Why switch from Peec AI
Analytics products are an excellent, low-cost first step into AI search — we routinely recommend starting there. This guide covers what to do when the analytics have made the gap obvious and the gap now needs closing.
Arise GEO vs Peec AI
Side-by-side table on scope, model, pricing shape and guarantees — including where Peec AI is the better buy. Read the comparison →
If you are still establishing whether AI search matters for your category, keep running the analytics for another quarter. Evidence is cheaper than a programme, and you should not buy remediation before you have proof of a problem.
Signals it is time to move
- →You have a clear, evidenced gap versus competitors and no plan to close it.
- →Mentions exist but rarely include a link or a citation to your site.
- →Your product and category pages are absent from AI answers entirely.
- →Multi-market visibility differs sharply and nobody knows why.
The migration, step by step
Roughly six weeks end to end. Steps run in order; the change freeze overlaps the handover deliberately.
- Step 01You · Day 1–2
Export the probe history and the query set
Your tracked prompt list is the asset, not the subscription. Export every tracked query, the engines each was run against, the citation and mention history, competitor share-of-voice, and any sentiment scoring. Keep it as CSV — this becomes the continuity baseline so the switch does not reset your trend line to zero.
- Step 02Us + you · Week 1
Audit the query set for commercial relevance
Most AI-visibility subscriptions end up tracking 30 to 50 vanity prompts containing the brand name. Cut those. Rebuild the set around 100 to 300 unbranded buying questions a real prospect would type — comparison, 'best X for Y', pricing, integration and problem-first phrasings. Fewer than 100 and normal model variance swamps the signal.
- Step 03Us · Week 1–3
Establish why you are not being cited
A monitoring tool tells you the citation rate; it cannot tell you the cause. We check the three usual ones: the target pages are not retrievable or not indexed, the brand entity is ambiguous to the models, or the content carries no extractable answer passages. The remediation is completely different in each case.
- Step 04Us · Week 2–4
Fix technical eligibility before touching content
Confirm AI crawlers are not blocked in robots.txt or by the WAF and bot-management rules, that key pages render server-side or are prerendered, that canonicals are self-referencing, and that response times are sane for a fetch-and-summarise agent. Publishing into an unretrievable site produces a flat line.
- Step 05Us · Week 3–5
Anchor the entity graph
One canonical Organization node with a stable @id, sameAs pointing to the profiles you actually control, a named Person entity with knowsAbout for author-level pages, and Product or Service nodes referencing the Organization node rather than repeating it. Ambiguous identity is the most common reason a model summarises you without naming you.
- Step 06Us · Week 3–8
Ship atomic answer blocks on pages already indexed
For each high-value query, a 40 to 60 word self-contained answer directly beneath a question heading, on a page that already ranks and is topically relevant. This is consistently the fastest lever on citation share — movement usually shows within 30 to 60 days on long-tail and comparison queries.
- Step 07Us · Ongoing, from week 4
Re-probe against the imported baseline
Run the same query set, on the same engines, at the same cadence, several times per cycle to control for model output variance. Because you imported the history in step one, the comparison is genuinely like-for-like rather than a fresh start that flatters the new vendor.
- Step 08Us · Week 4–6
Split the probe set by market before drawing conclusions
AI answers vary substantially by locale and language, and a blended global score hides which market is actually failing. Run separate probe sets per priority market, and check hreflang, locale routing and per-market indexation alongside them.
What to keep, not bin
Risks and how we contain them
| Risk | Mitigation |
|---|---|
| The AI visibility trend line resets and you lose the comparison | Import the exported probe history as the baseline so the new measurement continues the same series. |
| Query set changes make before/after meaningless | Keep the original tracked queries running unchanged alongside the expanded set for one full cycle, then retire the vanity prompts. |
| Expecting citation movement in two weeks | Long-tail and comparison queries typically move in 30 to 60 days; head terms take one to two quarters. Anything faster is usually model variance rather than progress. |
Frequently asked
We are mentioned but never linked. Why?+
The model knows the brand but cannot resolve a specific, citable source for the claim. That is an entity and structured-data problem: anchor the Organization node with a stable @id, corroborate it with sameAs profiles you control, and give each claim a page that states it plainly and machine-readably.
Does AI visibility differ by country?+
Substantially. Engine mix, language, and the corroborating sources models trust all vary by market. A blended global score is close to useless for prioritisation — split it per market before deciding where to spend.
Can we keep the analytics subscription?+
Yes, and many clients do as an independent check. We import the history either way so the trend line is continuous rather than restarting at the point we get involved.
