Why are our lookalike audiences on Facebook experiencing audience fatigue so quickly, and what percentage threshold should we use for refreshing the seed lists?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Why are our lookalike audiences on Facebook experiencing audience fatigue so quickly, and what percentage threshold should we use for refreshing the seed lists?
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). 1 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 Ads lookalike audience fatigue seed list refresh percentage threshold source audience size overlap frequency creative fatigue Google ↗
Meta Ads lookalike audience source audience best practices customer list recency seed size percentage 1% 5% official Google ↗
- Facebook Lookalike Audiences: A Complete Guide · jonloomer.com
- What Is Lookalike Audiences? Definition · adflint.com
- Facebook Ads FAQ · jonloomer.com
- Lookalike Targeting on Others' Journeys: Brand Versus Performance Marketing · cowles.yale.edu
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Meta Ads lookalike audience fatigue seed list refresh percentage threshold source audience size overlap frequency creative fatigue OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
Meta Ads lookalike audience source audience best practices customer list recency seed size percentage 1% 5% official OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |