CAUSALGEO™

Know why your AI visibility moved, not just what changed.

CausalGEO™ is the first AI-visibility engine built on causal inference, not correlation. Every visibility movement is decomposed into your changes, competitor moves, and engine drift, with 95% credible intervals on every estimate.

DIRECT ANSWER

How does CausalGEO attribute visibility changes?

CausalGEO attributes visibility changes by comparing observed AI visibility against counterfactual baselines, separating your content edits, competitor actions and engine drift into distinct measured effects.

WHAT YOU GET

The line, the cause, the receipts.

Every other tool stops at the chart. We tell you why it moved.

Visibility across engines

The line you've always been able to plot. The one every other tool stops at. Hover anywhere to read the day's value across all four engines.

Last 24 weeks
ClaudeChatGPTGeminiPerplexity
0%15%30%45%60%3 Feb27 Feb23 Mar16 Apr10 May3 Jun
Claude visibility dropped 11 pts in the last 2 weeks. Was it you, a competitor, or the engine? CausalGEO™ answers that.

Three causes. One number per cause.

Every visibility movement is decomposed into your changes, competitor moves, and engine drift — with attribution share, so you stop crediting the wrong actor.

Your interventionspages shipped, schema added, PR placed
4%
Competitor moves47 comparison pages quietly shipped on Tuesday
78%
Engine driftunannounced retrieval-stack tweaks, model bumps
18%
Posterior probability, never p-values. Every attribution ships with a 95% credible interval.

Other tools are thermometers. CausalGEO™ is the doctor.

A thermometer reads the number. A doctor tells you what caused it, what fixes it, and how confident they are. Same difference as correlation vs. causal inference.

Other tools
Count visits. Plot the line. Call it done."Visibility went up 5% — your edit worked!"
CausalGEO™
Diagnose the cause. Quantify the gap. Show the uncertainty."+1.2% [-1.8%, +4.1%], posterior 0.42 — indistinguishable from zero."
What we actually compute
ObservedCounterfactual

The dashed line is what your visibility would have done if the change in question had never happened. The gap is the effect. The gap, with credible intervals, is the answer.

Built by researchers.

The methods behind CausalGEO™ draw on decades of work in causal inference and time-series modelling — the same statistical lineage that powers ad attribution at the world's largest internet companies.

The first and only AI-visibility platform built on causal inference. Every other dashboard is still just plotting correlations.
20+yrs
in AI research, from expert systems to Causal AI
95%CI
credible intervals on every effect estimate
Counterfactual decompositionSee the line you observed alongside the line you would have seen, with the gap quantified.
Robustness tests on every resultRe-runs the same analysis on the period before your change. If it "detects" an effect that couldn't exist, the method is wrong — and we flag it.
Cause separationYour edits, competitors, and engine drift modelled as distinct interventions and ranked by attribution share.
Read the methodology →

Stop guessing. Stop crediting the wrong actor. Stop shipping on hope.

Fix root causes, not symptoms. Connect your domain and we'll separate the real wins from the noise across every AI engine.