An old maxim among trial lawyers states that you should only ask a question to a witness if you already know how he or she will answer. Otherwise you may be in for an unpleasant surprise. For this reason, effective prosecutors and attorneys engage in various pre-trial activities, including “witness preparation,” to help them gain control of the story.
Since many SaaS companies want to increase Net Revenue Retention (NRR) to compensate for weak or declining sales, they may want to take this maxim and modify it by saying, “Before we ask existing customers to renew or expand their subscriptions, we will develop customer success (CS) strategies and activities (“customer prep”) that will help us avoid unpleasant surprises and increase the number of successful outcomes.”
Now comes the tricky part. What types of customer health data should you collect and analyze to avoid unpleasant surprises? And what strategies and activities should your sales and post-sales teams pursue based on this data?
A DARE solution
Essentially, the DEAR Customer Outcomes Score allows you to tie workflows to leading indicators and lagging results.
Historically, many CS leaders have relied on anecdotal evidence and supposed “best practices” in hopes of driving NRR. Even when this approach seemed to work, Customer Success Managers (CSMs) often lacked the empirical evidence to tie success to their team’s good work.
To overcome such strategic “squishiness”, we have pioneered the development of a more scientific, data-driven methodology for scoring and maintaining customer health scores. Known as DEAR (Deployment, Engagement, Adoption, ROI), this framework is designed to help CS teams deliver exceptional customer experiences and lead existing customers to their desired outcomes. In addition to a customer experience score, DEAR also offers a customer outcome score, an objective indicator of whether the customer sees value and ROI on their investment.
Below is an overview of the four components of DEAR.
Keep in mind that to leverage this information efficiently, you need the right technology (ideally customer management software) and behavioral data (ideally telemetry on how your customers use the product).
Has the customer been activated? Are they set up to effectively use what they have purchased? Poor implementation is often a strong indicator of the risk of partial churn or downsell.
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