Case Study: INDIEZ


INDIEZ is a mobile game production and publishing company based in Vietnam. Currently, INDIEZ is running seven games covering different genres, including casual, hyper casual, puzzle, and action. With games such as Monsters & Puzzle: God Battle, Pet Connect: Tile Puzzle Match, Car Parking: Traffic Jam 3D, and Crazy Driver 3D: Car Traffic, the company now has over 17 million downloads.

The Challenge

For the continuous success of its games, INDIEZ needed to get a deeper understanding of each touchpoint of the user journey and measure campaign performance. The team at INDIEZ recognized the value of raw data early on, as it is extremely useful for analyzing advertising channels and testing campaigns. It also gave them the flexibility to measure metrics according to their needs. However, analyzing raw data required personnel skilled in data queries and processing. Plus, it took time to map vast data and sync information across multiple sources.

While testing new user sources from different partners, INDIEZ also encountered fraudulent traffic. They needed a tool to determine legitimate from illegitimate traffic sources to minimize the negative impact on their media budget and total revenue, and to prevent fraudulent traffic going forward.

The Solution

With the help of Adjust Datascape, INDIEZ was able to maximize its use of raw data, discover the unique value of different channels, and pull more accurate insights from A/B tests. Adjust’s raw data allowed the INDIEZ team to compare the performance of campaigns, creatives, and ad networks at country levels.

Lan Nguyen


Additionally, Datascape provided INDIEZ with a complete overview of critical KPIs and time-saving reporting. Having all of the data from networks and campaigns in one place made it easier for the INDIEZ team to gain meaningful insights, helping them to make faster and more strategic decisions in real-time.

Lily Truong

Sales Manager, Adjust Vietnam

The metrics the team at INDIEZ utilizes to evaluate performance vary depending on the campaign optimization goal and how the machine learning of that particular ad network works. That’s why they measure some metrics differently from the existing formulas in Adjust’s system. However, with the introduction of the ‘custom metric’ feature to Adjust Automate, INDIEZ could conveniently tailor formulas to calculate metrics suited to their needs.

INDIEZ also utilized Adjust’s Fraud Prevention Suite to stop its marketing budget from being spent on traffic that leads to a dead end. The INDIEZ team filtered out bad traffic sources, helping them determine partners that empower their success. The Fraud Prevention Suite helped INDIEZ identify that more than 50% of a particular partner’s traffic was from unidentified sources and had invalid signature SDKs.

The Results

Adjust raw data gave INDIEZ a granular and detailed overview of campaign and marketing channel performance. This helped them quickly review return on ad spend (ROAS) and allocate budget to channels bringing in users with a high lifetime value (LTV). Raw data also allowed them to combine data from many sources and create their own metrics.

With the help of Adjust, INDIEZ was able to:
  • Increase return on ad append (ROAS) in the US by 50%
  • Increase installs of their top game, Car Parking 3D, by 20%
  • Increase ad spend for Car Parking 3D by 40% while achieving their targeted ROAS.

Learn how INDIEZ has been successful with Adjust raw data in this blog: “Leveraging raw data to skyrocket your app’s success