Why is my Meta Conversions API event match quality score stuck in the low range, and how can my development team improve it?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Why is my Meta Conversions API event match quality score stuck in the low range, and how can my development team improve it?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
Meta Conversions API Event Match Quality score customer information parameters best practices official documentation Google ↗
Meta Conversions API customer information parameters hashing normalization em event_id deduplication official Meta documentation Google ↗
- Conversions API Direct Integration Playbook · storage.googleapis.com
- Meta Conversions API Extension Overview · experienceleague.adobe.com
- EMQ-Score-One-Sheeter V2 · d3m889aznlr23d.cloudfront.net
- Raise your Meta EMQ score · datahash.com
- Low event match quality in Meta · missingconversions.com
- Connector Insights: Facebook Conversions | Server-Side Connectors · docs.tealium.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Meta Conversions API Event Match Quality score customer information parameters best practices official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
Meta Conversions API customer information parameters hashing normalization em event_id deduplication official Meta documentation OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |