Reading Weekly Trends
Interpret weekly changes in observed AI requests without treating them as citation or referral proof.
Overview
The weekly trend view aggregates classified requests so you can see changes without as much day-to-day noise. Always confirm the selected domain, date range, and request class before comparing periods.
AI-related requests are HTTP requests classified into assistant, training-crawler, coding-agent, or AI-referral categories. They are not unique people or sessions.
What to look for
AI-related Request Share
The AI-related Requests column counts observed requests in the four canonical AI-related categories. The AI-related Request Share column is their share of all observed requests within the selected data. A change in this share proves only a change in the observed request mix. It does not by itself prove discovery, citation growth, or referral growth. Compare the category fields with separately collected sampled-citation and detectable-referral evidence before deciding what changed.
Platform shifts
The per-platform breakdown can reveal:
- New observed identities — a classified platform appears in the selected window.
- Request spikes — a platform makes substantially more observed requests.
- Request declines — observed requests fall, which may justify checking crawler access, deployment health, or classification changes.
These patterns are diagnostic leads. They do not establish why the platform changed its behavior or how generated answers used the pages.
Using the API
curl "https://api.seellm.link/api/analytics/weekly-trend?range=90d&domain=example.com" \
-H "Authorization: Bearer sk_live_..."Using MCP
Ask your AI assistant:
"Show me the weekly observed AI-related request trend for example.com over the last 90 days"
The get_weekly_trend tool returns the weekly summary and per-platform AI-related request breakdown.
Acting on trends
| Observation | Check next |
|---|---|
| AI-related requests increase | Which categories and important pages changed, then compare separate evidence |
| One platform dominates | Classification evidence and page distribution for that platform |
| Requests decline | robots.txt, adapter health, and deployment changes |
ai_referral_requests increase | Landing pages, conversions, and whether referrer coverage changed |
Use the Evidence Model when communicating what each trend does and does not prove.