Experiments on cancellation flow to increase retention and decreased operational costs

Multiple A/B testing that explored increased retention and decreased operational cost during cancellation flow.

Problem and hypothesis

Customers cancel subscription, because of number of captured reasons. The main one is cost of their subscription. At the same time, customers, who can’t cancel in the middle of their contract, often don’t pay and create additional operational cost of collection. Cancellation flow can provide customers with more options, like discount and early cancellation, to drive retention and lower operational costs.

Collaboration and my role

I’ve worked with the team of data analysts, product manager and engineers to come up with risk-reducing A/B to test our ideas. I communicated with stakeholders to keep them up-to-date with risks and measuring success of the experiments. I mapped out user journeys, I created detailed designs, and worked with engineers on iterations to the experiments.

Problem-solving solution

Example of the experiments:

  1. Allowing mid-contract cancellations for customers, who have subscription cost lower than managing collection process

  2. 30% discounts for 6 months

Challenges

Through the process, stakeholders needed to be kept updated regularly with bringing a lot of them through-out the improvements. As a result, a new multi-disciplinary cancellation group was created.

Outcomes for users and business

Mid-contract cancellations provided data that operationally is more cost-efficient to manage the collection process rather than allow customer to cancel mid-contract. 30% discount in cancellation flow did not provide statistically significant result to prove it retains customers.

What I learned

Both of these experiment were start to iterate on ideas and come up with solutions that work for customers and business with proved data.