Our client, a media house, had a team of data scientists but they did not have the requisite skill sets to deliver value while developing a personalized recommender system.
As the first step of our process, we did an assessment of the current state of their resources to determine what kind of mentoring they require.
We developed a roadmap for the skilling requirements for their resources. We provided hands-on mentoring to the team to develop the recommender system using multiple base recommender models and then combined them to build a hybrid model. We helped them to develop a strategy for the recommendation system to transition from being a un-personalized recommender to one that automatically increases personalize the content delivered to an individual as the signals of the interest of the individual starts increasing.
We mentored the team on the deployment skills needed for the recommender. And also suggested them (the client) on new hirings.
At the end of a 6 month period, not only did the client had a more robust team but also, a new recommendation engine was created that could offer more personalized recommendations to the consumers.