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Cowboy Escape is a casual endless runner. The purpose of this project was to gain a better understanding on the design and implementation behind casual games, as well as practice data driven design techniques as part of a University module.
This prompted a very basic game design which would evolve over time.
The games premise revolved around a western cowboy setting. Player aim is to navigate across 3 tracks, dodging randomly spawned obstacles with an ever increasing running speed.
In order obtain worth while quantitative data to inform my iterative design, a series of game hooks were identified along side a speculative diagnosis which aimed to anticipate potential problems.
With all the required tools in place, I created a general testing plan prior to any playtest sessions. The test plan was filled out subsequently to each session and pointed out the enquiry led by any changes.
The test plan can be found here: Link
In order to collect data, I researched different possible methods. While the most straightforward way would have been to utilise the built in system of Unity Analytics, I wanted to delve a bit further into learning new custom systems.
Therefore, a proprietary script was created which collected the assigned KPI's and exported them in a sorted CSV. To further automate the process, I created a piggyback script that sends the files to an allocated e-mail address. While not the most elegant, I was able to centralise all my data and access it at any time.
With qualitative data in the form of questionnaires completed by testers after each test session, mixed with automatically collected quantitative data - I was able to bring them together into a centralised dashboard on google sheets which would be used to visualise and analyse my findings.
Based on these findings, I would perform certain changes to each test version of the game, collect data and compare the results to one another in order to observe the impact that those changes had. The process would be then repeated several times.
The final data report can be found here: Link
Key Takeaways
Understanding of data driven design techniques, along with methods on how data can be collected, centralised and analysed.
Rapid prototyping, with data driven design changes.
Better understanding of casual and hypercasual games aswell as their respective markets.
Gained a better understanding on how to balance certain mechanics as well as implement them effectively. One of these being consistent random generation of a track.
Thanks for reading!
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