"How Alooma gave PlayDots the power to spot trends and conduct usage experiments in real time"
Tony He, Data Scientist

Industry: GamingLocation: New York City, New YorkWebsite: weplaydots.com

Dots builds games for iPhone, iPad and Android devices. The studio’s most popular games, Dots and Two Dots, have a combined 75 million downloads.

The Need

Dots data scientist Tony He had been tasked with implementing the data analytics needed to gain business-critical insights, such as why customers quit playing after only three levels and how to get millions of players still on the free tier to pay for at least one game add-on.

The existing system, a targeting and marketing automation application, was inflexible and offered no ability to dive deeply into the available datasets. So Tony set out to find a tool that he, as a “one-man data science department”, could use to deliver real value to the business.

After being disappointed by his initial search for a solution, a colleague suggested that Tony look at Alooma.

Why Alooma?

“I immediately recognized the power and potential of Alooma,” Tony recalls. But there was something else Tony noticed: Alooma makes all of that power easy to use. “I have colleagues who end up spending all of their time maintaining a custom data pipeline, and I believed I’d be able to avoid that trap with Alooma.”

After becoming more familiar with the full breadth of Alooma’s capabilities, Tony found even more to like. “Other solutions tend to be ‘black boxes,’ but Alooma gives me full visibility into and complete control over my data.” The control derives from the versatility afforded by the Python-based Code Engine used to tune scripts to accommodate different and changing needs. “The Code Engine is actually quite elegant in the way it makes scripts easy to test and tune to deliver the desired results with high ETL performance,” Tony adds.

The Results

Tony was able to get the Alooma data pipeline fully up and running far sooner than he had anticipated, and is now getting both the descriptive and the predictive analytics he wants. The descriptive insight consists of statistical analyses about use and retention. “To do that I had to create a hash to convert user IDs into a separate value to track usage and performance while protecting user privacy, and Alooma made that easy to do,” Tony explains. The predictive analytics enable Tony to spot trends and conduct experiments on usage.

Tony had expected he might need to hire someone full-time just to maintain the data pipeline. But Alooma has made that so simple, he is now convinced he can handle everything by himself with complete confidence in the integrity of his data: “Like all data scientists, I’ve had real problems getting data loaded completely and accurately. But Alooma’s Restream Queue is such a cool feature that I no longer need to worry at all about any data loss or corruption.” Tony is also now certain that Alooma offers both the versatility and scalability Dots needs to accommodate additional applications, and is already pursuing ways that he — and he alone — will be able to take full advantage of its potential.

GoFundMe Alooma for ETL
Invoice2go Alooma for ETL
PlayDots Alooma for ETL
Quid Alooma for ETL
More coming soon