Establish your Risk Management Framework: Part 1
In a new era of covid-related business volatility, subscription software companies are facing a new normal and that is: adapting to increased risk across your customer base.
Addressing risk of this magnitude requires a comprehensive framework for identifying customer risk, tracking and managing risk through the risk lifecycle, allocating proper resources to address that risk, and ultimately mitigating risk before churn.
Establishing a Risk Management Framework can feel daunting, but this series of three posts aims to break a Risk Management Framework down into digestible and actionable steps you can take to codify, manage, and mitigate customer risk before losing revenue.
Point 1 we’ll cover today, with future posts covering the other two key steps in establishing your Risk Management Framework.
Part 1: Truly understand why your customers leave
Part 2: Build the Framework
Part 3: Drive action in mitigating risk
Let’s get into Part 1, and it’s all about the data.
Craft your assumptions
Before establishing your Risk Management Framework, you truly need to understand why your customers are both reducing and churning.
That means collecting both qualitative and quantitative data about your customers leaving. On the qualitative front, let’s also start from a blank slate. While your company may already have a churn taxonomy in place, let’s throw out preconceived notions. Starting fresh should allow you to think through all the scenarios you believe to be why customers reduce or leave.
This can be done as a part of a weekly meeting with your CSM or Renewals team. You can gather this information from the field in a number of different ways, but I’d suggest a Google Form or Google Doc allowing your team to write down ways they’ve seen customers leave. The exercise here is to collect a number of churn reasons that can be tested as churn assumptions.
After gathering these churn assumptions, plan to summarize into a few key themes. You might notice a few right off the bat. Customers might leave because they go out of business. That’s what you’re looking for.
Review your internal loss data
Your next step is to analyze any data you have about why customers leave. That may include:
Churn / Loss reasons as defined in your CRM
Internal exit interviews conducted by your CSM team
Usage data of recently churned customers
By aggregating this information into a Google Slide Deck you’re starting to gain a better understanding from a few different areas as to why customers leave, and what led them to leave your service. Further, you should start to notice some repeating trends coming from both your internal data set, and the exercise you’ve just done with your CS group above. For example, companies that have layoffs typically reduce with us, or, when our champion leaves we typically lose a contract. You’re beginning to form the basis of your Risk Management Framework, but without external supporting data, what you have now are churn themes and hypothesis. We’ll test those hypothesis next.
Go External
The most impactful action you can take from here is to engage a third party for Loss Interviews. It’s calling in an unbiased third party to interview customers that leave so you can truly understand why those customers decided to churn. Working with a third party removes any bias your internal team might have in classifying churn or reductions. Four vendors that come highly regarded are…
IcebergIQ
These consultants are not cheap, but the value they provide outweighs the cost. They’re doing the hard work of engaging your lost customers into a 45 minute or hour long interview. It’s expensive, but worth the results. In engaging with these consultants, you can present them with your hypothesis as to why you believe customers leave your platform (based on the research you’ve done in steps 1 and 2) and allow the consultants to test these hypothesis after having conversations with actual churned customers.
Allow your Loss Analysis team to conduct interviews of 10 or more former customers (ideally 20+). Realize that those 10 churned customers is not in fact completely representing your entire customer base, and that’s okay. You’re looking for the qualitative data coming from actual customers that have left to back-up your hypothesis you’ve crafted in steps one and two.
Analyze & Share Results
At this point, you should have a solid understanding as to why your customers truly leave.
These reasons will have been backed up by your CSM team, your current churn data, and actual quotes from the loss interviews. In a presentation, be ready to speak to all of the data that was levereged in coming to these conclusions. Direct quotes, recorded interviews, usage data are all particularly helpful in building understanding and empathy in other departments & executives as to why your customers leave.
Present this information to leaders of your company, and be prepared to speak to how your future Risk Management Framework will address these challenges.
In the next two posts, we’ll dig into building the framework itself, and how to proactively mitigate risk through early identification, data, and resourcing.
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