Introduction
Digital signals—such as product usage data, support tickets, and customer engagement—offer real-time insights into customer health. Integrating these signals into your health scoring system provides a comprehensive view of customer risk, enabling more precise engagement and proactive risk management. This article will guide you through integrating digital signals into your health scores using Gainsight’s tools, ensuring that your health scores are both dynamic and predictive.
Step 1: Identify the Digital Signals to Incorporate
Start by identifying which digital signals are most important for predicting customer health:
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Product Usage: Track how frequently customers are using key features with Adoption Explorer. Consistent usage of core features is often a sign of product adoption and health.
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Support Interactions: Create a custom dashboard to track the volume and types of support tickets using Dashboards. An increase in support tickets might indicate dissatisfaction or friction with the product.
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Engagement: Use Timeline to track how frequently your team engages with decision-makers. Lack of engagement with key stakeholders can signal a risk.
By defining the right digital signals, you ensure that your health scores reflect real-time customer behaviors.
Step 2: Update Health Scores with Digital Signals
Once the key digital signals are identified, integrate them into your health score to make it more dynamic and accurate:
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Automate Score Updates with Rules Engine: Use Rules Engine to automatically update Scorecards based on changes in digital signals. For example, if a customer’s product usage drops, automatically lower their adoption health score.
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Adjust Weighting for Digital Signals: Customize your Scorecards to assign greater weight to signals that are most predictive of customer health. For instance, if low feature usage is a strong predictor of churn, increase its impact on the overall health score.
Integrating digital signals ensures that health scores provide a more accurate and actionable view of customer health.
Step 3: Monitor Health Scores and Risk Indicators
Use Dashboards to monitor how digital signals affect health scores and track overall customer risk:
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Track Health Score Trends: Regularly monitor trends in customer health scores via Dashboards. Identify which digital signals (e.g., low usage or frequent support tickets) are driving score changes.
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Identify High-Risk Customers: Use health score trends to identify customers at risk based on their digital signals. For example, if a high-value customer has consistently low product adoption, flag them for immediate intervention.
By continuously tracking health scores and digital signals, you can ensure that your team addresses risks as they arise.
Step 4: Take Action with Automated Playbooks
Ensure that your team responds to digital signal-driven health score changes by using automated Playbooks:
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Trigger Playbooks for At-Risk Customers: Automatically deploy Gainsight Playbooks when a customer’s health score drops below a certain threshold. For instance, if product usage falls, trigger a playbook that guides the CSM through re-engagement actions, such as offering additional training.
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Customize Playbooks for Different Risk Types: Tailor playbooks based on the digital signals that drive the health score changes. For example, if frequent support tickets are the issue, the playbook might include steps for escalating the issue to the support or product team.
Automating playbooks ensures that your team responds consistently and quickly to customers whose health scores indicate risk.
Next Steps for Success
With digital signals integrated into your health scores:
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Monitor digital signal trends regularly: Use dashboards to track which digital signals are affecting customer health scores most, and ensure your team is prioritizing these accounts.
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Automate playbooks for low health scores: Set up playbooks that automatically trigger when health scores drop, ensuring that your team takes immediate action to resolve risks.
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