Building the Sales Process and the Predictive Pipeline Dashboard
August 21, 2020
In previous blog entries we’ve covered some of the basic building tools used for constructing a sales process within the CRM. Using the “Steps” and “Actions” section in the Leads area will help keep everyone using the same process, the same check points, and the same tools used in predictive analysis. In addition to building the “Steps” and “Actions” of a sales process, there is another set of data tied to the sales history and it is used to help determine the potential revenue in the sales pipeline.
As an example, let us say there is a “Step” in the sales process called “First Engagement with a Customer” and it has a set of three matching “Actions” assigned to it. The three actions assigned to this new “Step” are “Phone call conversation”, “In-Person interaction”, and “Email Response”. Each “Action” assigned to this “Step” represents a specific percentage of completion within the sales process as a whole. This percentage value can play a vital role in determining where in the process this potential customer falls and knowing how much more effort is needed to close this potential customer.
Determining the weight of importance on an “Action” can be difficult, but in doing so, will make sales predictions much more accurate.
If your sales process ends up having only have four main steps, it makes sense to have each step represent 25% of the process as a whole. These types of assignments will ultimately give everyone in the organization a more accurate picture of the health of sales. Should the weight of one of the “Steps” require more effort, then the percentage assigned to the “Step” should be updated to accurately reflect the level effort needed.
Once the percentage of completion is assigned to the “Steps” and “Actions”, you can also assign the pipeline dollar value associated to the lead. This allows the Leads Dashboard to plot out the percentage of completion and the potential incoming revenue.
A platform such as this is only as accurate at the information provided, however when used properly, the value added can be extremely important for forecasting the next month and future growth in a specific market.