Pipeline analytics reveals patterns in deal progression, conversion rates, and bottlenecks. We build models to forecast revenue accurately, identify stages where deals get stuck, and recommend improvements to accelerate closes.
The Challenge
Pipeline in CRM but nobody trusts the forecast
Deals slip every month, forecast is worthless
No visibility into stage-to-stage conversion rates
Don't know which stages are bottlenecks
Financial planning impossible due to forecast unreliability
What's Included
Analysis of 3-12 months of pipeline history for patterns
Stage-to-stage conversion rates and deal velocity
Stages where deals get stuck or progress slows
Algorithm to predict revenue based on pipeline composition
How to improve conversion and cycle time based on analysis
Why It Matters
Most SMEs have no idea if their pipeline predicts actual revenue. They hope. Pipeline analytics removes hope—you know what to expect based on actual conversion patterns. This confidence in forecasting changes how you manage business.
Accurate revenue forecasting
Identify bottleneck stages slowing deal progression
Optimise sales process based on data
Predict cash flow with confidence
Early warning on pipeline gaps
Make better decisions about hiring and resources
The Process
Audit 3-12 months of pipeline data
Calculate conversion rates by stage
Model cycle time (how long deals stay in each stage)
Identify bottleneck stages
Build forecast model
Monitor and refine month over month
Best For
Sales teams with 3+ months of pipeline data
Businesses wanting accurate revenue forecasts
Companies with complex sales cycles
Leadership teams needing confidence in projections
Complementary Services
CRM data is only valuable if you can see it. We build dashboards showing pipeline health, sales productivity, win rates, and forecasts. Leadership sees the metrics they need; sales team sees what drives them forward.
A sales pipeline in CRM is only valuable if it matches reality. We design a pipeline structure that reflects your actual sales process, sets clear stage criteria, and creates visibility into what's closing and when.
CAC is the most important growth metric you're probably not tracking. We calculate your true customer acquisition cost across all channels, identify which channels are profitable, and optimise spend to improve margins.
FAQ
With good data and consistent process: 80-95% accurate. Depends on forecast horizon (next month more accurate than next quarter).
That's the problem. Analyse why—unstable process, inconsistent qualification, or external factors. Analytics reveals the pattern.
Minimum 3 months, better is 6-12 months. More data = better patterns and accuracy.
Yes. If pipelines have common characteristics (deal size, stage, timeline), we can identify which ones are high-risk and intervene.
Can't find the answer you're looking for? Get in touch
We can help you implement pipeline analytics and start seeing results. Book a consultation to discuss your specific needs and explore how this service can transform your business.