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AI Assistant · Deal Intelligence
All deals · Q1 2025
What are the top three reasons we lost enterprise deals last quarter? Break down by competitor.

Hindsight AI

Analyzed 83 enterprise deals closed Q1 2025. Here are the top three loss reasons:
01Integration gaps (Salesforce / QuickBooks)38%
02Pricing — deal size mismatch at late stage27%
03Champion lost internal support18%
Deal #3841Deal #3799Deal #3712+80 more
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Example Queries

Ask about anything that touches a deal.

Competitive

“Generate a battlecard for Competitor X. Use wins from the last quarter and include top objections and how we beat them.”

Battlecards, positioning analysis, win rate by competitor. Built from what actually closed deals.

Win-Loss

“What are the top three reasons we lost deals in enterprise last quarter? Break down by competitor.”

Loss reason analysis, deal patterns, trend breakdowns. Across every deal, not a sample.

Product

“Find deals lost due to reporting limitations. Quantify the pipeline impact and summarize buyer feedback for the product team.”

Feature gap reports, buyer feedback summaries, roadmap inputs. Straight from buyer conversations.

How It Works

Two ways to get answers.

Qualitative

Find and synthesize.

Ask qualitative questions about specific deals, competitors, or themes. The assistant searches across deals, finds the right context, and synthesizes it into a clear answer with citations.

“Summarize how we won the Acme Corp deal against Competitor A. What messaging resonated most?”

AI AssistantFind & Synthesize
Summarize how we won the Acme Corp deal against Competitor A. What messaging resonated most?
Hindsight AI
The win came down to time-to-value messaging and our native CRM integration. Three themes stood out across 4 calls and 6 emails:
Messaging"Deployed in a day" — mentioned twice by champion in final call
Competitor A gapBuyer raised Competitor A's slow implementation 3 times.
Decision makerCTO signed off after seeing the Salesforce integration demo.
Acme call 3Acme proposal emailCTO demo notes
Quantitative

Segment and analyze.

Ask quantitative questions across your entire deal history. The assistant filters, segments, charts, and analyzes without a 25 deal limit. No SQL. No exports.

“Break down win rate by segment, competitor, and deal size for Q1. Show me where we are losing ground.”

Build Deal Dataset×

Create a dataset for quantitative analysis—counts, percentages, trends, and comparisons. The Data Analyst will analyze your data and generate insights.

Name
Comp.
Drivers
Features
Score
Stage
Amt
Date
Zoozzy Deal
H
Deal Reviews (1)
Won
$6KMar 01, 2026
Logitech - New Deal
k
Integrations (2) +2
Lost
$4KMar 01, 2026
Rubrik - New Deal
k
Comp. Monitoring (1) +3
Lost
$4KFeb 28, 2026
Segment - Upsell
k
Deal Reviews (2) +1
Lost
$24KFeb 28, 2026
Realcube Deal
Integrations (2) +1
Won
$6KFeb 28, 2026
Okta - Renewals
k
Comp. Enablement (1) +1
Won
$24KFeb 27, 2026
Databricks - Upsell
Integrations (2)
Lost
$88KFeb 27, 2026
Atlassian - Renewal
Hk
Integrations (2) +1
Lost
$125KFeb 27, 2026
Showing 1–50 of 53 deals

The Output

What the output looks like.

⊞

Battlecard

Competitor positioning, top objections, best responses, win rate. Built from closed deals. Updated every time you ask.

Competitor analysisWin rateObjection handling
⊟

Loss reason breakdown

Top loss reasons by competitor, segment, and deal size. Quantified by pipeline value. Cited from deal records.

By segmentPipeline valueDeal citations
≋

Product gap report

Feature gaps mentioned across closed lost deals. Ranked by pipeline impact. Formatted for the product team.

Feature gapsPipeline impactBuyer verbatims

Get Started

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