Unlocking The Power Of Data-Driven Decision Making For Customer Success
Having worked on analytics and decision-making for over a decade in the B2B post-sales and customer success domain, I have seen firsthand the challenges companies face when trying to achieve the expected ROI from their customer success investments. Despite the presence of various solutions and product leaders in this area, businesses are still struggling to effectively retain and grow their revenue.
STRATEGIES & EXECUTION DEPEND HEAVILY ON HUMAN INTUITION AND GUIDELINE-BASED WORKFLOWS INSTEAD INSIGHTS-DRIVEN DECISION MAKING
One of the main reasons for this is the disconnect between the promise of a platform and its delivery in reality. Too often, strategies and execution depend heavily on human intuition and guideline-based configurations and workflows rather than data-driven insights.
As a data scientist, I have experience applying various data-driven strategies and machine-learning solutions across various industries. However, I have seen that the term "AI-driven," "data-driven," and "ML-driven" decision-making has become overused and misunderstood in the customer success industry. Many fail to realize that they are not fully utilizing the power of data due to a lack of data maturity, misaligned analytics, and, most importantly, a lack of actionable insights.
