Branded Search: How to Measure and Grow Brand Demand in 2026

Branded search is any query that includes your brand name, products, or close variants and misspellings. It signals existing demand rather than discovery. You can now isolate it with Google Search Console's branded queries filter, and it increasingly correlates with how often AI answer engines mention your brand.

Key takeaways

• Branded search measures demand you already have; non-branded search measures discovery. You need both, tracked separately.
• Google's branded queries filter - expanded to all eligible sites on 11 March 2026 - splits branded and non-branded performance without regex. [3]
• Branded web mentions correlated 0.66-0.71 with AI-answer visibility in a 75,000-brand Ahrefs study; branded search volume correlated a more moderate 0.35-0.47. [1]
• Treat branded search as a directional trend line, not a vanity number. Watch the slope, not a single percentage.
• Growing branded demand and growing AI visibility increasingly pull the same levers: consistent entities, credible third-party mentions, and helpful content.
• Branded demand is becoming the click moat: in Amsive's 700,000-keyword study, branded queries with an AI Overview saw CTR rise ~18.7% while non-branded fell ~20%. [6]

What is branded search (and what counts as branded)?

Branded search is a query where the searcher is already looking for you. It includes your company name ("Ranketize"), branded products or services, trademarks, and the messy real-world variants: misspellings, spacing errors, and name-plus-modifier strings like "Ranketize pricing" or "Ranketize vs [competitor]."

The opposite is non-branded search - generic, category-level queries like "AI visibility consultancy" or "how to rank in ChatGPT." Those searchers do not yet know who you are.

The distinction matters because the two behave differently. Branded searchers are usually further along; they have a destination in mind. Non-branded searchers are discovering the category. A simple test: if removing your brand name from the query makes it generic, it was branded.

Branded vs. non-branded search: what each one tells you

Think of them as two different instruments measuring two different things.

	Branded search	Non-branded search
Signals	Existing demand, recognition, loyalty	Discovery, category interest
Intent	Often higher, closer to a decision	Earlier, exploratory
What grows it	Awareness work, PR, word of mouth, product	Content, topical authority, links
What it warns you about	Awareness plateaus or reputation issues	Lost share of category demand

Neither is "better." A spike in branded search after a campaign tells you the campaign created demand. A healthy stream of non-branded search tells you the category still finds you when it does not know your name yet. The risk is reading only one: a brand that lives entirely on branded traffic is one reputation problem away from a cliff, while a brand with no branded demand has an awareness problem dressed up as a traffic number.

According to PwC's June 2023 Global Consumer Insights Pulse Survey, 54% of global consumers surveyed preferred to get pre-purchase information via search engines. [4] That wave predates the big AI-assistant shift, but the underlying point holds: both branded and non-branded coverage still matter even as discovery moves toward AI.

How do you measure branded search in 2026?

For years, measuring branded search meant writing regular expressions to catch your brand name and its misspellings. That changed.

The Search Console branded queries filter

Google first announced a branded queries filter for Search Console on 20 November 2025, then expanded it to all eligible sites on 11 March 2026. [3] In the Performance report, you click Add filter on the Query dimension and choose Branded queries or Non-branded queries. You then see clicks, impressions, CTR, and average position split between the two. [2][3]

Two honest caveats:

• It is AI-classified. Google uses an internal AI-assisted system to decide what is branded, and it can misclassify. [2] Spot-check the query list before you trust the split.
• Eligibility is limited. It is not available for sub-properties or for sites with low impression volume, and Google has not published an exact threshold. [3] A full domain property may qualify while a narrow subfolder view does not.

The regex / GA4 fallback

If your property is not eligible, the older method still works: filter Search Console (or GA4 organic landing data) with a regex that matches your brand name and its common variants and misspellings. It is more manual and you own the accuracy, but it is portable across tools and history.

A minimal pattern covers your name plus the misspellings and spacing variants people actually type - for us that would be ranketize|rank etize|ranketise. Two practical notes: Search Console regex uses RE2 syntax (no lookaheads), and you should keep the pattern versioned. If you quietly change what counts as branded mid-year, your trend line stops being comparable.

What is a "good" branded search percentage?

You will see the figure "30-50% of search traffic is branded" repeated widely. Treat it as a loose practitioner heuristic, not a law. The right number depends on category, brand age, and how much demand you have generated. A two-year-old SaaS and a household name should not share a benchmark.

The more useful question is directional: is your branded share trending up, flat, or down over the last few quarters, and does it move when you run awareness work? Annotate launches and campaigns in your reporting so you can read causes rather than guess.

Benchmark against competitors with share of search

Your own branded trend line answers "are we growing?" but not "are we winning?" For the relative view, use share of search: your brand's search volume divided by the total search volume for all brands in your category. Google Trends gives you a free approximation - plot your brand term against your main competitors' and read the ratio. Data reaches back to 2004, so long cycles are visible.

It earns its ten minutes of setup. In IPA-published research, Les Binet found share of search correlates with market share and works as a leading indicator of it - in some categories moving up to a year ahead of market-share shifts. [8] A follow-up analysis by James Hankins across 30 case studies in 12 categories found share of search accounted for roughly 83% of a brand's market share on average. [9] These are associations across many brands, not laws for yours, but as free directional benchmarks go, few metrics carry this much published evidence.

The AI-era framing: share of search and share of AI mentions are the same question asked of two systems - how often does the market reach for your name instead of a rival's?

Why does branded search matter for AI answer engines?

This is the part most branded-search guides have not caught up on.

When someone asks ChatGPT, Perplexity, or Google's AI Overviews "what are good AI visibility consultancies," the model returns a shortlist of named brands. Being in that shortlist is the AI-era equivalent of ranking. So the question becomes: what makes a brand show up?

An Ahrefs study of 75,000 brands looked at what correlates with brand visibility across ChatGPT, Google AI Mode, and AI Overviews. A few findings are directly relevant to branded search: [1]

• YouTube mentions were the study's strongest single signal, correlating around 0.737 with AI visibility across all three engines - a nudge that video and podcast coverage now feed the same machine. [1]
• Branded web mentions - how often the brand is talked about across the web - correlated strongly, around 0.66-0.71, with AI visibility. [1]
• Branded search volume correlated more moderately, around 0.35-0.47 - weaker than mentions, but still positive. [1]
• For contrast, raw site page count correlated barely at all (~0.19), which pushes back on "just publish more" thinking. [1]

Read this carefully, because it is easy to over-claim. Correlation is not causation, and these are associations across many brands, not a promise for yours. But the pattern is consistent with how language models work: they are trained and grounded on text where popular, frequently-mentioned brands appear more often, so a brand with real demand and real third-party coverage is simply more present in the data an AI draws from.

The click data points the same way. In Amsive's study of 700,000 keywords, branded queries that triggered an AI Overview saw CTR rise by roughly 18.7% on average, while non-branded queries fell by roughly 20% - worse when an AI Overview stacked with a featured snippet. [6] And Seer Interactive's tracking of 25 million organic impressions found brands cited inside an AI Overview earned about 35% more organic clicks than when they were not cited. [7] Neither study proves causation - Seer itself notes that stronger brands may simply get cited more - but the direction is consistent: as AI answers absorb generic clicks, branded demand is what keeps the remaining clicks flowing to you.

The practical takeaway: branded search and AI brand mentions are two readouts of the same underlying thing - how known and how talked-about you are. Branded search is the one you can measure cleanly in Search Console today. AI mention share is the one that increasingly decides whether you get recommended. Watching both, side by side, is more honest than watching either alone. This is the core of how we think about our methodology.

A lightweight way to measure the AI side yourself:

• Write 10-20 buyer-intent prompts your customers would plausibly ask ("best [category] for [use case]", "[your product] vs [competitor]").
• Run them monthly across ChatGPT, Perplexity, and Google's AI Overviews, and log whether you are named and how you are described.
• Expect variance. Answers shift with prompt wording, model version, and date, so read mention share over months, not single runs.
• Or take the shortcut: our free AI-visibility scan runs this first pass for you.

How do you grow branded search demand?

You grow branded search by giving more people a reason to search for you by name - and, conveniently, the same moves tend to help AI engines mention you.

• Be consistently described everywhere. One clear, repeated description of what you do, across your site, profiles, and listings, helps both humans and models attach the right meaning to your name. Entity consistency is foundational to AI visibility growth.
• Earn credible third-party mentions. Reviews, comparisons, podcasts, and community discussion drive name searches - and branded web mentions were among the strongest AI-visibility correlates in the Ahrefs data, with YouTube mentions (~0.737) the strongest single factor. Video and podcast appearances count double here. [1]
• Publish content people seek you out for. "[Your product] vs [alternative]," setup guides, and "how to use [your product]" pages turn awareness into branded queries and give AI engines something specific to cite.
• Win the branded SERP itself. Sitelinks, a verified knowledge panel, and a clean People-Also-Ask presence make the experience after a branded search match the intent.
• Run awareness work that compounds. Paid social, PR, and community presence create the demand that later shows up as branded search. Communities like Reddit are one ethical channel for this; see our Reddit marketing approach.

Should you bid on your own brand terms?

Often yes - branded paid clicks are cheap and convert well, and Dreamdata reports branded PPC can reach a return on ad spend as high as ~19x that of non-branded keywords in its own B2B benchmark data - one vendor's customer base, not a universal ceiling. [5] In competitive categories where rivals bid on your name, defending the branded SERP can be worthwhile.

But test incrementality rather than assuming it. Some users who click your branded ad would have clicked your organic result for free. Run a geo or scheduled hold-out, look at total branded conversions with ads on versus off, and keep the spend only where it adds conversions you would not otherwise win.

Honest caveats: where branded search misleads

• It lags. Branded search reflects awareness you built weeks or months ago. A flat line today is not necessarily a failure today.
• It can be inflated. A viral moment, a crisis, or a competitor's misstep can spike branded queries without lasting value. Read the trend, not the spike.
• The branded/non-branded split is fuzzy. Both Search Console's AI classifier and your own regex make judgment calls on edge cases. [2] Keep the method consistent so the trend stays comparable.
• AI correlations are not promises. The 75k-brand figures show association, not a lever you pull for a certain result. [1] Treat AI visibility as directional and non-deterministic - which is exactly how we report it, and why we publish our trust standards.

If you want to see where your brand stands in both classic search and AI answers - and which gaps are worth fixing first - that is what our free AI-visibility scan is built around. Our case studies show how we report the results: sampled, dated, and hedged.