Since churn is such an important SaaS KPI it is worth considering additional investments in time, tools and techniques to reduce churn but are Artificial Intelligence (AI) techniques the right approach? It likely depends a lot on your business including target market, price points, Enterprise vs. SMB, etc.
The chief data scientist at
, the subscription automation software provider,
advocates for more classical data science techniques
and believes that AI is not sophisticated enough yet to do the hard work in churn prediction and prevention. However, on the other extreme, the AI application developer
, has developed an
which they believe will help with churn prediction and prevention.
, an AI software vendor has a
of the work that was done at PayPal using their software. Another
, a customer journey analytics software provider, that they indicate uses some AI techniques in their solution.
After having reviewed the above and other information on the topic my view is that, yes, AI can help but there are other methods and issues that should be addressed first. AI is like any other tool but has it's own set of challenges, including the significant challenge of clean and applicable data.
Unless you have a low price point, high volume product and a good sized business you probably are not ready for AI. Instead focus on the items below which I believe are prerequisites to more sophisticated data techniques:
- Defined and documented customer journey - see my blog post
- Customer segmentation
- Tools to manage cohorts
- Usage analytics
- Clean and well understood data
- Appropriate levels of automation for the above
Focusing on the above will give you the basics and as you use these and gain more insights you'll be able to tell whether more sophisticated AI tools make sense to pursue.