AI Sales Call Analysis
What one call actually tells you.
A transcript is a record of words. Bylda reads a conversation the way an experienced manager does — the questions, the order, the pauses, who held control — and turns it into findings you can act on.
Transcription is not analysis
Accurate transcription has been a commodity for years. Every vendor has roughly the same word error rate, and none of it answers a manager's question, because the interesting information in a sales call is not the words — it is the structure.
Who asked the questions. How many, and how open. Whether discovery happened before the pitch or after it. How long the rep waited before answering an objection, and how long they talked once they started. Which moment the buyer stopped asking questions. Whether the person who signs was even in the room.
Two calls can contain nearly identical words and mean opposite things. The difference is in the order and the timing.
From conversation to finding
Bylda works in stages, and the vocabulary is precise because the stages are distinct.
Illustrative example — product shown with example data
Worked example
The same three minutes, read two ways.
A transcript search for "too expensive" finds the objection. It cannot tell you that the objection was invited, or that the response made it worse.
Bylda reads the sequence: the price landed before any decision criteria were established, the buyer's question rate dropped to zero immediately afterward, and the rep filled the gap with 90 seconds of unprompted justification. Three observations, each verifiable, that together explain an outcome the CRM recorded as "Lost — Price."
- Question count and quality, per speaker
- Discovery duration and what it covered
- Response latency after each objection
- Talk-time distribution, and where it shifted
- Attendance — who was actually on the call
- Turning points, with timestamps
Turning point
09:12 — price introduced. Buyer engagement did not recover.
CRM RECORDED THIS DEAL AS LOST — PRICE
Illustrative example — product shown with example data
What Bylda reads, and how it holds itself to it.
Call-analysis products often imply they know how people felt, then ask you to take it on trust. Bylda scores tone, emotion and sentiment, and holds those scores to the same standard as everything else on this site.
Every reading is tied to a moment you can replay: the words and the delivery at that timestamp, with a confidence level beside it. A shift in sentiment is shown on the call timeline next to what happened just before it, so you can see what moved it.
Bylda reports these as signals about a conversation, not verdicts about a person. A rise in frustration at 18:42 is something to listen to and ask about, not a rating of the buyer or the rep. Readings from voice and language are probabilistic, so each carries its confidence, and a reading with too little evidence is flagged rather than shown. Bylda does not type personalities.
FAQ
Sales call analysis, answered.
Start with structure rather than words: count and classify the questions each side asked, measure how long discovery ran and what it covered, note where pricing landed relative to decision criteria, measure how quickly the rep responded to each objection and how long they then talked, check who actually attended, and mark the point where buyer engagement and sentiment changed. Those observations explain outcomes; a word-level transcript does not.
Three things first. Whether discovery preceded the pitch. Whether the person who signs was ever present. And whether the stated loss reason matches the conversation — "lost on price" very often turns out to be a deal where price arrived before value or criteria were established, which is a sequencing problem rather than a pricing one.
Keyword search tells you a topic came up. It cannot tell you the topic came up in the wrong order, or that the response to it doubled the rep's talk time. The information in a sales call is largely structural — sequence, timing, distribution — and that is what Bylda measures.
Yes. Bylda scores tone, emotion and sentiment alongside observable delivery such as speaking pace, pauses, interruptions and response latency. Each reading is tied to the moment it came from, so you can replay it, and carries a confidence level. Treat it as a signal to investigate, not a verdict on a person.
Read the call, not the transcript.
Send us a lost deal. We will show you what the record left out.