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 SQL’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 API’s.
Finally, Eric’s team can push out the discounted sales promotions that are refreshed every day to the customers by leveraging Big SQL’s capability to call applications developed by users.

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