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Case Studies


Case Studies



"The choice to use DeviceAtlas was down to the accuracy of reporting and improvements to what we had."

Dennis Lapets, Engineering Manager at Adjust


Requests per second


Traffic cross-checked by DeviceAtlas



Headquarters:Berlin, Germany
Industry:Marketing and Advertising
Specialties:Mobile marketing performance tracking, mobile app attribution, business intelligence


Adjust is a mobile attribution and analytics company that provides software for clients (app developers) to better understand user engagement and activity within their apps. Clients can also uncover which marketing channels are impacting user acquisition or user re-engagement, etc.

Using Adjust’s platform, app marketers can understand where their users are coming from and which are their highest performing channels. This enables user segmentation real-time of behavioral patterns. The result is more fully optimized mobile campaigns.

We spoke with Dennis Lapets, Engineering Manager, and Katharine Kuhl, Director of Backend Engineering to understand more about how they have integrated DeviceAtlas into their technology stack and how they utilize it.

The Challenge

Having a reliable method of device detection is a business-critical asset for any company in the analytics space. With the ever-increasing variety of web-enabled devices in use today, it’s not easy to accurately detect which device is making a request for an ad or app in an efficient way. Accurate data on all devices customers are using across networks and online properties is a vital part of campaign targeting and analytics.

Before implementing DeviceAtlas, Adjust was using an internal regex solution based on a pattern matching approach on the device user agent strings returned by browsers. The main challenge with this approach was around labor resources and data accuracy. Using a regex solution can be very labor intensive so Adjust needed a device detection solution that would not impact its core engineering activities.

Also, while Adjust’s solution did work well in terms of performance, there were some inaccuracies. For example, the distinction between Android tablets and smartphones wasn't always correct. Such a differentiation is significant for Adjust, particularly as device breakdown is included in the customer dashboard. The company needed a premium device detection solution that was not only capable of conducting millions of detections per second to meet the required demand, but also to provide an up-to-date, accurate device database.


After evaluating several solutions on the market, Adjust chose DeviceAtlas’s locally deployed solution on the basis of its robust, high-performance APIs which can be deployed in demanding environments, and its market leading accuracy. DeviceAtlas was easily integrated into Adjust’s technology stack which helped it continue hosting data on its own servers. Adjust never stores information with cloud services which helps to eliminate any risk for their own customers around device information being exposed.

DeviceAtlas enables Adjust to provide clients with a deeper understanding of app users using granular device data to segment and analyze behavior in real time. For example, app marketers can see which types of devices are the best performing in terms of user acquisition, campaign attribution and revenue tracking. Over 90% of Adjust’s traffic is cross-checked by DeviceAtlas. It also utilizes DeviceAtlas's bot identification capability to filter out crawlers, spiders, etc. so they do not account for clicks or impressions. This ensures that Adjust's clients do not encounter issues of invalid traffic.

Using DeviceAtlas’s real-time API also enabled Adjust to map user agents more effectively when compared with the regex solution, and the company immediately saw an improvement over its in-house approach. "There was definitely an increase in accuracy, especially between tablets and smartphones", says Engineering Manager Dennis Lapets. "The choice to use DeviceAtlas was down to the accuracy of reporting and improvements to what we had. It's hard to estimate just how much time it has saved for developers over the years because we don't have to maintain these parsers anymore."

"For us it's about being able to focus our resources on what we do, which is understanding mobile attribution and analytics. It's fantastically helpful to be able to outsource device detection and it's greater business efficiency for us." Katharine Kuhl, Director of Backend Engineering.