I’ve always wanted to work on the next big thing.
I started my career as a product manager, and I enjoyed managing the lifecycle of various platforms and applications, from writing the initial specs to working with engineers to create new features based on user feedback. As I gained experience, I sought new challenges, and the most exciting trend in product development and growth was user research and data.
Instead of dealing with customer feedback surveys, I wanted to apply analytics to drill down to individual user behavior and find ways to improve their journeys as they used a product—not after the fact. I researched applying analytics to SaaS applications and B2B companies, but the books and blogs I read were mostly American. I wanted to apply these concepts to a French company.
Walkie-talkie was growing, but retention was low
In September 2021, I joined Picslo Corp as the Head of Product Growth for Walkie-talkie, a social audio app geared toward Gen-Z users. We had 16 million installs and one million monthly active users. My task was to help the company develop a data-first mindset and solve our number one issue: low user retention.
Walkie-talkie is super simple to use, and our user base was growing like wild. But even though people flocked to the platform, we weren’t retaining users, and people weren’t adding their contacts list to the app after registering as we hoped they would. Our retention rate was less than 8% after 30 days, but we didn’t know why because we didn’t have a data analytics platform and couldn’t establish why users weren’t performing the actions leading to the expected outcomes.
Without data analytics, teams can’t establish why users don’t perform the actions that lead to expected outcomes.
At the time, we were running Google Analytics and Firebase to collect limited user data. We could gather a few high-level metrics, like overall user retention, but we couldn’t look at user events to see what features drove individual retention.
In my previous roles as Head of Growth, I used Amplitude Analytics to track user behavior to boost product growth. Based on our previous success, I recommended Amplitude to leadership at Walkie-talkie. Our engineering team also looked at the Amplitude API to determine the appropriate integrations with Walkie-talkie. It helped that Amplitude offers a free starter package that allows customers to analyze up to 10 million user events a month. Everyone agreed that we should move ahead.
I can’t say enough about Amplitude’s French support and customer success team. They helped us choose the correct settings and deploy the platform in no time.
The importance of segmentation and visualization
We use Analytics to look at how our users interact with Walkie-talkie, what features they use the most, and how much time they spend on the platform. We then use this information to find the best ways to retain them.
Analytics lets me track specific user behaviors and events by segmenting customers into cohorts. For example, I can look at users who use a particular function and see how that translates into retentions. I can also look at user behavior based on when they downloaded the app. I can track what features people use, how much time they spend on the app, and how many friends they have after certain periods of time. Most importantly, we can see whether usage patterns in the first 72 hours predict how long people will continue using the app.
Sharing visual representations of the strengths and weaknesses in your sales funnel is light-years ahead of relying on spreadsheets and customer surveys.
The visualization tools within Amplitude allow me to generate charts and graphs based on user events, behaviors, and cohorts with just a few clicks. I can segment information in dozens of ways and present them as easy-to-understand dashboards and reports that offer far more detail than rows and columns of numbers. I can also use Analytics to pinpoint strengths and weaknesses at specific points in our sales funnel, which is light-years ahead of relying on spreadsheets and customer surveys.
Discovering our true value proposition
Analytics helped us gain some surprising insights into our product.
Our app uses public and private “frequencies,” which are essentially user channels. Users can connect with strangers on public frequencies and with their friends on private ones. We recently launched a new onboarding process where we pushed new users to sign up with their phone numbers and asked them to upload their friends and contacts lists. This triggered them to use the private frequencies first. We figured they’d want to connect with people they already knew, creating a growth loop and increasing retention, but the opposite proved true.
Analytics revealed that the highest retention rate after 30 days was among users who communicated with strangers. It was a startling discovery because it was so counterintuitive. We would never have imagined that users downloading Walkie-talkie preferred making new friends over communicating with people they knew.
Analytics revealed that the highest retention rate after 30 days was among users of the public frequencies. It was a startling discovery because it was so counterintuitive. We would never have imagined that users downloading Walkie-talkie preferred making new friends over communicating with people they knew. But it makes sense because they’re already talking to their current friends on other messaging apps, such as WhatsApp and Messenger.
As a result of this learning, we realized that discovery is our primary desired feature and true value proposition. So, we shifted onboarding focus to push activity on public frequencies. We now let people experience the app first by making and adding three new friends in the first three days. Upon completing this challenge and understanding the benefits of Walkie-talkie, we ask them to share their contacts and invite their current friends to join the platform.
A jump in retention and active users
Changing our onboarding funnel to focus on public frequencies instead of existing contacts had a tremendous impact. Our 30-day retention rate went from under 8% to over 20%. Over 50% of Walkie-talkie users now have three or more friends, and we retain 80% of users with 10+ friends after 30 days.
Our daily active users have more than quadrupled from 70,000 to over 300,000. Our monthly active users have gone from 1 million to 4 million since we started using Analytics, and we’ve seen 12 million more installs. We knew we had a winning app, but Analytics let us see what worked from our users’ point of view.
Catching up quickly
Walkie-talkie is a small company. Our app was created as a side project for two engineers who grew a team of ten to handle product design, engineering, and marketing.
One of my biggest challenges was joining the Walkie-talkie team two years after the app launched. Lacking analytics tools, we had limited metrics, no historical data, plenty of blind spots, and lacked the insight to address our poor retention rates. Analytics provided the building blocks to address these issues.
Today, half of the company uses Amplitude, including our product team, marketers, and CEO. My team started tracking user events and finding the properties and payloads that yielded the most actionable information, homing in on pain points in our user experience, onboarding process, and retention funnel.
Today, half of the company uses Amplitude, including our product team, marketers, and CEO.
I’m proud of using Analytics to retool our user experience and boost our retention rates, and I can only imagine how much further along Walkie-talkie might be if we’d incorporated analytics from the start. Like many startups, we only started thinking about data after we got stuck, and so much information from the early days was lost. When you have analytics and insights from Day One, you know you’re always making the best decisions based on accurate data.
We no longer work with yesterday’s assumptions
Using Amplitude Analytics, we’ve begun to develop a data culture at Walkie-talkie, incorporating analytics as part of everything we do. We tackled the user retention riddle with Amplitude Analytics and saw how better data leads to better outcomes. As we build new features and improve the user experience, we’ll back everything with facts instead of relying on guesses and conventional wisdom.
You can’t build the next big thing with yesterday’s assumptions. We’ve used Analytics to tap into unknown user needs and deliver the products and services people crave.
