RPGMatch Machine Learning 

rpgmatch-header

20,000+

data points analyzed

10M

user target

<3

months to build
BUSINESS PROBLEM

Playing TTRPG goes beyond just playing time and games. There are play styles, safety tools, and play environments. Complicating things further, many games last more than one session and can span months or years. To solve this, RPGMatch built a questionnaire with over XX questions. As players answered the questions and engineers looked at the data, It became clear that there were too many data points to program an algorithm that is accurate and robust. 

RPGMatch realized they needed a better technical solution for matching players on their social network.

rpg-match-1-1
TECHNOLOGY SOLUTION

RPGMatch approached Metal Toad with the need to use their user data and match users together into potential groups for playing TTRPGs with.

Metal Toad set up a webhook for API Gateway, to get new surveys as they were filled out. The data was processed and stored in Dynamodb, where it could easily be analyzed and Metal Toad data scientists could decide what features were needed. 

Once the preliminary data review was done. Metal Toad used SageMaker to try different machine learning algorithms. After several tries, Principal Component Analysis provided the best matches with the current data. 

With the matching algorithm ready to go. Metal Toad integrated it into the data pipeline to make the whole process seamless. 

IMPACT

With a complete data pipeline with integrated ML, users can now be matched in seconds. Using ML instead of traditional programming has meant that RPGMatch has gotten matches quicker and they are already looking at how to improve matches by iterating on their questionnaire.

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