November 4, 2024
When it comes to maintaining account health, it is safe to say that measuring customer sentiment is an important business practice. However, focusing solely on the present moment is not enough. To fully leverage the power of customer sentiment, you need to recognize the value of historical data and start tracking sentiment overtime.
Consider a simple system, using red, yellow, green indicators, where a Customer Success Manager (CSM) updates the colour after every interaction with a customer. While this may give the CSM a sense of where the customer stands, what about other team members or leaders? Without historical context, the sentiment conveyed by these colours lacks meaning and fails to capture the entirety of a customer’s journey.
Here are the three main reasons why historical data is essential for getting the most out of customer sentiment:
Historical data offers the context you need to accurately interpret current sentiment. By understanding past interactions, you gain a better understanding of why a customer may react or feel a certain way in the present.
For instance, consider a scenario where a client account is transferred between CSMs. If the new CSM only has access to the current sentiment, they remain unaware of past interactions, challenges, and successes. Meaning, they lack insight into the client’s journey and will struggle to gauge the current state of the relationship. With historical data, however, the new CSM can review past communications and get up to speed on how to provide personalized support. This kind of continuity is essential for maintaining strong client relationships.
Trends don’t appear overnight, they evolve gradually over time. Tracking sentiment over time brings light to trends, such as recurring issues with implementation of certain product features. Identifying these trends provides insight into the factors that influence sentiment over time, enabling you to identify risks and get ahead of customer dissatisfaction.
Reporting on these sentiment trends empowers CS Teams to make decisions supported by data. This level of informed decision-making would not be possible if only current customer sentiment were recorded.
Effective sentiment analysis extends beyond monitoring the present - it requires measuring the impact of factors such as feature additions or changes in support practices. Access to historical data enables this.
Imagine a scenario, for example, where a customer requests a new feature. Upon implementing this feature, for example, you can visualize how sentiment shifts based on fulfilling this request. If the feature is successful and makes their day-to-day easier, you're likely to see sentiment an improvement in sentiment overtime. This comparison process allows you to assess the direct impact of change on customer satisfaction and make informed decisions moving forward.
To conclude, relying solely on the current customer sentiment lacks the depth and context needed for CSMs to take meaningful actions. It’s like navigating without a map - you have a snapshot of where you are, but you’re lost without knowing how you got there or where you’re headed. By leveraging historical sentiment data, CS teams can anticipate customer needs, mitigate risks, and ultimately, prevent churn.
Interested in a low-cost solution to help you record and track sentiment overtime? Check out Gauge.
