Predictive vs reactive Customer Success methodology.
We have conversed with over 100 capable and knowledgeable Customer Success professionals, across industries, from startups to Fortune 500 companies. In the end, it is clear that there ceases to be an accurate and coherent methodology to produce a customer health score, let alone a predictive one.
We empathize with well-intentioned professionals who have no options but to work with reactive customer scoring. They are forced to rely on subjective scoring often after few-and-far in between customer interactions, resulting in a laggard and subjective score and leaving the time in between unaccounted for. During that time, there may have been a discrepancy between your service and the customer goals. The customer may have already disengaged, considered alternative providers, and stopped using your product due to a resolvable matter.
Customer Success Managers are faced with a choice every day between spending time in front of their customers or spending hours digging through customer data to understand what is going on with every account. They often choose the former as it is just not feasible to go through the details of every account. Often, CSMs can only prioritize the loudest, largest, and upcoming renewing accounts and overlook valuable customers who require immediate attention. But what if Customer Success Managers did not have to choose?
Adaptive Pulse is helping with those difficult choices and changing the status quo by enabling Customer Success Managers to succeed with every account through intelligent scoring. We built proprietary machine learning models that provide predictive scoring, including both qualitative and quantitative customer data points, for a comprehensive score from a single source of truth.
By creating a single source of truth, often leveraging a data warehouse and pipeline, and customer intelligence, we provide not only an intelligent health score but all the relevant customer-like activity and interactions. We save our users up to 10 hours a week by automatically providing critical customer insights for CSM's to act on immediately. Our users are notified just-in-time and always have access to the who and when a customer is at risk or ready to expand and the what and what now to increase retention in their accounts.
Our scores help create new or optimized current customer journeys for our clients across their tiers and help them understand the factors that contribute and define their customers, their journey, or how to retain them better. We automatically pull the fields that correlate with customer retention and include custom fields that pertain to each specific organization or industry to generate a real-time health score. Our machine learning models use this scoring for each customer segment and apply the retention scoring from historical data to predict retention outcomes for current and future customers within similar segments.
We have and continue to replace the dated, manual, and subjective scoring of companies who prioritize becoming data-driven, customer-centric, and proactive towards their customer retention efforts.
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