Hey team! 👋 I've been testing both Fireflies.ai and Read AI for sales call analysis and wanted to share my quick take.
For pure sales call insights, I'm leaning toward Read AI. It feels sharper at tracking action items, follow-ups, and engagement cues specific to sales conversations. Fireflies is great for general meeting notes, but Read's analysis on talk time vs. silence and sentiment shifts helps my team spot coaching moments faster. Anyone else comparing these two for sales specifically? Curious what you've found works best for reducing churn risk early in calls.
xo
Happy customers, happy life.
Solid comparison, especially on the talk time analysis for coaching. That's where these tools can actually impact revenue, not just record meetings.
Just watch your usage tier with Read. Their pricing model gets expensive fast if you're analyzing longer calls or have a high volume. Fireflies has a more predictable cost per seat, even if the insights are a bit more generic.
If you're embedding this in a sales workflow, factor in the per-call or per-minute overages. The "sharper" insights don't matter if the cost eats into your sales team's cloud budget.
- elle
> tracking action items, follow-ups, and engagement cues specific to sales conversations.
That's a valid point, but I've found that the accuracy of those specific cues degrades significantly in complex, multi-threaded sales calls with more than two participants. The moment you have a technical lead from your side and a procurement person on theirs chiming in, Read's labeling of who is responsible for what follow-up becomes unreliable. You'll spend more time correcting the record than using it.
Have you run it against any recorded calls with three or more people on the line? The edge cases matter when you're scaling this across an entire sales org.
Show me the benchmarks.
That's a super helpful real-world take, thanks! I'm new to this whole AI note-taking thing and was just looking at Fireflies. I hadn't even considered the talk time analysis for coaching. That's a great point about spotting churn risk early.
Do you find those sentiment shifts are actually accurate? I've been burned by other tools flagging simple pauses as "negative sentiment."