+267% AI Citations with EntityMap: a Bing Case Study | Waikay®
+267% AI Citations with EntityMap: a Bing Case Study
17 June, 2026
EntityMap on waikay.io: what the Bing data shows
We installed EntityMap on waikay.io in week 12 of our tracking window. No new content. No backlinks. No other changes. This is 19 weeks of Bing Webmaster Tools data, analysed honestly.
Source: Bing Webmaster Tools Surface: Copilot & Partners Baseline: 11 weeks pre-install Post-install: 7 weeks Site: waikay.io (B2B SaaS)
3.7× Total citation lift, pre vs post install avg
+54% Unique pages cited, pre vs post install avg
1,063 Peak citations in a single week (week 19)
6 New English pages entered cited set post-install
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Key Findings
Two findings worth your time
Finding 01
AI shifted from citing broad guide pages to citing product and feature pages. BOFU citations up 406%. TOFU citations down 80%. Total English volume barely moved. The citations did not disappear. They moved to the pages that convert.
Finding 02
Citations per page went from 3.65 to 8.55 on average. The retrieval layer is not just finding more pages; it is extracting more value from pages it already knows. That is the mechanism EntityMap is designed to trigger.
The overall picture: both needles moved
Before install (weeks 5 to 11), waikay.io averaged 167 Copilot citations per week. After install (weeks 13 to 19), the average was 614. That is a 3.7× lift measured over the same number of weeks, with a single intervening change.
Weekly citations and pages cited: waikay.io Copilot & Partners · Source: Bing Webmaster Tools · EntityMap installed week 12
167 → 614
Citations per week, pre-install avg vs post-install avg
3.65 → 8.55
Citations per page ratio, pre-install avg vs post-install avg
Summary of citation shifts
EntityMap did not increase English citation volume. It restructured which pages get cited, shifting from broad TOFU guide hubs toward BOFU product pages. The commercial value per citation went up even as the raw count stayed flat.
A note on the aggregate numbers
The 3.7× headline is real, but 75% of the volume lift is carried by multilingual pages (French and Spanish URLs that surged dramatically after install). The mechanism is different from what the spec is designed to produce on individual English pages.
Why this pattern points at EntityMap
1. The ratio divergence
If an external factor drove the lift, you would expect citations and pages cited to scale together. They did not. The ratio of citations per page went from 3.65 to 8.55 on average.
2. New pages entered the cited set without new content
Six English pages that received zero citations before install entered the cited set after install, including the features page and the about page. No new content was published on any of them.
3. The citation shift follows EntityMap’s entity graph
The pages that surged: /brand-visibility-tracker/, /ai-audit/, /factual-accuracy/ are precisely the pages that EntityMap represents as named entities.
Page-by-page breakdown: funnel stage, lift, and hidden value
| Page | Stage | April | Now | Change | Hidden value |
|---|---|---|---|---|---|
/ai-audit/ |
BOFU | 29 | 114 | +293% | Highest-intent page on the site. |
/brand-visibility-tracker/ |
BOFU | 1 | 107 | +10,600% | Near-zero before install, now the third most cited English page. |
/prompt-tracking/ |
MOFU | 48 | 110 | +129% | Evaluation-stage content. |
/nike-ai-visibility-action-plan/ |
MOFU | 28 | 48 | +71% | Social proof content. |
/how-to-turn-llm-noise-into-brand-strategy/ |
MOFU | 3 | 19 | +533% | Strategic positioning content. |
/brand-reputation-management/ |
MOFU | 8 | 17 | +113% | Adjacent use-case page. |
Conclusion
EntityMap provides a structured approach to improving citation distribution, emphasizing a shift in content that drives conversions rather than just visibility. The installation of EntityMap serves to enhance the AI’s understanding and retrieval of pages, demonstrating a clear impact on citation patterns and overall content effectiveness.