Data Driven Product Management allows for each feature set to have a conceptual Business Case, ARR, and P&L. Data Driven Product Design also allows us to Drive A/B Testing to Assess the Overall Utility of the SAAS Platform, and the Marginal Utility Derived by the Feature Set Change.
Anyway we slice it, Data Driven Design is the Glue that Binds SaaS; <Development> <Product Management> <Product Marketing> <Customer Success>.
The following could be a short punch list to build a Product Data Set that can be Leveraged by AI;
- Build Rich Data Points at the Feature Set and Application Utilization Levels: Need to have the Data First.
- Create a Data Equation: Leverage a Weighted Average Feature Set Model to Analyze the Sum of the Parts.
- Identify the KPIs for AI to Feed into: Know What to Change – Baselined A/B Testing Against ARR and Retention.
- Create Agile Communication Flows: Get the Matrix’ed Silos Focused on the Same Change – at the Same Time.
- Mandate Regular Product Updates: Create the Urgency to Execute the Change.
- Incentivise the Team on the Delta ARR: Keep Chasing the Change – and the ARR.
- Create Dynamic In-App Marketing and Feedback Mechanisms: Create additional Product Marketing Channels to support Account Management and Customer Success.
AI can be a catalyst to executing on a Robust Data Driven Product Management Strategy, by Centralizing and Benchmarking the Goals and Objectives (KPIs) of your SaaS Platform.