the industry are currently using it. In this article, we’ll explain all about LLMs.txt and if you really need to implement it on your site.

What is LLMs.txt

As we’ve mentioned, LLMs.txt is a text file that lives on your web server and is being used to try and make content more discoverable for AI chatbots. However, this isn’t really why it was designed. Unlike a traditional Robots.txt file, according to Google’s John Mueller, LLMs.txt doesn’t actually help you to rank in search engines at all, but was rather designed to help search engines who already know about your site to find out what else is here,

“So I talked with, I think, one of the people who created that proposal a while back. And the idea was really not to create something that makes it easier for search engines or LLM systems to discover all of your content, but almost more that if an LLM already knows about your site and wants to find out what else is here, then that might be an approach.

And I think the aspect of using this as a way to optimise for Discovery by AI systems or Discovery by search systems, that doesn’t make any sense at all.“

Many users at the minute think that using LLMs.txt will help them rank more on search engines, and this simply just isn’t the case.

How can you help your website rank in AI?

While using an LLMs.txt file won’t help you rank in AI, there are still steps you can take to make sure your website is more likely to rank in LLMs, which is going to be important moving forward as the amount of people using them is going to grow. Some steps you can take to help improve AI performance include:

• Question-based queries with direct answers
• Implement structured data
• Build brand authority
• Allow crawlers in robots.txt file

This last one is crucial: while LLMs.txt is largely irrelevant for ranking, Robots.txt is not. If, for whatever reason, you don’t permit LLM crawlers in your robots.txt file, then they won’t be able to crawl your site. Make sure you explicitly state that they can in your robots.txt file.

What this means for Marketers

An LLMs.txt file isn’t going to help improve your rankings in Chatbots, so if this is what your aim is in creating one, you don’t need to. Creating clear, structured, trustworthy content that is crawlable is going to do you way more favours in terms of improving your rankings.

Google Ads has announced three significant updates to the way it bids and manages budgets on your behalf. While the technical detail can get complex, the implications for your advertising spend are straightforward, and for business owners and marketing managers who rely on Google Ads to drive growth, understanding what’s changing matters more than ever. These updates began rolling out this month, with the most impactful change scheduled for 17th August.

Google’s AI Will Now Hunt for Customers You’re Currently Missing

The first update is the global expansion of a feature called Smart Bidding Exploration. In simple terms, Google’s AI will now actively look for additional customers you might be missing, people who are ready to buy but whose search behaviour falls slightly outside the patterns your campaigns normally target. Previously available only to a limited set of advertisers, this is now accessible to all, including those running Shopping campaigns. Crucially, it does this without requiring you to loosen your return-on-ad-spend targets, meaning Google is doing the exploratory work while still holding itself to your performance benchmarks. For businesses that feel they’ve hit a ceiling on their current campaigns, this is a meaningful new lever for growth.

Promotions and Sales Periods Just Got a Lot Less Manual

The second update introduces something called Promotion Mode, currently in beta. If you’ve ever run a product launch, a seasonal sale, or a flash promotion, you’ll know the manual effort involved in temporarily adjusting ad budgets and targets to match the spike in demand, then carefully resetting everything afterwards. Promotion Mode is designed to automate that process, giving Google permission to be more flexible during defined short windows without permanently changing your campaign settings. It’s an operational improvement as much as a strategic one, reducing the risk of human error during the moments when your campaigns matter most.

The August Update Every Advertiser Should Prepare For Now

The third update is the one that deserves the closest attention, because it will affect all campaigns that regularly run up against their daily budget limits, whether you actively choose to engage with it or not. From 17th August, Google will change how it optimises these campaigns behind the scenes, with the goal of delivering more predictable results when budgets are increased. Google will begin sending account notifications from 6th July and is recommending that advertisers review their cost-per-acquisition and return-on-ad-spend targets ahead of the rollout. Our advice: don’t wait for the notification. If you’re running budget-constrained campaigns, now is the right time to review your targets and ensure they still reflect your actual business goals, before Google’s changes trigger a recalibration that catches you off guard.

Anthropic’s latest AI model, Claude Fable 5, represents a significant step forward in autonomous reasoning, coding, and research capabilities. Unlike earlier generations of AI assistants, Fable 5 can handle complex, multi-step tasks with greater independence, helping businesses accelerate development, research, and operational workflows.

Coding

One of Fable 5’s best features is its ability to code to a more advanced level than other agentic AI agents that have come before it. Tasks that had previously taken software engineers days or even months can be done in a matter of hours, such as coding websites and developing web apps.

It can also work autonomously for longer periods of time than other AI models without the need for human input or prompts due to its advanced capabilities. Anthropic used a case study to test Fable 5’s software engineering capabilities before releasing it to the public, and here’s what they found.

“During early testing, Stripe reported that Fable 5 compressed months of engineering into days. In a 50-million-line Ruby codebase, the model performed a codebase-wide migration in a day that would otherwise have taken a whole team over two months by hand.”

This is invaluable for marketing businesses who would have to spend months of time and manpower towards development costs. It can also help digital marketers and web developers with other coding tasks in the industry such as:

• Assist in building websites
• Prototyping web apps
• Building landing pages from a brief
• Creating custom SEO tools and dashboards
• Integrating CRMs with marketing platforms

Research

The autonomous nature of Fable 5 means it is also capable of performing advanced research tasks and can even be used to help train users in complex tasks and new skills, including web development and SEO. It’s not only limited to training, though; it can also aid in complex digital marketing research tasks. Some SEO tasks Fable can help with include:

• Competitor analysis
• Content gap analysis
• Audience research
• Market trend identification
• Industry report summarisation
• Technical SEO audits

How does this affect Digital Marketers?

The ability to edit and build digital websites and web apps at scale allows marketers to be able to develop much more efficiently, while Fable’s enhanced research capabilities now make marketing tasks such as keyword research, SEO and data analysis so much less complex and streamlined if used in the right way.