Search Marketing Takeaways for Leaders: August 2026

Written By Sam Gadsby

How to compete when search increasingly interprets intent, recommends options and shapes the decision

Search used to have a fairly straightforward job. Someone had a need, entered a query, reviewed the results and decided where to go next. Marketing teams could map much of that behaviour through keywords, rankings, clicks, impressions and conversions.

Those signals still matter. But the environment around them is becoming far more complex.

A customer might now describe a problem to ChatGPT, compare products through Google AI Search, discover a brand on TikTok, check reviews through Maps and only visit a company website near the end of the journey.

At each stage, platforms are doing more of the interpretation. They decide which information to retrieve, which sources to trust, which products to present and increasingly which options deserve to be recommended.

This creates an important question for marketing and business leaders:

How do you compete when search increasingly understands the need, selects the evidence and helps shape the decision?

Several developments over the past month give us some useful clues.

1. Search is fragmenting, but Google is far from disappearing

It is tempting to reduce the changing search landscape to Google versus ChatGPT (or traditional search engines vs LLMs). The latest data suggests a much more fragmented picture, however.

Similarweb reported in late July that ChatGPT's share of worldwide generative AI website traffic had fallen from around 76% a year earlier to approximately 53%. Gemini had increased to around 27–28%, while Claude had grown to close to 9%.

That does not necessarily mean fewer people are using ChatGPT. The overall market continues to grow, while meaningful AI-led discovery is spreading across more platforms.

At the same time, Google's traditional search business remains commercially enormous. Alphabet reported 17% year-on-year growth in Search and Other advertising revenue in July. Google also said AI Mode had surpassed one billion monthly users and that its AI-powered experiences were generating incremental search activity. These are Google's own figures, but they hardly suggest conventional search is disappearing. The important shift is fragmentation.

A brand could perform strongly within Google while being barely visible in ChatGPT, Gemini or Claude. The answer isn't to add every new AI platform to a dashboard. Start with where customers actually discover, research and compare.

Leadership takeaway:

Map the discovery environments that genuinely matter to your audience. Understand where customers research, compare and seek recommendations, then measure those that have a credible relationship with demand, enquiries or sales.

Search strategy increasingly needs a portfolio view.

2. Paid search is starting to understand deeper context beyond queries

One of the more interesting search advertising developments this month has come from outside Google. OpenAI's Ads Manager Beta now gives a clearer indication of how advertising within ChatGPT will work.

Advertisers can provide ‘context hints’ describing the conversations, topics and situations where a product or service may be relevant. OpenAI explicitly states that these are not exact-match keywords. Ad selection can consider the context and intent of the conversation alongside the advertisement, landing page and other signals.

Consider the difference between someone searching:

"best CRM software"

and someone explaining:

"We're a 25-person B2B business, leads come through several channels and our sales team currently manages everything in spreadsheets."

The commercial intent may be similar. The second provides significantly more context.

Search advertising has been moving towards broader matching and automated intent interpretation for years. Conversational interfaces could take that much further.

OpenAI is also building increasingly familiar advertising infrastructure, including impression and click-based buying, with conversion optimisation developing within Ads Manager Beta.

Leadership takeaway:

Paid search teams need to become experts in customer intent, not just advertising interfaces.

Clear customer problems, use cases, proposition, landing-page relevance and commercial outcomes become increasingly important when platforms make more of the matching decisions themselves.

3. Product data is becoming infrastructure for discovery

Product feeds have featured in previous updates, but developments this month reinforce how much their role is expanding.

OpenAI now allows retailers to upload product feeds directly into Ads Manager. Titles, descriptions, availability and other product information can then help match relevant products with conversations. It says advertisers using feeds have been among the stronger performers in its advertising programme so far. The programme remains in beta, but the direction is notable.

Google is moving in a similar direction. Google Ads Editor 2.13 has introduced a wider set of AI Max capabilities into Shopping campaigns, including automated text generation, URL controls and brand guidance. The bigger point is that product information increasingly feeds multiple systems deciding what customers see.

Leadership takeaway:

Treat product information as a shared commercial asset, not a feed-management task. Focus particularly on:

  • Clear titles, categories and descriptions

  • Useful attributes and differentiators

  • Accurate pricing, availability and promotions

  • Strong imagery, reviews and ratings

  • Correct landing pages and delivery information

Poor data can now constrain performance across search, shopping, AI, marketplaces and paid media before creative or bidding optimisation even begins.

4. AI search measurement is moving towards topics and authority

One of the biggest problems with AI-search measurement has been the temptation to track a list of prompts and repeatedly ask whether the brand appears. Customer behaviour is rarely that predictable.

Two people researching the same product may phrase their question differently. An AI platform may also generate several additional retrieval searches before producing its response.

Microsoft Clarity took an interesting step in July by adding topic-level analysis to its AI Citations reporting. Rather than showing only individual grounding queries, Clarity can group them into broader themes and report citation volume and share of authority at topic level.

That moves the strategic question from:

"Do we appear for this prompt?"

towards:

"What subjects does AI associate us with, and where are we considered a credible source?"

That is potentially much more useful.

Leadership takeaway:

Organise AI visibility around customer needs, commercial topics and areas where you want the brand to have authority.

For each priority theme, understand whether you appear, which pages are cited, which competitors are prominent and whether the brand is represented accurately.

That should produce better decisions than monitoring hundreds of isolated prompts.

5. Search, social and video continue to move closer together

The distinction between search and social is becoming increasingly difficult to maintain. TikTok announced on 28 July that Smart+ automation is expanding into Search Ads campaigns, combining search-specific targeting with more automated optimisation.

TikTok also says 57% of users use its search functionality and 25% search for something within 30 seconds of opening the app. Those are TikTok's own figures, but they help explain its continued investment in search.

Google has meanwhile completed the global rollout of Search Console properties for Instagram, TikTok, X and YouTube, allowing businesses to understand which Google searches surface social and video content.

YouTube is becoming more conversational too. Google said more than 140 million users interacted with Ask YouTube on video watch pages during June, with that functionality also moving into wider YouTube search.

A customer could now discover a subject through TikTok, search for more information there, encounter social content through Google, use YouTube to research further and then ask an AI assistant to compare their options. Trying to attribute that neatly to one channel quickly becomes difficult.

Leadership takeaway:

Think about your searchable content estate, not only webpages.

For important customer needs, consider whether the best response is a strong webpage, useful article, short-form social post, detailed video or credible third-party evidence.

Planning should increasingly start with the customer question, then determine the right format and environment.

6. Google is consolidating more search activity, making governance more important

Google continues to automate and consolidate previously separate advertising products. Local Services Ads are beginning to migrate into a specialised version of Performance Max in the US this August, with wider international migration planned for 2027.

One detail is particularly important: historical Local Services Ads performance reports will not transfer into Google Ads. Google is advising advertisers to export their historic data before migration.

Separately, Google will enable Local Inventory Ads by default within eligible Shopping campaigns from 31 August. Businesses wanting to keep local and online inventory separate will need to apply the appropriate filters.

As platforms simplify campaign management, businesses need stronger independent governance around what changed, where budgets are going and whether reporting remains comparable.

Leadership takeaway:

Own your performance history and commercial definitions independently of the advertising platform.

Before significant migrations or automated changes, retain historic benchmarks, understand any changes in campaign scope and make sure the system is optimising towards outcomes the business actually values.

7. Reputation is becoming part of the information machines can understand

Google added a review-snippet guideline on 24 July covering fake and undisclosed incentivised reviews. It is a relatively narrow change and shouldn't be exaggerated into a new ranking update. Google says its purpose is to improve transparency in user reviews.

Reviews now influence discovery through search results, Maps, business profiles, marketplaces and product listings. AI systems can also retrieve third-party evidence when researching businesses, products and services. Reputation therefore has a machine-readable dimension alongside its obvious human impact.

Leadership takeaway:

Treat review management as part of search, reputation and customer-experience governance. Focus on:

  • Having credible, current reviews on the platforms that matter

  • Making review requests compliant and transparent

  • Responding appropriately to negative feedback

  • Using recurring themes to identify operational problems

  • Keeping structured review and third-party profile information accurate

The strongest long-term approach remains simple: create experiences people want to recommend and make it easy for them to do so.

8. Being visible to AI and being recommended by AI are very different outcomes

Perhaps the most useful measurement reminder this month came from Brainlabs. In one account it analysed, a brand appeared 42 times across 33 tracked prompts. It was actually recommended only four times.

The same research found that 76% of cited URLs appeared for a single week and were never cited again during the analysis. Brainlabs has consequently been experimenting with measures such as Share of Recommendations, Citation Half-Life and Share of Narrative. These are emerging approaches rather than agreed industry standards.

The principle matters more than the individual KPI names. A report saying "our AI visibility increased 23%" sounds positive. But was the brand simply mentioned? Was it cited as evidence? Was it recommended? Was the information accurate and positive? Did that visibility influence demand or enquiries?

Similarweb's data also shows how quickly the mix of AI platforms is moving. A strong position on one assistant today does not guarantee the same outcome elsewhere.

Leadership takeaway:

Avoid creating another vanity metric. I would focus AI-search reporting on five areas:

  • Presence: Are we appearing for commercially important topics?

  • Authority: Are our sources being cited?

  • Recommendation: Are we actually being selected?

  • Narrative: Are we represented accurately and positively?

  • Impact: Is there evidence this influences demand, leads or customers?

The measures will evolve. The commercial questions are already familiar.

Leadership Perspective: Search is becoming an interpretation layer

There is a connected theme behind this month's developments. Search platforms increasingly have more information available before deciding what to present.

A keyword provides a query. A conversational prompt reveals more context. Product feeds explain inventory. Reviews provide third-party evidence. Social and video demonstrate expertise and experience. First-party data helps advertising platforms understand value.

Those signals can then be combined to decide what deserves to be surfaced. For leaders, that means competitive advantage increasingly depends on the quality of what sits behind individual search tactics:

  • Clear proposition and customer understanding

  • Useful expertise and content

  • Accurate product, service and business data

  • Credible reputation and brand signals

  • Reliable commercial measurement

Excellent SEO and paid-search execution still matter. But as platforms get better at understanding customers, businesses need to become better at expressing why they are relevant to those customers.

Leader's Checklist

A few useful questions to ask this month:

  • Do we know which search, social and AI environments genuinely influence our customers?

  • Are our paid-search teams planning around customer intent as well as keywords?

  • Is our product, service and business data good enough for automated discovery?

  • Are we measuring AI visibility around meaningful topics, authority and recommendations?

  • Do our search KPIs remain connected to revenue, lead quality and customer value?

Final Thought

Keywords are still useful. Rankings still matter. Search advertising remains one of the strongest ways to capture existing demand.

But the unit of search strategy is getting bigger. Increasingly, the real unit is customer intent.

What is someone trying to achieve? What information will help them decide? Which environments might they use? What evidence will those platforms find? How clearly can they understand your business? And why should they select you?

That is where search, AI, social, video, product data, reputation and paid media increasingly meet. For leaders, there is little value in chasing every new search feature individually.

The more durable opportunity is to build a business that is easy for people and platforms to understand, credible enough to recommend and measurable when that visibility turns into commercial value.

Useful Links & Further Reading

Sam Gadsby
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