Use pipeline metrics to become a better closer
As a deal maker, you probably know how well you close. In other words, you may know:
- how long does it take to get a customer,
- what percentage of the people you contact you close,
- how large are the deals you close, etc.
I’ve seen that these kind of numbers make up a formula of success, predicting sales results, and shining a light on what is possible with improved effort and skills. NB! In case you’re starting out as a deal maker, you may want to read about the things you should monitor and improve in order to close more business.
Today we’re introducing Pipeline metrics in the Statistics section – a functionality that helps you see how good of a closer you currently are, and what you need to improve to become a better closer.
Let me walk you through what’s new. Go to ‘Statistics’, and click on the ‘Pipeline metrics’ tab.
There is a drop-down for selecting the pipeline that is displayed (in case you have created multiple pipelines). You can use built-in and custom time filters to see the metrics in regards to a desired period.
A header familiar from a pipeline view of deals represents your sales stages. Even though some of the numbers around it are easy to understand, I’ll break them down one by one:
- ‘New deals‘ — the number of deals that were added to pipeline during the selected period. The more you fill the pipeline with fresh deals, the more chances you’ll have for closing more sales. Of course, one should look for a balanced effort of filling the pipeline, and working with deals already in it.
- ‘Moves between stages‘ — this number displays all the moves from one stage to another during the selected period. It adds up both forward and backward moves, and gives some idea of the “hustle” during the period. If the number is close to zero, we can conclude that open deals have not progressed much further — the bigger the number, the stronger the momentum.
- ‘Average age of deals‘ — this is the average age of all deals (open deals as well as closed deals) by the end of selected period. In other words, how long they’ve been in pipeline. If you can close deals faster (read: win AND lose faster), then you free up time for working with other deals, and bring in the commission faster as well :).
- ‘Deals left open‘ — the number of deals that are still open (if the selected period ends with today), or were still open when the selected period ended. This basically gives you an understanding of the potential of your pipeline in regards to future sales. For example, if the period selected is ‘This month’, then you can see how many open deals you still have in your pipeline (since the period ends today). If the number is too small, then it calls for filling the pipeline with fresh deals.
- ‘Deals lost‘ — the number and value of deals you marked as lost during the selected period.
- ‘Deals won‘ — the number and value of deals you marked as won during the selected period.
- The numbers below pie chart display the conversion percentages at which you won (or lost) deals during the selected period. Of course, the higher the winning conversion, the more of the open deals you are able to successfully close.
- Stage-to-stage conversions are drawn on the pipeline image to show what percentage of deals you were able to move from one stage to the next and not lose them. For example, if you moved 10 deals forward from one particular stage — 6 to ‘lost’, 3 to the next stage, and 1 to ‘won’ — then stage-to-stage conversion at this point is 40% (note that won deal “steps through” all remaining stages in the pipeline on its way to ‘won’ status). If you can improve these conversions, then your overall winning conversion will go up as well. Stage-to-stage conversions are extremely helpful for locating bottlenecks in the process, and literally tell you where and what you should be better at in order to close more business.
I do hope pipeline metrics either provide an expected monitoring functionality to Pipedrive, or mark the start of you becoming more aware of how well you close (in case you have not monitored your metrics before).