Is anyone actually separating brand traffic from category traffic in their reporting?

[JollyFirst]

Genuine question, not rhetorical. When you look at your organic numbers, how much of it is real category demand (someone searching "best casino bonus [country]" with zero prior awareness of you) versus brand demand (someone searching your own name because they already know you, or got pointed there by an affiliate, a forum, word of mouth)?

Reason I'm asking: most of what gets discussed here (backlinks, core updates, schema, AI citations) is about improving visibility, but visibility against what denominator? If 60-70% of your "organic" traffic is branded queries, you're not really measuring SEO or GEO performance, you're measuring how well your brand already travels through channels that have nothing to do with search, and GSC is just crediting the wrong line item for it.

Has anyone here actually pulled their query data apart into brand vs category vs what I'd call crisis queries (your name plus "complaint", "scam", "withdrawal issue", etc) and looked at the ratio between them? In my experience that split tells you more about where the real risk and the real opportunity sit than any rank tracker does. Curious whether that matches what others are seeing, or whether I'm overthinking this.

[Spindex]

Same experience here. We've shifted almost entirely to high-quality editorial placements on real iGaming sites. They're harder to get, but the ROI has been much better than link exchanges or generic guest posts.

[Mark Donowan]

Has anyone here actually pulled their query data apart into brand vs category vs what I'd call crisis queries

I did something similar last year and the difference was pretty eye-opening. I had a case where organic traffic looked like it was growing nicely, but once I filtered out brand queries the picture was much less impressive. A lot of SEO growth was actually people who already knew the brand coming back. The harder part was defining category demand properly. Some queries look non-branded but still have a lot of brand bias behind them because users have seen the site before or are comparing a short list of operators. For me the most useful split ended up being brand/generic commercial/reputation-related queries. It made content decisions much clearer, especially around where we were actually creating new demand versus just capturing existing awareness. I don't think GSC is wrong, but it definitely mixes together very different things that need different strategies.

[abidseo]

Yes, I do this now, and it changed how I read my own numbers. The split I use is simple and strict: brand queries are the site or brand name and close misspellings only, category queries are generic intent with no brand in them, and crisis queries are brand plus complaint, scam, payout or withdrawal terms. I keep crisis separate because a spike there can make brand traffic look healthy while trust is actually falling.

In Search Console I export queries, tag them with those three rules, and then look at clicks and impressions by bucket, not just in total. I also split the landing pages the same way: brand pages, category pages, and reputation or complaint pages. That stops a branded homepage surge from hiding a category page slide, which is exactly the problem you described.

One practical point: do not judge category performance on rankings alone. Compare category clicks with category impressions and with clicks to the same category pages from other channels. If impressions are flat but clicks fall, that points to the search results themselves. If both fall, that points to demand or visibility. That distinction has saved me from chasing the wrong fix more than once.

[SolFayerman]

Good question, and I would push it further. Three buckets is not enough. The one that gets missed is operator-brand demand: searches for the operator's name with a modifier, "X casino review", "is X legit", "X withdrawal times". For most affiliate sites that is the bulk of organic traffic, and it is neither your brand nor category demand.

It belongs to the operator. When they run a TV campaign or sign a sponsorship, your review page traffic rises and nothing you did caused it. When they cut spend, it falls the same way. Plenty of affiliate sites have reported a great quarter that was a partner's media buy, and a bad one that was the same partner going quiet.

So the honest denominator is non-brand, non-operator-brand commercial queries, and on most sites that is a small slice of what the dashboard calls organic. GSC will not split it for you. It takes a maintained regex list of every operator name and misspelling you cover, applied as a filter, and you rebuild it as your brand list changes. Tedious, and it is the only report I have that tells me whether the SEO work moved anything.

[GlobalPokerSites]

We are not, just as a new brand probably no point. I can see it becoming more important as your audience and brand grows though and you start to get brand recognition.

You're right it is probably something not discussed as much as other topics on here also. I'd imagine not many people doing it.

[Bonushajen]

Small data point from my casino site that went live about a month ago, so no brand awareness at all yet. Search Console to 1 November: 387 queries with impressions, 5,963 impressions in total.

Own-brand queries: zero. Operator-brand queries (the name of a casino we review, with or without "recension", "bonus", "uttag"): 96 queries, 1,220 impressions, 20 percent. Generic queries: 291 queries, 4,743 impressions, 80 percent.

The 80 percent looks healthy until you split it by landing page. 1,865 of those impressions are tax questions landing on one information guide. Every review page gets almost nothing but operator-brand queries. Our most visible review has 671 impressions and nearly all of them contain the operator's name.

So SolFayerman's point matches exactly what a new site sees. The commercial pages are riding operator demand we did not create, and the only real category visibility is on an info page that is two clicks from a tracking link. The split took a short list of operator names and a filter in the query export, nothing more. Worth doing from day one, because at this stage the numbers are small enough to read by hand.

[arix]

once the buckets are agreed the thing that makes it stick is putting the classification in one place instead of redoing it per report. a regex per bucket in search console, or in looker studio on the gsc connector, means everyone reads the same definition and changing it changes every report at once.

worth knowing the gsc interface only shows you 1000 rows per view, so the long tail of category queries gets cut off exactly where the interesting demand sits. the api returns the full set and gives you query and page together, which also surfaces the case where a brand query lands on a category page. and keep a monthly export somewhere, gsc only holds 16 months and this split is only really useful as a trend.