Improving resource allocation in User Acquisition at Angry Kraken

Improving resource allocation in User Acquisition at Angry Kraken

The Angry Kraken S.L. is a dynamic company specializing in the development of relaxing and logical mobile games. Since its founding in 2014, it has gained a strong foothold in the casual gaming market, providing intuitive and accessible games such as Sudoku, Four in a Row and Guess the Word. These games are monetized 90% by advertising. The team ranges from a dozen to 30 people, and the company's annual marketing budget in 2024 is up to $160,000.

The Angry Kraken mobile game studio specializing in casual logic games and User Acquisition optimization

Project objective:

The objective of the project was to create a unified User Acquisition reporting environment that would provide a clear and reliable view of marketing performance across all channels and games.

The lack of integrated UA data limited the team’s ability to evaluate campaign effectiveness, optimize budgets, and make timely data driven decisions. By consolidating attribution, cost, and monetization data into a single analytical framework, the project aimed to enable faster optimization of marketing spend and improve overall UA efficiency.

Scope of work

  1. Data Analysis and Preparation
    At the initial stage, we supported the Angry Kraken team in configuring the export of raw data from Firebase and Adjust, as well as integrating data from the Applovin Max mediation platform. This enabled us to provide accurate and consistent data sources for revenue and user attribution.
  2. Development of Comprehensive BI Reporting
    We developed User Acquisition reports that allow for ongoing analysis of marketing campaign effectiveness, monitoring of user acquisition costs (CPI), and evaluation of player retention. Additionally, we prepared product reports (app development report) analyzing key KPIs, enabling comparisons between new app versions, tracking game economy, and monitoring player behavior across different segments.
  3. Predictive Models and Report Integration
    In response to the need for faster decision-making, we implemented predictive pipelines that feed BI reports with forecasted cohort LTV values and ROAS indicators. This has enabled dynamic adjustment of marketing campaigns and advertising budgets.
  4. Implementation of a ROAS Calculator
    We created a tool for real-time evaluation of marketing campaign profitability by integrating actual campaign data (CPI, target ROAS, predictive LTV) with Google Ads targets. The ROAS calculator allows for automated budget decision-making, optimizing fund allocation.
  5. Ongoing Support and Optimization
    Following the implementation of reporting and predictive systems, we provide ad hoc support for the Angry Kraken team in maintaining reports and addressing ongoing analytical needs.
User Acquisition data analysis and player behavior insights based on BI reporting and predictive analytics

Results

Key results:

  • Reports consolidate data from multiple sources (Firebase, Adjust, Applovin Max, Google Ads), enabling a complete analysis of marketing costs, monetization KPIs, and MMP attribution.
  • Elimination of manual tasks such as exporting CSV data and merging it in Excel – reporting processes are now automated.
  • Reliable revenue data through integration with Applovin Max and a mechanism for filling in data gaps.
  • The ability to continuously optimize marketing campaigns and budgets using the ROAS calculator and predictive LTV models.
  • Faster marketing decision-making – reducing the risk of wasting budgets on unprofitable campaigns.

Business value:

  • Precise allocation of advertising budgets across games, channels, campaigns, and countries.
  • Enables dynamic responses to market changes, such as shifts in ad rates or competitor actions.
  • Ability to assess the financial potential of new games and identify winners and underperformers in UA campaigns.
  • Greater control over campaign profitability through access to predictive ROAS metrics over different time horizons (e.g. 510 days).

Client feedback

Carlos Felipe

Thanks to our collaboration with Alterdata, we gained full insight into the performance of our User Acquisition campaigns. BI reports and predictive models allow us to make fast, data-driven decisions, directly contributing to better budget allocation and increased profitability. We appreciate the team’s flexible approach and the speed of implementation, which exceeded our expectations. It's a completely different level of working with data than what we were used to

Thanks to our collaboration with Alterdata, we gained full insight into the performance of our User Acquisition campaigns.

Carlos Felipe
Carlos Felipe,

CEO, The Angry Kraken S.L.

Summary

The project delivered for The Angry Kraken S.L. demonstrates how effectively implemented analytical and predictive solutions can support User Acquisition teams in the dynamic mobile gaming industry. By integrating multiple data sources, automating reporting processes, and incorporating predictive insights, the company gained tools for efficient budget management and marketing optimization.

If your company develops mobile games or applications and needs a comprehensive data analytics approach, get in touch with us – we’ll implement solutions that help you make better decisions and increase your ROI.

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