What is Sales Pipeline Analytics?
Most sales leaders analyze their pipeline the same way they’ve done it for years – this is why sales is still a grind, forecasting is still a struggle, and there are still surprises and disappointments at the end of the sales period. Your pipeline analytics should answer these questions with precision:
1. How much new and total pipeline do we need – and will we have enough?
2. Is the pipeline filling at the appropriate rate?
3. Where are deals getting stuck in the pipeline so I can change or coach on those sales activities?
4. Am I converting what’s in the pipeline at the necessary rate?
These questions have to be answered for the whole company, the region or division and for the sales reps. If I don’t know the answers to these questions (and some follow on questions), I may be caught flat footed at the end of the sales period and miss the number. But more importantly, without good answers to these questions throughout the sales period, I can’t make good decisions to improve my process and my reps – costing the company millions in lost deals. Another blog we have related pipeline anatlytics, which is about finding the right sales forecasting tool can be found here
What’s needed is the ability to understand more about your pipeline – where it came from, what happened to it, and ultimately, to understand and predict if I’ll have enough to hit my number. The fundamental components of understanding your pipeline to see if you’ll hit your number are:
- Composition of the Pipeline
- Pipeline Prediction
- Accuracy of the Pipeline
- What Happened in Previous Periods
- Conversion Rates
To learn in greater detail how to understand your pipeline better, download the full guidebook “Analyzing the Pipeline”. A nice follow up to this download is our recent post about increasing conversions through the sales process.
Sales analytics with artificial intelligence is helpful because it can predict the outcome in time for you to make an impact. CSO Insights reports that 94% of their World Class sales performers use sales analytics technologies for better decision making and less digging.