On Device Research: Smarter Operations using AI
On Device Research: Smarter Operations using AI
Machine learning has huge potential in making day-to-day business more intelligent. This case highlights how incorporating models in the everyday workflow for On Device Research can improve security and enhance user experience
Background
On Device Research, ODR is a kickass UK-based tech company that has a world-class platform that allows users to complete online surveys in the exchange for a monetary reward. ODR, and businesses alike, can attract fraudulent users trying to cheat the system for their own gains. It’s essential to protect the business from such users, while at the same time not punishing good users. Furthermore, it’s crucial to have a good user experience, so that the platform can attract and keep new customers, as well as suppliers of surveys.
Solution
We trained, in close collaboration with the talented team at ODR, multiple models per market to streamline ODR’s business operations. Classifiers were trained to predict the likelihood of a survey being finished with bad intent – one using features describing the user, context, and survey. A ranking system was developed to sort the surveys available to a user based on relevance. Finally, model results were aggregated across many tasks and used for user segmentation to enable the personalization of application logic based on segments.
Tools/Tech
Feature engineering was done in relational databases. Gradient boosting models were trained using Dask to handle the large dataset size and the trained models were deployed in AWS using various managed services. Training and validation pipelines were developed in Python with DVC.
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Research surveys delivered
Since their inception, On Device Research has delivered over 35 million surveys worldwide.
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Countries
On Devices Research reach has gone global, conducting studies across the Middle East, Africa, and Asia.
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Survey completes for training
We trained the recommender system on 3.2 million completed surveys.
Smarter Operations with AI: Detecting Fraud and Boosting User Engagement
AI and machine learning models can be a valuable tool for many businesses. This blog posts highlights a few examples of how machine learning models can be used to protect, increase value and gain insights in your business.
In 2022, we built ML fraud detection models and recommendation systems for the UK-based company On Device Research to complement their platform, Curious Cat, which allows users to find and take surveys.
