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In typical CRM platforms, Leads, Opportunities and Accounts have a set of statuses as part of the funnel/pipeline management. As an example, a software company may maintain the following stages for an “Opportunity” object in Salesforce:

  • Prospecting
  • Discovery
  • Demo
  • Negotiation
  • Closed Won
  • Closed Lost

One of the challenges for sales teams is to systematically categorize the opportunities for forecasting, tracking, reporting or actionability. For instance, an opportunity might be in “Prospecting” stage but an optimistic sales rep who is new to the organization may set the stage to “Discovery” after an initial conversation. This can be expensive for organizations and may result in improper forecasting or inconsistencies in the way opportunities are tracked at the organizational level. While, sales teams are trained on the processes, there is a very high probability for mistakes because often times, the stages are  manually selected by the reps. In addition, each stage offers a great chance to know more about the customers’ challenges and capture additional data points. In reality, these nuggets of information end up in email, notes or other tools used by the reps.

In our view, the system should present a series of short assessments at each stage of the opportunity. Upon completion of the assessment, system should automatically score the opportunity and update the stage based on a set of rules. Over time, system should leverage machine learning algorithms to recommend the best stage given the historical data. In this blog, we will walk through a simple example to explain how StoryPulse can be leveraged by multiple personas to achieve organizational objectives:

  • Sales Operations or Sales Administrators
    • Objective #1: Define  multiple assessments
      • Define assessments specific to each opportunity stage using Open Rules or other rules engine
      • Define threshold scores for each assessment and distribute them to the field sales so that they can capture useful data points in the field and  in Offline and Online modes (with or without internet).
        • If ProspectingAssessment.Score > 60, Then, Upgrade to  Discovery
        • If DiscoveryAssessment.Score    > 75, Then, Upgrade to Demo
        • If DemoAssessment.Score          > 80, Then, Upgrade to Negotiation
        • If Salesfeedback.Assessment     =100, Then, Upgrade to Closed Won
  • Sales Reps in the field
    • Objective #2: Select specific opportunity and complete the assessment that the mobile device or system recommends based on the opportunity stage.
      • For example, the assessment for an opportunity in the Prospecting Phase may have questions described below.
        • How many hours do you spend on your data challenges every week?
          • 1-2 hours
            • 10 Points
          • 2-4 hours
            • 20 points
          • >5 hours
            • 40 Points
        • Do you have any compliance implications if the data is not validated?
          • Yes
            • 30 Points
          • No

  • System
    • Objective #3: Synchronize the assessment details with back-end CRM platform such as Salesforce. At Focal, we follow the below pattern to push/synchronize data with Salesforce.

Finally, the opportunity gets updated in Salesforce and all the answers to assessment questions are part of the opportunity for future reference. Over time, the Machine Learning enabled Rules Engines such as Open Rules can learn from the existing data and suggest new rules or modifications to current rules in production system.

Cost Perspective

  • The best part in StoryPulse is that it is completely serverless and thus the pricing for dynamic assessments is negligible per change in opportunity stage.

 

For more technical details about this process please refer to the following blog written by Venkat Yerramsetti, a Senior Engineer at Focal. Drop a note at contact@focalcxm.com if you want to know more.