Case study

Teatime & Avo

Teatime Games is reinventing social games for the next generation of mobile players. With a focus on iOS and Android, the team is developing a live platform technology that supports a new type of highly personal, face-to-face gaming experiences, where players can see the reactions of the people they are playing with.

The company was founded two years ago by team members from Plain Vanilla Games, creator of the popular live social media trivia game, QuizUp. Teatime Co-Founder and CTO, Jóhann Thorvaldur Bergthorsson, oversees the engineering teams and builds the shared technology that is used in all of their games.

Avo is enabling Jóhann’s team to make better product decisions and generate value by fostering conversations around data and events, removing the friction of implementing analytics, and helping his team make fewer coding errors so that data is accurate and immediate.

The decision to buy instead of build

The Teatime founders knew they needed a tool to easily plan and track analytics seamlessly across their products, and that could fit within their development process. “Previously, we had rudimentary analytics all over the place, no overview, and no one with direct ownership over our data,” Jóhann said. To be successful, the team needed to make decisions based on how people reacted to their products and the features they were building. They didn’t have the capacity to hire a data scientist initially.

The decision to buy instead of build was driven by three primary factors. The first was focus. “We deeply prefer not to build tools that are not directly related to the core problems that we’re solving,” said Jóhann. “We have learned from experience that doing so slows us down as a company.”

“Avo lowers the cost of adding analytics, and makes the implementation process frictionless.”

Jóhann Þorvaldur Bergþórsson
Teatime Co-Founder and CTO

The third factor was Avo’s agility and its ability to support Teatime’s tech stack. The team uses a matrix of programming languages and data analytics platforms. Avo is used to generate ReasonML code for React Native and C# for the Unity engine that the games are written in. “It has been really nice not to have written all of that boilerplate code by hand,” said Jóhann.

Enabling a data-driven culture

Avo has helped Teatime foster a data-driven culture without a lot of specialization. As the company grows, the team can easily train new team members to use Avo and get excited about using analytics generally.

Product managers use Avo to define and implement product metrics that are tied to their overall business objectives. They can confirm early on whether they are focusing on the right thing. “Sometimes, a gut feeling or excitement drives us in one direction,” said Jóhann. “By talking about the metrics and outcomes when we are planning a feature, it forces us to think about the data that we need to actually measure those outcomes.”

Using Avo, the team can easily create events, collect data, build out dashboards based on defined workflows, and iterate. Currently, the product teams are using Avo to track all primary KPIs, including onboarding funnels, retention metrics, and feature-by-feature metrics.

“With Avo, we could be a small, non-specialized team and still have sophisticated data workflows.”

Jóhann Þorvaldur Bergþórsson
Teatime Co-Founder and CTO

Teatime’s developers can implement and update events and verify that they are working with fewer errors. “Because Avo is so low friction, a developer can define an event and add it into the app without needing to talk to a product person,” said Jóhann. “Previously, it was something that was perceived as very boring, or a hassle.”

Avo has helped the team eliminate certain types of bugs altogether. “We no longer have issues with making a typo when implementing our analytics,” Jóhann said. In addition to not having to write boilerplate code, Avo has eliminated the need to write tests along with the code the team generates for tracking.

With a data scientist now on board, the team can use Avo to further visualize, build, and refine workflows and dashboards, and gain real-time feedback regarding user behavior and product success.

A single source of truth for analytics

Avo is helping Teatime to standardize analytics across their products. The product team can define a tracking event once and then send it from different sources. “If you have multiple games or products that don’t share code but would share some analytics schema, you could leverage Avo to share events between those sources and generate the analytics code in two different codebases,” said Jóhann.

Maintaining a single source of truth to cover product analytics helps reduce the risk of lost or delayed data that can prevent timely decision making. “When you’re a startup, the risks and costs of errors can be high,” Jóhann explained. “You need to know the right direction to go in, and you need to know rather quickly. With Avo, we can get the clean data immediately.”



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Key takeaways

  • Teatime opted to buy Avo instead of build to remain focused and cost-efficient.
  • Avo works seamlessly with Teatime’s programming languages and data analytics platforms, including ReasonML for React Native and C# for Unity.
  • Avo lowers the cost of adding analytics, and makes the implementation process frictionless
  • Avo enabled Teatime to build a data-driven culture from the start.