Real ChatGPT answer · index seed3hlVno95CaYcompleteMarketing and advertising · web analyticscommercial

We need to evaluate three different attribution modeling tools by the end of the day which ones currently offer the most transparent data-driven models for paid media

ChatGPTgpt-61 query11/1/2026
Download run

Fan-out diagram

The searches the AI actually ran for this prompt.

SEED QUERY
We need to evaluate three different attribution modeling tools by the end of the day which ones currently offer the most transparent data-driven models for paid media
1 real search · 1 real-search pass
2026 marketing attribution tools transparency model methodology Northbeam multi touch attribution documentation; Google Meridian open source MMM documentation; Meta Robyn open source MMM documentationGoogle ↗
OBSERVEDComparison

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 (1)
Short factOther / navigationalComparison100%ConsequenceReasonDefinitionInstructionYes / no

Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.

Searches and sources

ChatGPT1 real searches · gpt-6
2026 marketing attribution tools transparency model methodology Northbeam multi touch attribution documentation; Google Meridian open source MMM documentation; Meta Robyn open source MMM documentation Google ↗

Queries

1 queries · click a column to sort
Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
2026 marketing attribution tools transparency model methodology Northbeam multi touch attribution documentation; Google Meridian open source MMM documentation; Meta Robyn open source MMM documentation
OBSERVED
Google ↗
AI Mode ↗
—Comparison——1x
of 1