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Sheldon - AI Powered Smart Recommendations (Introduction)


Sheldon is an Artificial Intelligent (AI) system that learns from the behavioural patterns of previously churned and retained customers and helps you to understand their behaviour by providing meaningful insights. Sheldon provides this information in the form of recommendations and anomalies. Sheldon also uses advanced techniques to understand the correlation between Product feature adoption + CSM actions and Retention. This is what enables Sheldon to generate Smart recommendations that lead to retention.

Who is this for?

If you are a Customer Success Manager (CSM) handling a portfolio of accounts, this article will help you use to understand how you can leverage Sheldon's AI Powered Smart Recommendations to drive retention.

What recommendations will Sheldon generate?

Sheldon will generate three kinds of recommendations for you:

  1. Anomaly: Sheldon will cover your blindspots for you and highlight unusual increases and drops in different features used by your customers.

  2. Product Adoption: Sheldon will give you account wise recommendations for which areas of products where adoption can be improved to lower the chances of each account getting churned.

    LTV (Lifetime Value): Customer lifetime value is a prognostication of the net profit contributed to the whole future relationship with a customer.

     LTV =  MRR / Churn Probability

  3. Engagement: Sheldon will monitor your engagement with customers to nudge you to get in touch with the right customer at the right time. This will include all interactions with customers (Emails, Calls, Logs etc.) as well as the CSM activity (Tasks, Playbooks etc.) for each account.

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In most cases, you would have a dedicated Customer Success Manager who will be your point-of-contact for any queries or assistance. You may also,

  1. Initiate a chat directly from within CustomerSuccessBox. Use chat option from the Chat icon in the left side navigation bar
  2. Create a conversation from here
  3. Send an email to
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  1. Deepshikha Chakraborty

  2. Posted