How Personalization Helped G-Loot Improve its Player Experience
Using Amplitude, the esports platform created a better onboarding experience
the number of its daily active payers
Founded in 2015, G-Loot launched with the goal of adding an extra layer of excitement to competitive gaming by offering players innovative competitions and the ability to grow a lifelong player identity.
The idea took off with players and publishers, and as the company grew it turned to Amplitude to ensure it was spending its own cash wisely, investing in new products and features that would pay the best returns. Today, G-Loot uses Amplitude for a rapidly expanding list of functions.
The mom test
Amplitude stood out from its competitors for its ease of integration with Segment, which G-Loot had been using to shape its marketing strategy, said Jamie Dunbar Smyth, Chief Growth Officer at G-Loot. Plus, Amplitude impressed Jamie and his colleagues with its accessibility.
That was a must-have for G-Loot, which wanted any employee at the company to be able to conduct their own data analysis, an approach it believed would help prevent overburdening data teams and boost efficiency.
“We wanted a tool that is so easy and user friendly that I could give it to my mom and with some basic training she would be able to use it,” Jamie said.
Now more than half of the company uses Amplitude to do everything from mine insights into user behavior to catch issues before they become full-blown problems.
“I am often aware of things before they get out of control, which means I’m able to very quickly slack message our VP of product or our VP of tech and immediately flag the problem and let them know Amplitude has noticed an anomaly,” Jamie said.
The power of personalization
But perhaps the most important role Amplitude plays today, Jamie said, is in G-Loot’s segmentation and experimentation efforts. Amplitude has been particularly effective in that area because of the depth of data Amplitude leverages–including the core data that correlates to revenue, he noted.
“We were already using Amplitude to analyze our data so it was a seamless transition between analysis and experimentation,” Jamie said. “It has certainly made things easier and more efficient for our teams.”
For example, G-Loot made an important discovery about its onboarding approach—an opportunity it took advantage of with remarkable speed using Amplitude Experiment. “Looking at the data, we realized that we were providing the same experience to everyone—from novices to skilled players. In other words, the challenges were too difficult for new players,” Jamie said.
In response, G-Loot used Amplitude Experiment’s segmentation tools to roll out player challenges tailored to win rates and game-round outcomes. “We initially planned to get the segmentation done in three months, but it took less than one month. We were able to complete the project quickly and immediately see business metrics improve,” Jamie said.
Indeed, those changes have already yielded a major payoff, doubling the number of its daily active payers.
Experiments With Real-World Ramifications
Amplitude also allowed G-Loot to quickly explore and monitor in real-time the impact of a multitude of changes to its ad-driven landing pages, from design to value proposition. The experiments analyzed through Amplitude helped the company home in on modifications, made through Optimizely, and boost paid conversions from three to 35 percent.
Looking ahead, Jamie said G-Loot plans to use Amplitude Experiment to drive further improvements to its various landing pages as well as in tests of new features. The company even has a dedicated project manager to oversee the experiments it’s planning to roll out across a broad range of teams.
With Amplitude, you can cut and splice the data in so many different ways,” he said. “We’re really just getting started.