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Introduction

After setting up a foundational health scoring system, the next step is to enhance it with data-driven insights for greater predictiveness. By integrating Gainsight’s data tools like product usage analytics, support data, and customer feedback, you can ensure health scores are more dynamic and actionable. This article will walk you through how to leverage multiple data sources and automate score updates for more effective customer management.


Step 1: Integrate Multiple Data Sources for Comprehensive Health Scores

To make your health scores more insightful, integrate various data sources, such as product usage, support interactions, and customer feedback.

  • Product Usage: Track customer feature usage and engagement depth with Product Analytics.

  • Support Data: Monitor recurring issues using Support Ticket Volume to identify customers facing product challenges.

  • Feedback: Incorporate insights from NPS Surveys and satisfaction surveys to gauge customer sentiment.

Integrating these data points gives you a comprehensive understanding of customer health, making your scores more reliable for proactive action.


Step 2: Identify Patterns and Trends in Customer Behavior

Leverage Gainsight’s analytics tools to spot patterns and trends that can influence your customer engagement strategies.

  • Behavioral Patterns: Use Dashboards to track critical behavioral changes, such as declining product usage or engagement.

  • Churn Indicators: Analyze historical trends using Data Designer to find correlations between certain behaviors and churn risk, such as frequent support interactions before renewals.

By identifying patterns early, you can make adjustments to your customer engagement strategy and mitigate risks before they escalate.


Step 3: Automate Health Score Adjustments Based on Insights

Automation keeps your health scores updated and actionable without manual intervention.

  • Set Rules for Automatic Updates: Use Rules Engine to automate health score updates based on pre-set thresholds. For instance, if product usage drops below a certain level, trigger an automatic health score adjustment.

  • Trigger Playbooks Based on Health Scores: When health scores fall below a threshold, automatically trigger Gainsight Playbooks to guide CSMs through the steps needed to re-engage at-risk customers.

Automation ensures that health scores stay relevant, actionable, and scalable.


Step 4: Continuously Refine Your Health Scores with New Data

Health scores should evolve as new data becomes available:

  • Test for Accuracy: Continuously validate your health scores by comparing them with customer outcomes, such as renewals and churn. Adjust weightings in Scorecards to reflect stronger predictors of churn.

  • Refine with Feedback: Use feedback from CSMs and customers to refine score thresholds, incorporate new metrics, or adjust existing weights based on real-world data.

By refining your health scores continuously, you ensure they remain predictive and aligned with changing customer behavior.


Next Steps for Success

Now that your enhanced health scores are in place:

  • Identify disengaged customers: Use health score data to identify customers at risk of churn and build targeted re-engagement strategies.

  • Automate proactive actions: Ensure that Playbooks and CTAs are set to trigger automatically based on health score changes, ensuring timely engagement and resolution.


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