How Often Should You Check Your Site's AI Visibility?

Why cadence matters more than effort

AI visibility problems share one trait: they are cheap to fix when caught early and expensive when caught late. A broken schema block found this week is a five-minute fix. The same break found next quarter has cost you a season of citations and forced AI systems to rebuild trust in your domain from a lower baseline.

That makes checking frequency, not checking intensity, the variable that matters. One thorough scan on a reliable schedule beats a heroic deep-dive audit once a year, every time.

The framework: match cadence to rate of change

Your ideal schedule depends on two things: how often your site changes, and how much an unnoticed problem costs you per week.

Weekly: active sites and revenue pages

Choose weekly monitoring if any of these describe you: you publish content regularly, you run plugin or theme updates on a live site, AI-referred visitors convert into real revenue, or you are actively working to improve your scores and want fast feedback on whether changes helped. Weekly is also the right cadence during and after a site migration, when silent breakage is most likely.

Monthly: stable sites

Monthly fits sites that rarely change: a services site with a fixed set of pages, a portfolio, a local business site that gets touched a few times a year. The site is not generating new risk, so the main threats are external ones like model retraining and competitor movement, and monthly checks catch those trends comfortably.

After every meaningful change, regardless of schedule

Any redesign, migration, plugin overhaul, or robots.txt edit deserves an immediate scan on top of whatever schedule you run. Most catastrophic visibility losses trace back to a deploy that nobody verified from a machine's point of view.

What to actually look at

Whatever the cadence, a useful check covers four layers: crawler access (can AI systems reach your pages), machine readability (schema, meta tags, clean HTML), content signals (freshness, structure, authorship), and outcomes (what AI systems actually say about your domain when asked). A check that skips the last layer measures inputs without measuring results, which is how sites end up technically perfect and completely uncited.

Comparing against your previous result matters as much as the check itself. AI responses vary naturally between runs, so a single snapshot can mislead. Trends across snapshots are what separate a real decline from ordinary noise.

The honest problem with manual schedules

Almost nobody keeps them. The weekly check becomes biweekly, then monthly, then a thing you did in the spring. This is not a discipline failure, it is just what happens to recurring manual tasks that never feel urgent until the day they were.

DidItIndex Monitoring exists to take the schedule off your plate. Pick your URLs, pick weekly or monthly, and the scans run themselves: full 46-check coverage each time, snapshots compared automatically, and an email only when something changed. No news means genuinely no news, not "nobody checked."

The cost is predictable because it uses the same credits as manual scans, 1 credit per URL per run. Monitoring 5 pages weekly runs about 22 credits a month; the same pages monthly cost 5. A single credit pack covers months of coverage, there is no subscription, and unused credits never expire. You see exactly how long your balance lasts before you switch it on.

Pick the cadence that matches your site, set it once, and let the schedule do what manual intentions never quite manage: actually happen.