AI Search Analytics
AI search analytics turns raw AI answers into KPIs a marketing team can run on: visibility rate, average position, recommendation rate, sentiment, and share of voice — per engine, per campaign, per week. Seeqly is one source of truth for everything it measures, and recommends you act on.
- AI Search Analytics
- Marketing teams & agencies
Last updated
The KPI layer
Every Seeqly campaign rolls its runs into a weighted score, backed by the metrics beneath it: visibility rate per engine, average position in list answers, recommendation rate, sentiment trend, and mentions over 7 and 30 days. Every number clicks through to the prompt traces that produced it — no black-box scores.
Audits and the action queue
Analytics that end at a chart don't change anything. Seeqly pairs KPIs with audits that flag what is hurting visibility — citation gaps, uncovered prompt clusters, stale crawls — and a queue of fixes pointing at the next ship, ordered by expected impact.
Drift alerts
When a score moves, you shouldn't have to find out why by hand. Drift alerts pair every significant change with its cause: which engine, which prompts, which competitor or source shifted. The 'why' arrives with the 'what'.
Frequently asked questions
What metrics matter in AI search analytics?
Visibility rate, average position, recommendation rate, sentiment, share of voice, and AI citations — tracked per engine, because engine-level differences are where the actionable gaps live.
How is this different from Google Search Console?
Search Console reports how you rank in Google's index. AI search analytics measures how AI engines answer buyer questions — a different retrieval process, different ranking factors, and mostly zero-click.
Can I export or share the analytics?
Yes — shareable digests are built for exactly this, including read-only views your stakeholders or clients can open without a seat.