Customer churn is one of the most expensive problems facing SaaS businesses, yet most teams rely on reactive indicators like missed payments or support escalations to identify at-risk accounts. By the time these signals appear, it's often too late to prevent the churn.
The Challenge
The challenge lies in synthesizing multiple data sources—product usage analytics, sales call transcripts, support tickets, and account information—into a unified risk assessment. Manual analysis of this data is time-consuming and inconsistent, while simple rule-based systems miss the nuanced indicators found in qualitative feedback.
The Solution
Elvity.ai transforms this complex analysis into an automated system that continuously monitors customer health across all touchpoints, provides intelligent risk scoring, and suggests specific remediation actions based on the unique context of each account.
Example Prompt
From Salesforce, get me all customers with a renewal in the next 6 months and an ACV over $50k.
Next, analyze their product usage. Define high-value events as 'document_sent_for_signature' and 'template_created'.
Assign a 'High' risk level if there's been no activity of any kind in the last 30 days.
Assign a 'Medium' risk level if there's been no high-value activity in the last 60 days.
Otherwise assign a 'Low' risk level.
For each customer, analyze the text from their Gong call transcripts and their Zendesk support tickets. If this analysis indicates additional risk increase the above activity-based risk level.
Also, based on the text assign a 'Primary Risk Category' for each customer which is one of:
- Champion Change
- Competitive Threat
- Feature & Roadmap Gaps
- Usage Disengagement
- Other
Also, based on the text, suggest remedial actions for each at-risk customer.
When suggesting remedial actions, keep in mind that customers that are not negative or upset but are not engaging with the product are often doing so because of lack of training. We should reach out to them, probe for the reasons and offer free training sessions if so.
For customers who are unhappy about product quality it might make sense to ask the Account manager to pull in his/her manager into a call with the customer.
For customers who are unhappy about missing features, the account manager should work with the product manager and try to schedule a roadmap call to communicate timelines.
The attached data is not current, so use Sep 01 2023 as today's date.
Data Sources
This comprehensive analysis combines data from four key systems:
- Salesforce Data: Customer account information including renewal dates, contract values, and account managers
- Product Usage (Segment): User engagement events tracking feature adoption and activity levels
- Sales Conversations (Gong): Call transcripts revealing customer sentiment and concerns
- Support Data (Zendesk): Ticket history highlighting product issues and frustrations
Key Metrics Generated
- Risk Score: High, Medium, or Low churn probability
- Risk Category: Primary reason for churn risk
- Usage Patterns: Engagement level and feature adoption trends
- Sentiment Analysis: Customer mood and satisfaction indicators
- Remediation Plans: Specific action items for account managers
Sample Data Files
Download these files to test comprehensive churn risk analysis:
- salesforce_data.csv - Customer account and contract information
- segment_data.csv - Product usage and engagement events
- gong_data.csv - Sales call transcripts and customer conversations
- zendesk_data.csv - Support ticket history and customer issues
Implementation Benefits
- Proactive churn prevention instead of reactive damage control
- Personalized retention strategies based on specific risk factors
- Early identification of account health issues
- Data-driven account management and customer success planning
- Improved customer lifetime value and retention rates
Advanced Features
- Continuous Monitoring: Automated daily or weekly risk assessment updates
- Alert System: Notifications when accounts move to higher risk categories
- Trend Analysis: Historical risk progression tracking
- Segmented Reporting: Risk analysis by account tier, industry, or region
Get Started
Ready to implement proactive churn risk management?