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 Zuora, 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 Altexsoft, has developed an approach which they believe will help with churn prediction and prevention. H2O.AI, an AI software vendor has a case study of the work that was done at PayPal using their software. Another perspective is from Pointillist, 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