Reach product-market fit using Net Promoter Score
Net Promoter Score: A step-by-step guide to reaching product-market fit by efficiently moving from an NPS survey to an updated roadmap.
If you’ve recently launched an innovative product, you’re probably gathering feedback for the next iterations while following a few metrics to ensure product adoption.
How to ensure your product fits the market? How to ensure your product satisfies users? And if it’s not, how do you identify and prioritize the improvements to develop next?
I answer all these questions in this article by sharing my experience. Using Net Promoter Score (NPS) surveys, I measured and reached product-market fit in 4 months. I’ll walk you through the process I put in place to get tangible results:
- Step #1: Understand the current state
- Step #2: Define an action plan
- Step #3: Send a Net Promoter Score (NPS) survey
- Step #4: Analyze the results and prioritize improvements
- Step #5: Update the product roadmap
At the end of this article, you’ll find a list of reference articles and resources about product-market fit.
I worked as a product owner in a retirement pension organization. I was responsible for a service designed for future retirees. This service lets them complete their files online to request their retirement pension.
I didn’t know anything about this area. Here are some key findings:
- The retirement request represents the outcome of a life of work. Future retirees have high expectations regarding the service provided.
- The product I managed consists of simple forms, but it’s just the visible part of a vast machine in the back office, not very agile, a legacy built in the 60s.
- Future retirees have already requested their pension from several other organizations when they use my online service. Indeed, France has 42 pension funds, each with a different functioning.
Several signals showed that we were far from product-market fit:
- Discussions with customer relationship managers were tense.
- The number of active users was stagnating. Future retirees prefer to request their retirement pension by talking directly to operators.
- Customer support operators in contact with future retirees didn’t spontaneously promote the service.
Step #1: Understand the Current State
Customer support operators are in contact with users, and their work is essential for understanding user dissatisfaction.
They track their discussions on a customer relationship tool. I started by analyzing more than 100 conversations they had with future retirees.
I made several interesting discoveries:
- Future retirees encounter significant but recurring difficulties in their digital journey.
- Operators couldn’t assist users. They didn’t know how the product worked.
- The incidents reported to the IT team were handled case-by-case, and IT wasn’t implementing the necessary product improvements to prevent incidents from happening again.
Step #2: Define an Action Plan
PM shouldn’t stand for Product Manager but for Problem Manager.
After this first diagnosis, I implemented an action plan to solve these issues:
- Weekly meetings with customer relationship managers and the IT team to discuss user difficulties and co-build relevant product improvements.
- Integration of these improvements in the product roadmap.
- Training of operators so that they can answer users’ problems and guide them through the online service.
- Definition of 3 key metrics to align stakeholders around common goals and monitor the impact of our actions.
These three key metrics were:
- Activation: The rate of users requesting their retirement through the online service compared to the total number of requests.
- Task success: The rate of users encountering difficulty compared to the total number of requests made on the online service.
- Happiness: The number of users so satisfied with the service that they spontaneously recommend it to other users.
This last metric is the Net Promoter Score.
Step #3: Send a Net Promoter Score (NPS) Survey
The NPS is a standardized metric for measuring customer satisfaction. You ask your users on a 0 to 10 scale:
How likely is it that you would recommend our[product, service, company] to a[user like you]?
I chose this indicator to measure product-market fit for the following reasons:
- It’s simple to calculate and track through surveys sent by emails.
- It’s suitable for non-recurring use services as a retirement request.
- It fits well with future retirees who are attentive to the recommendations of their peers.
I created a form with the following questions:
- How likely is it that you would recommend our online service to a friend or colleague? (0 to 10 scale)
- What difficulties have you encountered in using this service? (free text field).
The second question collect pain points.
I asked the team to integrate the survey into a confirmation email sent at the end of the user journey because this email had a high open rate.
Step #4: Analyze the Results and Prioritize Improvements
The NPS result comes from the following formula:
NPS = % promoters — % detractors
- The promoters are those who give a score of 9 to 10.
- The promoters are those who give a score of 0 to 6.
Unsurprisingly, the first NPS result was negative: more detractors than promoters.
I, therefore, analyzed the pain points to identify the issues to be addressed. I placed them in a prioritization matrix:
- On the horizontal axis: the average NPS of users who mentioned the pain point.
- On the vertical axis: the frequency with which the users raised the pain point.
I thus distributed the pain points in 4 boxes:
- Springboard box: most frequent pain points from promoters. Solving them would trigger an enchanting effect on users.
- Diving board box: most frequent pain points from detractors. Solving them provides a powerful lever for user satisfaction.
- Ideas laboratory box: less urgent pain points from promoters.
- Pain points to watch box: less critical pain points from detractors.
It’s better to make something that a small number of people want a large amount, rather than a product that a large number of people want a small amount — Rahul Vohra
In theory, I had to prioritize the Springboard box pain points. But as a social protection organization’s vision is to make life easier for all users, I started by prioritizing the Diving Board box pain points.
I analyzed each pain point through user interviews and prototype testing and worked with the team to find the best solutions.
Step #5: Update the Product Roadmap
I reoriented the product roadmap towards priority, dedicating the following sprints to pain point solving. Correlating our work to metric goals motivated us daily and enriched our discussions.
Three sprints later, the result surprised us:
- The rate of users experiencing difficulty with the online service has dropped to 1%.
- The NPS increased to 50 points. It means that users are delighted with the service.
Several months after implementing this approach, we also observed a 3-fold increase in user activation rate.
Beyond these metrics, from an organizational point of view:
- Meetings with customer relationship managers and the IT team became highly productive.
- Customer support operators began to have more confidence in the service, spontaneously redirecting users to it, thus focusing their efforts on complex pension requests.
When it comes to product-market fit:
- Move stakeholders from opinions to objective metrics to share common goals and track progress toward them.
- Have a look at the system as a whole, beyond the product. Listen and understand users’ pain points and the issues encountered by internal stakeholders. Solve organizational problems to reach the product-market fit faster.
- Based on frequency and NPS results, prioritize pain points to solve and separate problem-solving from solution ideation.
More Resources about Product-Market Fit
- The Only Thing that Matters by Marc Andreessen
- When do you Know you Have Product-Market Fit? by Elad Gil
- Before Growth by Sam Altman
- How To Know If You’ve Got Product-Market Fit by Lenny Rachitsky
Product-Market Fit Metrics
- The Startup Pyramid by Sean Ellis
- The Never-Ending Road To Product-Market Fit by Brian Balfour
- The Best Metric for Determining Quantitative Product-Market fit by Jeff Chang
Product-Market Fit Optimization Methods
- Validating Product-Market Fit by Steve Blank
- How Superhuman Built an Engine to Find Product-Market Fit by Rahul Vohra
- A Playbook for Achieving Product-Market Fit by Dan Olsen
- A How-To Guide to Product-Market Fit by Gannon Hall
Product-Market Fit Stories
- Do You Have Product-Market Fit? It’s All About Retention by Casey Winters at GrubHub and Pinterest
- How To Find Product-Market Fit by David Rusenko at Weebly
- The Myths of Product-Market Fit by Greg Davis at Intercom