Revenue Growth

Opportunity-Conversion
Prediction

Know which deals will close — and when — before the quarter-end surprise arrives.

The Challenge

Pipeline confidence is a persistent problem

Sales forecasting based on rep self-reporting and CRM stage progression is notoriously unreliable. Deals marked "commit" slip. Sleeper opportunities close unexpectedly. Leadership makes resourcing decisions on data they don't fully trust.

By the time a deal shows visible signs of stalling, the intervention window has often already closed. The cost isn't just the lost deal — it's the misallocated time, the missed coaching moment, and the forecast miss that erodes credibility.

Signals we analyse

Deal age vs. historical win benchmarks · Stage progression velocity · Rep activity patterns · Engagement frequency decay · Decision-maker involvement · Competitive signals · Deal size vs. win-rate correlations

Our Approach

How we build it

1

Historical Win/Loss Analysis

We analyse your closed opportunities — won and lost — to identify the patterns that distinguish successful deals: stage timing, activity cadence, deal characteristics, and rep behaviour.

2

Lifecycle Benchmarking

We establish expected opportunity lifecycles by deal type, size, and segment — then build deviation models that flag deals diverging from winning patterns before the damage is done.

3

Close-Probability Scoring

Each open opportunity receives a dynamic close-probability score updated as deal characteristics change — giving managers and leaders a live, data-driven view of pipeline health.

4

Forecast & Intervention Tooling

Scores are integrated into your CRM and forecasting dashboards, with flagged deals surfaced to managers with suggested intervention actions and supporting evidence.

Typical Outcomes

What to expect

40%
Improvement in win rate through lifecycle-aligned selling
More accurate quarterly revenue forecasts
Early
Stall detection weeks before deals become unrecoverable
Live
Dynamic scoring updated as deal activity changes in real time
Related Case Study

40% win-rate lift at global scale

A Fortune 500 manufacturer discovered that the anticipated opportunity lifecycle at inception had the most significant influence on win rate — a finding regional leaders initially contested, but which workshops and lifecycle data ultimately confirmed.

Read the case study →

Leadership buy-in through data

When stakeholders pushed back, the client hosted data workshops comparing lifecycle patterns across thousands of won and lost opportunities. The evidence drove lasting changes in sales practice — not just model adoption.

Turn your pipeline into a forecast you trust

We'll show you what your historical win/loss data already reveals about the deals sitting in your pipeline today.

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