Explanation of how the 90-day sales Velocity Metrics are used to calculate the new business Prediction.
What are Velocity Metrics
Sales Velocity Metrics are a measure of how quickly your business is winning new deals. A higher sales velocity means you’re bringing in more revenue in less time. The quicker you can grow your pipeline and convert prospects into paying customers, the more successful your business will be.
The five key measures of sales velocity are:
- New deals per month – the average number of new prospects add to your sales funnel each month. This includes all deals in your CRM system, not just the stages included in your QuarterOne sales Pipeline.
- Months to convert – the average number of months it take for prospects to move through your sales stages. The average difference between the date an opportunity was created (the 'create dates') and the day an opportunity starts generating income. By default, QuarterOne uses the opportunity 'closed date' for the date an opportunity starts but 'months to convert' will be calculated based on your chosen field for 'start date' instead if you choose something other than close date.
- Win rate – the proportion of prospects that convert into paying customers over a given period. Calculated as Won deals/(Won deals + Lost deals). This includes all deals in your CRM system, not just the stages included in your QuarterOne sales Pipeline.
- Average deal value – the average value of awarded deals.
- Average deal length – the average number of months revenue from awarded deals is recognised over. We actually calculate the average deal length weighted by deal value so that higher value deals count more towards the average calculation.
How are they linked to the Forecast
The Velocity Metrics for the previous 90 days are automatically used to calculate a new business Prediction in the Forecast - as represented by the values in purple below.
What if the metrics don't look right
If users have recently uploaded lots of data to their CRM or are aware of missing data or recent anomalies, this can cause the metrics and Prediction results to become skewed. If this occurs users can Override particular metric inputs to create alternative Prediction scenarios on-the-fly.