Willingness to Pay / Experimentation
Monetizing a Fintech three years after launch
Role: Contract User Research Lead
Designed and implemented multi-stage study to prepare for going from a free app to a monthly subscription.
Stakeholders: Head of Growth, Head of Marketing, and founders.
Outcomes
The company’s first attempt at monetization was successful! 🥳
60% of existing users upgraded to paid
1000s of new customers signed up for paid product
“How do we charge money for something we’ve offered for free?”
Talk to anyone in Sweden or Norway, and they’ve likely heard of savings app Dreams. But with over 100,000 users, Dreams had yet to make money from the popular app when I joined.
They knew their business model would be based on subscriptions - but “how much to charge?” and “would users all leave?” were the questions on everyone’s minds.
Fellow researcher Ben Dressler and I ran a monetization experiment to asses the risk of charging legacy users a monthly subscription.
Finding willingness to pay
Tension was high. The whole C-suite had opinions about how to charge users, and how much.
But in order to inform a decision that wasn’t made just on gut, we needed to understand the willingness to pay of both the user base and the broader market. Plus, we had to identify a starting price point with a reasonable chance of converting users.
Our plan aimed to answer three questions:
What was the chance of retaining existing users when they have to pay? (Users’ Willingness to Pay)
At what price do we have a high probability of retaining a majority of users?
How likely are we to attract new users from the market who pay immediately? (Market’s Willingness to Pay)
Methods
A/B Subscription test sent to % of users - a small but representative % of users were sent upgrade announcements via email. Half received Price #1, and half Price #2
Landing page test for non-users - we drove ad traffic to a fake copycat app to test demand/willingness to pay among the broader market
Qualitative analysis of responses - we analyzed commentary around the fee test among users to highlight what we needed to address in-product in the near future to make paying more appealing
Comparing two price points
The executive team gave us a few price points under consideration based on the revenue model. We chose two of the price points for our A/B test.
First, we sent out A and B versions of an email to two samples of the user base.
Simultaneously, we launched a landing page test with A and B versions that showed a copycat savings app with the same value proposition and features.
Tests with both users and non-users showed a significant difference in conversion between the two prices.
The key findings and decision
The top findings that led to a price selection and product plans:
01
Significantly more users converted at the lower price. That’s natural, but the difference meant a potentially huge drop-off of existing users if the team chose Price point B.
02
Significantly more non-users converted at the lower price, but more than expected converted at the higher price, too. We hypothesized that the price point was not unreasonable to this audience, and that the Dreams team could expect to convert new users to the product at this higher price in the future.
03
During the test, the word about subscriptions launching leaked to a couple of closed Facebook groups. I ran a qualitative analysis of these conversations among users. While there was some backlash, there were also long-time users defining the Dreams team and expressing understanding of the need to charge for the value they provide. We were able to profile user types based on these conversations and message responses we received during the test.
Recommendation
We recommended that the team launch the subscription at the lower price. Why? Partly because retention was a top priority for management. But we also prioritized retention because of Dreams’ noteworthy recommendation engine.
A large portion of legacy users also frequently recommended the app to others. Written responses received from users who got the higher price were noticeably more negative on average than those at the lower price.
Lessons + Constraints
Charging 💰 after three years? Expect some backlash.
Managers and Owners