Developing data-driven customer teams


Why data-driven customer teams matter

Organizational leaders who live and breathe metrics and revenue impacts jump at the chance to be more data-driven. Individual contributors, on the other hand, may not.


Team members responsible for customer success and retention - Customer Success Managers, Account Managers, Support Representatives, and Account Executives to name a few - may be more focused on their relationships with key contacts and their intuitive feel about customer health than on an unseen set of data.


This disconnect creates a barrier to organizations trying to be more data-driven.


After all, if the team members responsible for updating customer health scores and prioritizing deliverables are doing so based on a limited view, then health scores and prioritization are likely to be… wrong. This is how organizations wind up blindsided by churn or overlooking expansion opportunities.


As organizations move toward Customer Intelligence - a holistic view of their customers’ health based on unified data - it’s imperative to bring customer facing teams along on the journey.


How to create data-driven customer teams

Give them easy access to data!

The first, and arguably most essential step in this transformation is to give customer teams access to holistic customer data.


If your teams don’t have an easy (repeat: EASY) way of seeing everything their assigned customers are doing and saying, of course they are going to rely on limited interactions and gut feeling! But if they can prepare for customer conversations by reviewing an all-in-one dashboard of product usage, support tickets, sentiment, and more, they’ll be better able to situate those one to one interactions within the context of customers’ broader health.


Help them understand the risks of an intuition-led approach

Walk through postmortems of churned accounts or upsells with your teams – What signs did you miss? What data points did you rely on too heavily? Whether unpleasant or happy, review surprises like unexpected churn or upsell for examples of how intuition led your teams astray. Keep the tone of such reviews supportive, collaborative and growth-oriented, not blaming or disciplinary.


Understand the key indicators of health for your customer base, and help your customer teams use them proactively.

If you have the capability to run data analyses, try to understand the historical impact of specific customer behaviors on renewal, and educate customer teams to be especially proactive in these areas. If, for example, you find that low NPS scores aren’t meaningful to churn, but that low usage of a particular product feature is, customer teams should spend more time addressing feature adoption than working through NPS comments, despite what their intuition - or key contacts - might be telling them.


An early warning system is game changing

Involve.ai provides comprehensive customer data in a single view, with one, easy login for customer-facing teams. It can help them see what behaviors and data they missed in past surprises, as well as predict future health and recommend specific data-driven actions for them to take.


Intuition is important, but it’s not enough. And Customer Intelligence is only successful if your full organization embraces it. Book a demo to learn how involve.ai can help.


In the meantime, Account Manager Ryan Loughlin shared a first-person account of his own data-driven transformation in our Community, the CI.ty. Share it with your teams as a starting point!

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