Today
- Thousands of opinions across different platforms
- Contradictory signals between audiences
- Averages that hide meaningful differences
- AI summaries whose evidence is hard to verify
Opinions. Evidence. Insights.
Turn customer reviews and feedback into defensible decisions.
Bring reviews, comments and customer feedback from multiple sources while preserving their context. EchoMotive uses AI to turn them into evidence-backed claims and a Decision Brief you can trace to the original observations.
DECISION BRIEF · XM6 EXAMPLE
EchoMotiveDecision Brief
EXECUTIVE FINDING
Comfort evaluations reverse direction across source environments.
Best Buy +66.7Sony −9.1YouTube −71.4
Claim→Evidence→Observation→Source
The problem
Move from “we think” to “the evidence shows.”
With EchoMotive
- Every observation keeps its source
- Patterns are compared across environments
- Claims carry supporting evidence
- Conclusions can be inspected and challenged
Multi-source by design
Different sources. One analysis. Context intact.
Analyze them together without erasing where each opinion came from.
YouTubeProduct reviewsPublic communitiesCSV / ExcelSupport exportsYour own data
01Sourceskept identifiable
→02Observationswith context
→03Evidencequalified
→04Claimstraceable
→05Decision Briefready to use
Source-awareness in practice
The average can be correct — and still misleading.
Aggregate comfort NSS0balanced when pooled
Best Buy+66.7
Sony−9.1
YouTube−71.4
Pooling suggests balance. Source conditioning reveals strongly opposing environments.
Evidence-backed claim
Not another sentiment chart. A defensible market narrative.
Comfort evaluations are strongly positive in Best Buy reviews, slightly negative in Sony-hosted reviews and strongly negative on YouTube; aggregation hides this opposition.
Exploratory COMFORT result from the separately verified XM6 multi-source confirmatory sample: 27 applicable observations.ClaimComfort perceptions diverge substantially across source environments.
↓EvidenceBest Buy +66.7 · Sony −9.1 · YouTube −71.4
↓Observation27 independently verified comfort observations
↓SourceBest Buy · Sony-hosted · YouTube
Trace evidence
The deliverable
A Decision Brief, not another dashboard to monitor.
Every important conclusion carries its evidence trail.
EchoMotiveDecision Brief
VERIFIABLE EXPORT01Executive findingAggregation masks a strong cross-source disagreement in comfort perceptions.
02Evidence-qualified claims
03Source differences
04Key aspects
05Risks & uncertainty
06Supporting observations
07Provenance
How it works
From evidence to a decision in four steps.
- 01
Connect evidence
Choose sources, URLs, files or datasets.
- 02
Analyze
EchoMotive extracts opinions, aspects and source context.
- 03
Build claims
Patterns and differences become traceable, evidence-backed claims.
- 04
Decide
Receive a Decision Brief with evidence, uncertainty and provenance.
Built to be questioned
Credibility lives in the evidence trail.
Product safeguards preserve evidence context and make important conclusions inspectable.
Traceable
From conclusion back to the source observation.
Reproducible
The analyzed corpus and configuration are preserved.
Source-aware
Platform differences are measured rather than averaged away.
Inspectable
Claims expose the evidence on which they rely.
Built for evidence-led teams
Ask better questions of customer opinion.
What do customers actually dislike about the new model — and does it differ by channel?
Do the same perceptions appear across platforms — or only in one audience?
Which issues are widespread enough to act on, and what evidence supports them?
Real-world analysis example
Sony WH-1000XM6: source differences that pooling conceals.
A bounded study of 360 observations: 120 each from YouTube, Best Buy and Sony-hosted reviews. It demonstrates source sensitivity for this selected sample, not a population-wide platform effect.
Read the demonstration analysis360frozen observations
3source environments
27verified comfort observations
“Pooling is not numerically false; it is evidentially incomplete.”
Privacy & control
Your evidence does not have to become somebody else’s training data.
EchoMotive can run with local analysis, local/open models and operator-controlled storage where required. Deployment and retention choices remain explicit rather than assumed.
Local model supportOperator-controlled storageExplicit evidence boundaries
Bring your evidence
Leave with a decision you can defend.
Have a dataset already? Bring it to the demo.
Request a demo