ChurnIQ is an AI-powered subscriber analytics and data platform designed to help Direct-to-Consumer (D2C) subscription businesses reduce churn and increase customer lifetime value (LTV). It provides integrated subscriber analytics, enabling businesses to identify at-risk subscribers and implement smarter retention strategies. The platform offers customizable reports and dashboards, allowing users to predict and prevent churn with AI-driven insights. ChurnIQ helps unlock new revenue opportunities by identifying at-risk subscribers and facilitating the building, execution, and measurement of subscription growth campaigns without requiring code. It automates subscriber segmentation and retention strategies, providing access to hundreds of ready-to-use segments and AI-powered churn models with up to 95% accuracy. The platform unifies subscriber analytics across all channels into a single intelligent dashboard, offering a complete view of subscriber behavior to test, refine, and scale retention strategies. ChurnIQ accelerates revenue growth with unified, predictive subscriber analytics, maximizing conversion and retention for D2C subscriptions across web, CTV, and mobile platforms. Its actionable analytics model optimizes every key step of the subscriber journey, and it offers over 50 out-of-the-box attributes for audience refinement, with the ability to add dynamic behavioral traits. ChurnIQ enables businesses to activate engagement anywhere by connecting to engagement tools for personalized offers and experiments across various platforms. The system provides systematic and predictable churn-fighting strategies, allowing for targeted interventions with 95% prediction accuracy. It optimizes revenue with a 360° view of each subscriber by ingesting data from every app and channel, unifying subscription, payment, support, and subscriber activity. ChurnIQ also reduces data maintenance TCO by 80%, lowering development, infrastructure, and integration costs. It empowers teams with actionable data intelligence for engagement tools, offering tailored engagement and higher retention through rich user profiles and personalized prompts. The platform ensures the right message is delivered at the right time by showing the right moments to deliver targeted prompts and in-app messaging. Seamless marketing integration is achieved by easily connecting ChurnIQ to leading marketing tools like Braze, unifying subscriber data for personalized campaigns. ChurnIQ Studio, with its AI-ssistant, allows for effortless insight discovery, personalization, and analysis of subscriber data, providing instant answers and uncovering hidden patterns. The platform offers simple, all-inclusive pricing with no extra license or setup fees, and is easy to scale. It provides comprehensive revenue and subscriber analytics, including MRR, LTV, churn rate, and campaign performance metrics. The customer segmentation toolkit allows for analysis across various attributes and time periods, while data personalization tools enable tailoring content and marketing strategies. The AI-ssistant chatbot simplifies report generation, making data accessible and actionable for all users. ChurnIQ offers complete data freedom with its flexible report personalization and a data lake supporting over 80 data dimensions, enabling deep understanding and segmentation of subscribers.

Features & Benefits

• AI-Powered Churn Prediction: Identifies at-risk subscribers with up to 95% accuracy to enable proactive retention strategies.
• Unified Subscriber Analytics: Consolidates data from all channels into a single dashboard for a complete view of subscriber behavior.
• Automated Segmentation & Retention: Provides hundreds of ready-to-use segments and AI-driven models for automated retention campaigns.
• Cross-Channel Campaign Activation: Enables launching and optimizing dynamic campaigns across web, CTV, and mobile platforms.
• AI-ssistant for Insight Discovery: Offers an AI-powered chatbot for instant data analysis, report generation, and uncovering hidden patterns.
• Reduced TCO: Lowers development, infrastructure, and integration costs, reducing data maintenance TCO by 80%.