Currently, when a sub-account initiates cancellation within the app, they are presented with a question about their reason for leaving. While this provides valuable feedback, it doesn't actively try to retain the customer. This proposal suggests integrating a retention flow into the cancellation process, offering a compelling reason for the user to stay. Proposed Solution: Implement a phased approach to build a robust retention flow: V1: Basic Retention Offer (Skateboard) * Goal: Introduce a simple retention mechanism to capture some immediate wins and gather data. * Features: * Single retention offer presented to all canceling sub-accounts. * Offer type: Discount on the current plan (e.g., 10% off for 3 months). * Simple acceptance mechanism (e.g., "Yes, I want to stay" button). * Basic tracking of offer acceptance rate. V2: Segmented Offers & A/B Testing (Bicycle) * Goal: Refine the retention flow by targeting specific user segments and testing different offer types. * Features: * Segment users based on plan type (e.g., offer a free add-on to lower-tier plans, offer a discounted upgrade to higher-tier plans). * Introduce A/B testing to compare the effectiveness of different offers (e.g., discount vs. free add-on). * Track acceptance rates for each segment and offer type. * Gather feedback from users who decline the offer. V3: Advanced Customization & Automation (Race Car) * Goal: Maximize retention by personalizing offers and automating the process. * Features: * Advanced segmentation based on usage behavior, cancellation reason, and other relevant data. * Personalized offers tailored to individual user needs and preferences. * Automated offer delivery based on user behavior (e.g., trigger a retention offer if a user hasn't logged in for a certain period). * Integration with other HighLevel features (e.g., email marketing, workflows) to create a seamless retention experience. * Comprehensive reporting and analytics to track the effectiveness of the retention flow and identify areas for improvement. Further Enhancements (Beyond Race Car): * Predictive churn analysis: Utilize machine learning to predict which users are most likely to churn and proactively target them with retention offers. * Gamified retention: Introduce gamification elements (e.g., points, badges, rewards) to incentivize users to stay engaged and loyal. * Win-back campaigns: Develop targeted campaigns to re-engage customers who have already canceled. Benefits: * Reduced churn rate: Proactively address customer churn by incentivizing users to stay. * Increased customer lifetime value (CLTV): Encourage customers to remain subscribed for longer periods. * Improved customer satisfaction: Demonstrate a commitment to customer retention and provide valuable offers. * Valuable data insights: Gain a better understanding of why customers cancel and what types of offers are most effective in retaining them. Implementation Notes: * Ensure the retention offer is prominently displayed and clearly communicated during the cancellation process. * Make it easy for customers to accept the offer with a simple click or button. * Track the effectiveness of the retention flow and make adjustments as needed. This feature enhancement has the potential to significantly impact HighLevel's bottom line by reducing churn and increasing customer lifetime value.