Your reps make 200 calls a week. Each one contains objections, competitor mentions, and buying signals. Today, that data lives in recordings nobody watches. Improvado extracts it, connects it, and acts on it — automatically.
See how it works →Call Intelligence
Reps hear the same pricing objection 30 times a month — but marketing doesn’t know, so messaging never changes
A major account mentions a competitor on 4 consecutive calls — nobody connects the dots until the deal is lostFeature requests surface daily in calls — they never reach product in a structured way.
Post-call follow-up tasks get forgotten or delayed — costing deals and trust.
Pipeline reviews are based on rep memory, not actual conversation data.
Why current tools fail: Call recording tools transcribe and tag — but don’t connect call insights to marketing data, product usage, support tickets, or financial impact.
The agent connects your call platforms to every system that gives those conversations business context.
Gong: transcripts, talk ratios, competitor mentions, deal risk signals. Chorus: conversation analytics, coaching insights. Fireflies.ai: meeting transcripts, action items. CallRail: call tracking, source attribution, keyword spotting.
Salesforce: opportunities, stages, contacts, deal history, forecasts. HubSpot CRM: deals, contact timelines, lifecycle stages. Outreach / Salesloft: sequences, touchpoint data, rep activity, response rates.
Objection taxonomy — a structured map of every objection type, its frequency, which segments raise it, and which responses correlate with deal progression. Competitor intelligence — every mention cataloged with prospect types and win/loss correlation. Feature demand signals — requests quantified and linked to account revenue potential. Rep effectiveness patterns — which messaging approaches correlate with deal advancement. Account narrative — a living story of every call, objection, promise, and sentiment shift connected to pipeline stage.
Now that the agent has full call context connected to your entire business, here’s what it does.
Objection patterns, competitor mentions, feature requests, buying signals, sentiment trends. Not one call at a time — all of them, continuously.
Links call insights to deal stage, marketing source, product usage, and support history. A pricing objection from a $500K opportunity is very different from one on a $20K inbound lead.
Creates CRM follow-up tasks with specific next steps. Alerts sales managers to emerging competitor threats. Sends structured feedback to product teams weighted by revenue. Updates marketing on objection trends. Drafts and queues personalized follow-up emails.
"Competitor X mentioned in 34% of calls this week, up from 12%. Top accounts affected: ACME Corp ($420K opp), Globex ($280K opp). Common context: pricing comparison on enterprise tier."
Objection detection
"I feel like pricing comes up a lot"
"Pricing objection in 38% of calls, up 12% MoM"
Product feedback loop
Slow, informal, unquantified
Structured, revenue-weighted, linked to accounts
Follow-up speed
Hours to days
Minutes — AI-drafted, rep-approved
A call tool tells you what was said. The knowledge graph tells you: this prospect mentioned competitor X. They came from a LinkedIn campaign targeting enterprise. Their support tickets increased 40% — they're shopping because their current vendor is failing. Similar accounts that switched converted 73% when offered expedited implementation. Recommend fast-tracking.
Calls analyzed automatically
Insight-to-action time
Objection tracking — trended and segmented