Wise Insights

How to Apply Machine Learning to Each Phase of the Customer Success Lifecycle

How to Apply Machine Learning to Each Phase of the Customer Success LifecycleMachine learning enables each department in an organization to make the best use of its data and ultimately improve customer success.  Using advanced data science techniques, machine learning goes beyond any individual’s ability to uncover patterns from complex data, learn from past behaviors, and predict future outcomes.  In fact, machine learning can take incredibly complex interactions inherent to each phase of the customer success lifecycle and find ways for an organization to automatically adjust and improve over time.

Any company that collects data can improve customer success and make more profitable, real-time business decisions with machine learning.  Here’s how:

  1. Customer Acquisition: Finding and attracting the right customers.

    • Machine learning can help ensure that your sales team is focused on leads that result in great customers, and that your marketing team can present the best converting content based on individual buying patterns.

  2. Customer Onboarding: Helping customers use your product and obtain value immediately.

    • Machine learning can predict usage patterns that will lead to successful customer outcomes. It makes onboarding more personal and sets a solid foundation for reducing future churn. 

  3. Customer Support: Reaching out to customers to offer assistance, both proactively and reactively as customers use the product.

  4. Customer Expansion: Ensuring that customers get as much ongoing value as possible from the product or service, with an ultimate goal of increasing usage and encouraging adoption of additional services.

  5. Customer Retention: Monitoring for churn threats, incentivizing continued engagement, and identifying trends that indicate retention or churn.

    • Machine learning can identify the at-risk customers and the signals they're demonstrating, while predicting what content or approach will be most likely to re-engage them.

Companies collect a great deal of information throughout the customer lifecycle.  Machine learning enables each department in an organization to leverage this data and understand how customers actually behave now and how to anticipate their future actions.  This knowledge turns insights into tangible assets to drive better outcomes across the entire customer lifecycle.

Thredup Case Study

Topics: Machine Learning, Customer Success