Sentiment analysis reads words. EchoDepth reads the person.
Updated October 2026
Keyword-based sentiment tools have genuine value. But for high-stakes enterprise decisions - earnings calls, HR assessments, change communications - they systematically miss the signals that matter most.
Is EchoDepth just sentiment analysis?
Sentiment tools label words positive, negative or neutral. In under two minutes: what emotion analysis adds, what tone and delivery reveal, and when sentiment is enough.
Read the transcript
Sentiment analysis sorts what customers say into positive, negative, and neutral. It's fast, and it's often wrong in the moments that matter most. Here's a worked example. A customer writes, "Thanks so much for finally sorting it.
Only took three calls and six weeks. Brilliant." Sentiment analysis sees thanks and brilliant and scores it positive. Case closed. Happy customer.
Echo depth reads it differently. Sarcasm, frustration high, trust low, and a customer close to leaving. The right response is an apology, not a thank you email. Now, a second message.
"I'm worried the new tariff will push my bill up. Can you explain what changes?" Sentiment calls it negative, and it's routed as a complaint. Echo depth sees anxiety, but also engagement. Someone who wants to stay and needs reassurance.
That's a chance to keep a customer, not a complaint to manage. Across thousands of messages, those mistakes add up. The wrong customers escalated, the wrong ones thanked, and the real risk missed. Sentiment tells you positive or negative.
Echo depth tells you what customers feel and what to do next. See what your customers feel.
Side-by-side comparison
| Feature | Sentiment Analysis | EchoDepth |
|---|---|---|
| What is measured | Words and phrases | 44 FACS Action Units + vocal + linguistic VAD |
| Input type | Text only | Video, audio, text, image |
| Arousal detection | No | Yes - activation level per frame |
| Cultural calibration | Single-model | multiple cultural cohorts |
| Output granularity | Positive / Negative / Neutral | V, A, D scores + Trust Score per second |
| Pre-behavioural signal | No | Yes - detects resistance before behaviour changes |
| FCA Consumer Duty evidence | No | Yes - timestamped vulnerability record |
Common questions
What does sentiment analysis miss that EchoDepth detects?
Sentiment analysis misses delivery quality, conviction signals, and all the signals present in non-verbal channels - vocal patterns, speech pace and hesitation. A customer in financial distress may use entirely neutral language while showing significant risk signals in voice and delivery.
When is sentiment analysis the right choice?
Sentiment analysis is the right choice when you have high-volume text data that needs rapid classification and the decision stakes are low. For social media monitoring, review classification and helpdesk triage, sentiment analysis performs well. For earnings call credibility, vulnerability detection, interview consistency and change management resistance - you need EchoDepth.
Is sentiment analysis enough for high-stakes enterprise communications?
Sentiment analysis classifies words as positive, negative or neutral, which suits high-volume social, review and helpdesk data. For high-stakes enterprise decisions such as earnings calls, HR assessments and change communications, it systematically misses the signals that matter most. It cannot see delivery, arousal or non-verbal channels, including vocal patterns, speech pace and hesitation, so a customer in financial distress can use neutral language while showing risk in voice and delivery. EchoDepth analyses video, audio, text and images, using 44 FACS Action Units plus vocal and linguistic signals. It returns valence, arousal and dominance scores plus a Trust Score per second, and it detects arousal per frame. For sentiment analysis, the right choice is rapid classification of high-volume text where the decision stakes are low. For earnings calls, vulnerability detection and change communications, the two can be used together, with EchoDepth providing the timestamped, auditable output.
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