6 High Usage Accounts That May Still Churn
This infographic offers six types of high usage customers who still may decide to leave:
- If they feel that they have achieved everything they can with the product, and there are no more milestones to hit with the product
- If the key executive sponsor leaves the organization, and the new stakeholder has a different favorite product
- If the customer feels that the product roadmap is not exciting, and that the vendor has stopped innovating
- If the last customer-vendor interaction was a negative one
- If the vendor is not able to justify the ROI achieved from the product
- Competing priorities won the mindshare of the key executives
A good Customer Success process reduces customer churn and increases your revenue, making use of churn metrics. This is extremely beneficial for you – a reduced churn rate of 4% can double your MMR. The main culprit for customer churn is often the onboarding process. The seeds of churn can be traced back to onboarding, the experience could have been painful, or expectations were simply mismanaged.
Customer churn analysis is necessary to get a complete view of your customers’ requirements and behavioral patterns, it helps companies understand who their customers are and what their requirements are, both of which are crucial in the efforts to retain them. Simply because customer churn isn’t binary – there are so many different aspects to it, both intangible and tangible. This makes customer churn prediction a challenge.
With so many different types of customer churn models, having to create a model that satisfies a specific company is a challenge in itself. There is no one-size-fits-all predictive technique that can be designed for a company. There are various intricacies involved in each model and adopting a model that caters to your business objectives is a win for everyone in an organization.
A customer’s digital footprint is scattered across varied data sources, and if analyzed closely, they have a complex story to tell. It can also suggest the appropriate actions that have to be carried out. The need is to understand which data pieces are useful, which metrics are to be tracked, and which KPIs to present. Predictive analytics provides customer churn analytics, and this data can be used to derive the customer churn formula. By analyzing current and historical facts, companies can make predictions about future or otherwise unforeseen client churn.
This infographic was inspired by the article “Product Usage: The Customer Success Blindspot” by Shreesha Ramdas, CEO of Strikedeck. Read the full article at https://bit.ly/2nn2QnC