#21: From knowledgebases to churn predictions

In this edition of #NewThingsInCustomerEducation, we talk about self service knowledge bases and how you can effectively predict churn.

I know most of us skip this part but if you get value from this newsletter, send this to a friend so they can get it too, here's the link

It would also really make my day if you shared this newsletter on Twitter. To make it easy, I wrote a tweet you can use.

Let’s get started.

Best Reads of the week

⌗1. Simran Mohanty, SmartKarrt, shares how to build a self servie knowledge base. (Source: Smartkarrt blog)

What is it about: The piece talks about how to structure a KB, what to include and the range it should cover. Formatting should take care of structure and design. Content should be descriptive and simple. Visuals can include imagery and video. Lastly, it should cover everything and anything.

What we learned after reading the piece: 90% of the customers prefer getting an immediate response via a knowledge base over other channels for their queries (Forrester study) so creating a KB which is like a Google to your product should be a priority.

Our thoughts: Honestly we arent’t a fan of the industry standard KBs. Though they are easy to navigate they are boring. Why many SaaS still have 1000 words on one page of their KB is something atleast we can’t understand. Maybe it is for SEO but that’s a compromise on the primary use of the knowledge base which should be to help users. Fix your KB for customer experience not for Google.

Want to see a great knowledge base?

Look at this one by Coda.

Share

⌗2. Brian Nordli, Built In, discusses effective churn prediction through planning. (Source: Built In)

What is it about: The piece takes opinions from leaders at Drift and 15five about churn prediction, a strategy that factors in customer data to identify clients who are least likely to renew their contracts.

What we learned after reading the piece: A good strategy is looking at data at understanding which metrics are important. Then predicting their health scores. For example with user logins, 15Five’s health target is set at 75 percent of users logging into its platform every 30 days. Shifting to tools like Churnzero over spreadsheets and more importantly focusing on the bigger picture.

Our thoughts: Now we help with churn mitigation rather than prediction but the one line the stuck with us was by Amanda Ingraham, VP of CS at 15Five,“We’re starting to move toward thinking, ‘Every quarter, let’s have a thing and rally behind it’.”
So it can be difficult for CSMs to see the bigger picture when they jump from customer to customer. Building a churn prediction model redirects them to the right path.


Hope you enjoyed reading this edition of #NewThingsInCustomerEducation

Until next time,

Rishabh