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Awem Games exceeds ROAS target by 76% on the Chartboost platform

January 19 · xierdang · 3 Min read
Awem Games is a casual game developer of match-3 puzzle titles like Cradle of Empires, a hit with over 17 million downloads. Its users are mostly female and over 35 years old. Awem Games was founded in 2002 in Mogilev, Belarus, and today has more than 160 employees. Challenges Unlike some competitors’ match-3 games, Awem’s...
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Awem Games is a casual game developer of match-3 puzzle titles like Cradle of Empires, a hit with over 17 million downloads. Its users are mostly female and over 35 years old. Awem Games was founded in 2002 in Mogilev, Belarus, and today has more than 160 employees.

Challenges

Unlike some competitors’ match-3 games, Awem’s titles don’t have a linear story. Users can choose what level to beat and they make purchases not very early in the game. For players, that’s a fantastic game design choice but for Awem, it means a slower conversion of players to paying users and a lower conversion rate compared to the market at large. With these factors in mind, Awem needed control over its cost per install (CPI), a predictable return on its investment (ROI), and stable traffic volumes.

Solution

To drive more installs and payers for Cradle of Empires, the Awem UA team started with setting up an advertising campaign using Chartboost’s Flexbid tool. Flexbid allowed Awem to optimize buying on a more granular level by setting more competitive bids on publisher apps that convert the most users. Simultaneously, they decreased their CPI on less performing publishers to sustain install volume but for a lower price. They were well pleased with the performance but desired more scale and automation.Working closely with the Chartboost team, Awem was later up-and-running with programmatic advertising campaigns on the Chartboost DSP. The team set up campaigns for Cradle of Empires in key markets, tier 1 countries, and Japan, in which Awem provided localized creatives for the campaigns to perform its best on the Chartboost DSP. Awem’s focus was on creative conversions, and return on ad spend (ROAS), measured by a D7 ROI.

Access to user data from Awem allowed Chartboost DSP’s machine learning (ML) algorithms to run more precisely and efficiently quickly. The ML algorithms understood the core audience of the title and targeted high-value users that were most likely to engage and convert to payers while keeping a high IPM and stable CPIs.

Chartboost account manager’s responsiveness and openness in explaining the work of the algorithms, the continuous improvement of the platform, and technical support all impressed us.”

– Aleksey Golovachev, Marketing Team Lead

Results

Awem results

The Chartboost DSP has performed well above Awem’s D7 ROAS goals. On Amazon, Awem achieved a 76 percent increase above its goal in the third quarter of 2020. Followed by iOS with a 46 percent increase over its goal. Google Play was launched last with a higher D7 ROAS target than the other platforms and has yet to scale, but is already showing promising results by reaching 3 percent above the target. This reveals one of the strengths of programmatic advertising: over time, the machine learning model gathers more data and automatically improves its own performance.

Running programmatic advertising campaigns with Chartboost has provided access to unique inventory and great payers rate. The results have exceeded our expectations.”

– Aleksey Golovachev, Marketing Team Lead

Download case study

Awem Case Study