How Appfire Developed and Evangelized a Common Activation Methodology

Insight/Action/Outcome: With one of Appfire’s Jira apps, they knew the onboarding experience wasn’t ideal. They worked to standardize and revamp the page, which they hypothesized would increase the number of people getting to the signup stage. Their experiment led to a 117% increase in users reaching the signup moment.

Everybody talks about being data-driven. But without the right tools, smart processes, and a team of excellent people, it can be difficult to make the shift.

At Appfire, we develop software that enhances, extends, and connects the world’s leading platforms, including Atlassian, Microsoft, monday.com, and Salesforce, enabling teams to thrive and do their best work together.

Over one million users rely on us to help them overcome the limitations of their ecosystems and personalize their workflows.

When I first joined Appfire, the company only had about 70 people and a portfolio of about 50 apps. I quickly learned that our apps were instrumented by developers, primarily with developers in mind since we didn’t have a product management function when analytics were first implemented. The event structure wasn’t documented and was different for every instrumented app, so there was no point of reference. In addition to the lack of instrumentation documentation, the existing data structure was inflexible. Combine all of these together, and our ability to conduct any meaningful analysis was hamstrung.

This isn’t an uncommon scenario, but what was exciting to me was Appfire’s eagerness to become more data-driven—we just needed to determine how we were going to get there. The company was growing fast. We were bringing on new team members and expanding our leadership team. The goal was to become a more product-led growth (PLG) company, and we needed to create a standard activation methodology as part of the shift.

Bringing on the best in class

I have experience with several different analytics platforms, but Amplitude Analytics has always felt like the frontrunner. Unlike Amplitude, other platforms I've used in the past did not live up to the hype. Some platforms struggled to make instrumentation a straightforward process, which meant I spent what felt like too much time just trying to arrive at insights. Other platforms weren’t flexible enough to handle specific logic, so the team and I had to make a significant investment in structuring the data in a specific way just to ensure that the events came through exactly how we wanted them to. A few platforms suffered from both of these drawbacks.

On the other hand, Amplitude offers the best of both worlds: an easy and straightforward instrumentation process and a flexible interface that allows you to quickly derive insights from your data.

Another big advantage of Amplitude is data democratization. Everyone in the company should be enabled and empowered to use data, from your product marketers to designers and engineers. Amplitude makes it easy for people to quickly learn how to pull up events, segment users, and look at the data in several different ways. With Amplitude, I can educate the product marketing managers (PMMs) on how to pull data from the platform so they can get what they need, but I can also collaborate with our analyst team to take a deep dive into some tough questions.

Developing and evangelizing our activation methodologies

One of my first goals upon joining Appfire was to understand our activation metrics. I was responsible for the go-to-market strategy for several apps, and I was eager to dive in. Pretty quickly, I discovered a mix of random events streaming unreliably into what was, at the time, Appfire’s analytics platform. I realized then that the future of any meaningful activation analysis looked bleak. But not all was lost and as my role at Appfire evolved, I found myself in a position to influence how we structured and analyzed our activation data moving forward.The first step in our journey was deciding on a standard yet flexible activation methodology that could span our vast portfolio of 100+ B2B apps and products. After considering several approaches, we decided to define activation—based on Reforge’s approach to activation—as a journey with four consecutive moments: signup, setup, aha moment, and habit. Once our activation methodology was established, we went on a “tour,” sharing Appfire’s new approach to activation in sessions targeted at getting the product, product marketing, design, and engineering teams on board and on the same page regarding how we mapped and measured activation across our apps.

The next step was to sit down with individual product teams and, using our activation methodology, help them define activation journey maps for their specific apps. During these sessions, we agreed upon analytics events that would be used later to build the journeys out in Amplitude. At the same time, our growth platforms team also worked with these teams to instrument Amplitude in the apps. The teams could then take the events we created during our activation journey sessions and add them to their initial Amplitude event plans. This process allowed us to build the product activation funnels in Amplitude almost instantly after the analytics launch.

By operationalizing this approach to activation, we’re now able to deliver about eight activation journey maps and Amplitude implementations a month. Everyone on our growth team is now an expert at mapping these journeys and running implementations. We have also successfully brought all of the different product teams onto the same page, which has resulted in all of us now speaking the same language and using the same tool to improve activation in Appfire’s products.

Identifying (and remedying) activation gaps through experimentation

Even before bringing on Amplitude, we were beginning to pilot our new activation methodology with various teams with the goal of working out the kinks. By the time Amplitude Analytics was up and running and we were starting to get into implementations, we already knew what we were doing, so we only had to do a few more trial runs with Amplitude. This allowed us to move quickly, and we could partner with different product teams on activation experiments. We created a model where we would partner with a product team on multiple cycles of activation experiments aimed at improving an app’s baseline activation metrics, which we were able to view in Amplitude Analytics.

Throughout those cycles, we leaned on Amplitude for deeper insights into the activation friction points in our apps. Activation comes right after acquisition, and it’s the first barrier to entry that customers hit when trialing our products. If they don’t activate, then the chance of a purchase or retention drops significantly. This means it’s critical to activate new customers as quickly as possible.

In one case, we spotted a 70–80% dropoff between signup and setup moments in a specific product’s activation journey. Configuration was one of the pages between these two moments, and because the configuration was complex, we assumed people simply weren’t configuring due to the complexity. But we actually found out that the majority of the drop off occurred before users even made it to the configuration page, so configuration wasn’t the problem at all. Analyzing these friction points in Analytics allows us to build enhanced user flows that improve UX and lead to an increase in activation. We now know exactly where to focus our energy.

In another example, we saw in Amplitude that the current onboarding experience of a specific Jira app wasn’t ideal, so we worked on optimizing it. These changes included adding the app to Jira’s top navigation menu and updating the app’s Getting Started page to include a CTA. We hypothesized that creating the page would increase the number of people getting to the signup moment from the very top of the funnel. The end result was that we increased users getting to the signup moment—one of the most crucial parts of the activation journey—by 117%.

By operationalizing our approach to activation and evangelizing Amplitude across the entire Appfire organization, we’ve moved the needle on activation for the top 38 apps in our portfolio. Our small but mighty growth team has established a common portfolio-wide activation methodology, defined activation journeys for those 38 apps, collected baselines for those activation journeys via Amplitude, and run activation experiments across 20+ apps.

Experiment data for these projects is still rolling in, but our early results already show a 10–14% increase in post-experiment product activation metrics. Except for some qualitative experimentation cycles, we’re using Amplitude to identify gaps in the users’ activation journeys and measure the impact of the improvements we make.

Connecting activation with conversion

The holy grail of activation is being able to correlate activation with conversion. The relationship might seem intuitive, but intuition isn’t enough. Our ultimate goal was to drive new revenue for the company. To ensure that we were doing so, we had to prove that there is a relationship between activation and paid conversions in our apps. As a result, we used Amplitude to conduct an in-depth statistical analysis, using data from 10,000 customer accounts across a half dozen of our highest-volume apps. Our findings showed that activation and paid conversion are indeed closely related—we found that a 10% improvement in activation leads to a 2.5–3% improvement in the paid conversion rate, and that customers who successfully activate within the first 30 days are three times more likely to convert to a paid license.

Perhaps more importantly, we also wanted to correlate activation with retention. We’ve used Amplitude to show how vital activation is with 3–6-month retention, especially with paying customers.

These findings on activation’s impact on conversion and retention validated our program, helped us estimate our activation program’s revenue contributions, and gave us the evidence we needed to get buy-in from leadership to further expand our program in 2024.

Our goal is to be a best-in-class growth team. To do that, we need to use best-in-class software. We strive to partner with industry leaders because that’s who we strive to be in our own work. This initiative truly was a team effort and no one person on our team could have gotten to where we are today alone. We consistently push each other, and our success is a culmination of all our hard work. I’m excited to see where we’re heading in the future.