In this video, we will demo that how the marketing team at a Sports Equipment Store operationalizes a Spark ML model that can predict customer’s product preference based on customer’s profile.
Lets meet Eric, who works for Outdoor Equipment Inc., an sporting goods retailer. Eric works as a Marketing Analyst for this organization.
Based on competitive analysis, market trends and customer behaviors, Eric’s team has concluded that a prospective customer may convert into a paying customer if they are provided with proper incentive to shop. This key finding motivated Eric to come up with a sales campaign to send out product promotions to targeted users based on their interest in products.
He has put together a plan to run a sales campaign for 3 months with a variety of products that are available in the store.
Eric’s team can leverage IBM Big SQLâ€™s federation capabilities to connect and query data that is stored in separate data sources in a secured way.
With IBM Big SQL and Spark integration, Eric’s team can operationalize spark ML models without knowing the details of how Spark works or its APIâ€™s.
Finally, Eric’s team can push out the discounted sales promotions that are refreshed every day to the customers by leveraging Big SQLâ€™s capability to call applications developed by users.