u/Altruistic-Meal6846

Three clients called this month asking why their competitors show up on ChatGPT and they don't. all three are in home services. plumbing, renovation, HVAC. local businesses that were doing fine on Google six months ago

now traffic is down and when i run their brand names or their core queries through ChatGPT and Perplexity they are just not there. competitors are getting cited, getting recommended, showing up in answers for stuff like best plumber near me or top renovation companies in the area. we have zero data on why. no citation tracking, no AI brand visibility monitoring, no way to show clients what is happening or what to do about it

the worst part is i can't even tell them if this is fixable or how long it would takeanyone running local or home services clients dealing with this.

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So i've been running both tools side by side for a few months now across some client accounts and i still can't fully make up my mind

SimilarWeb is genuinely better when it comes to audience demographics. i'm talking real breakdowns industry, age, location, device stuff that actually matters when you're doing b2b targeting. had a client last month ask why their traffic was spiking from a weird referral source and SimilarWeb was the one that told me who those visitors actually were. SEMrush just showed me the spike happened

SEMrush still does keyword tracking better in my opinion. competitor gap analysis, position changes, backlinks it's all cleaner and faster to pull. but every time i need to go deeper on who the audience is it just feels surface level

price wise i'm paying for both right now which feels dumb but dropping either one feels risky for certain clients

anyone else running both or did you eventually pick one? curious if people are finding SimilarWeb more useful as AI search data becomes a bigger part of reporting.

also open to hearing if there's something else people are using for the audience demographics piece specifically.

We are mid audit right now. Auditor sent a sample of 25 user accounts and asked us to provide the approval record for each one showing who authorized access, when, and to what.

For about 20 of them we have Jira tickets. Fine. For 5 of them the access was granted because someone messaged the IT person directly in Slack and they just did it. The DM exists. The IT person remembers doing it. But a Slack DM between two people is not exactly what auditors mean when they say documented approval. No timestamp exported, no approver field, no formal record that the person being granted access had a business need that someone with authority signed off on.

Our auditor was not impressed. We are not going to get an exception on these but we are going to get a finding and they want to see a remediation plan before they close the report.

The frustrating part is that the access itself was completely legitimate. The right person got the right access for the right reason. It just was not captured anywhere that an auditor can sample cleanly. The security was fine. The evidence was not.

We are now retroactively trying to build a lightweight request and approval workflow that is not so heavy that engineers route around it by just messaging IT on Slack again. Has anyone found a middle ground between full blown IGA tooling and pure honor system that actually produces evidence auditors accept?

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