Big Data Comes to Retail Via SwiftIQ Daypart API

Following its groundbreaking APIs for predictive and Big Data analytics, SwiftIQ has released the Daypart API.

Retail is fundamentally shifting as APIs enable the industry to redesign the shopping experience by drawing in cloud, mobile, big data, and new tech like wearables and Internet of Things sensors.

The SwiftIQ Daypart API allows large-volume retailers to analyze sales volumes for any given hour of the week, filtered by product, brand, location or individual store. Heat maps are also able to be generated to visualize (using D3 widgets) key shopping times for specific products.

Chicago-based startup SwiftIQ started life as a predictive analytics company but this year has found itself consistently focused on the packaged goods and supermarket retail industry.

This is in part due to the uptake of its previous API product. At the start of the year, it launched a Frequent Pattern Mining API. That API allowed supermarkets to analyze each basket purchase made at the checkout counter and identify products that aligned best; for example, data from the API quickly uncovered one brand of light beer that was bought with healthy purchases like yogurt and bananas, while another brand more often went with frozen pizzas.

The Frequent Pattern Mining API showed SwiftIQ that its expertise in building API infrastructure to manage data related to billions of records was ideal to support the supermarket industry. According to CEO and founder Jason Lobel, this has led to the creation of the Daypart API, which “will be a critical element serving as the intelligent data layer that powers content recommendations for interactive shopper experiences. Retailers and marketers can leverage the API to activate content and targeted promotions delivered via mobile beacons, programmatic ads, interactive displays, and other media.”

Use Cases

SwiftIQ has identified several use cases, including digital signage, inventory management, streaming better personalized/contextual content via beacons and use of electronic shelf labels.

Other possibilities include:

Reducing food waste: APIs are beginning to be used in a range of global initiatives aimed at better preventing the significant food waste that occurs as food passes its expiration date and is thrown out. FoodLoop in Germany, for example, uses the FIWARE API platform to provide shopper discounts on food that is nearing its expiration date, but that can still be a cumbersome, Resource-intensive workflow (for example, stickers need to be manually added to products that are nearing their expiry dates). Using the SwiftIQ Daypart API in conjunction with new technologies like beacons or even digital pricing shelf labels could dynamically reduce the prices of foods that near their expiration dates, thus guiding shopper behavior to more sustainable shopping practices. Items could even be co-located to help shoppers plan whole meals.

Bringing big data insights to any retailer: In their book Big Data, authors Viktor Mayer-Schönberger and Kenneth Cukier mention how Wal-Mart used big data analytics to discover that when a hurricane warning is given, people rush to the store to buy Strawberry Pop-Tarts! With the Daypart API, that sort of insight becomes available to a whole range of supermarket suppliers, not just those with the analytics resources of Wal-Mart.

Redesigning store displays based on time: A report into APIs by Fabernovel last year showed how 7-Eleven stores are able to analyze their sales data to manage in-store displays at three crucial sales times: before work, after school and after work. By rearranging store displays, the chain helps shoppers more easily find the sorts of items they are buying (conveniently) from 7-Eleven while also cross-promoting items for their particular demographic.

Rostering staff times and managing supply chains: The potential of a data analytics API like the Daypart API is that over time, the data will help supermarkets better roster staff times and can even optimize the distribution and logistics supply chains into their stores while reducing warehousing and stock needs and avoiding over and under stock risks.

In all, the Daypart API could play a part in creating greater efficiencies and more sustainable supermarket industry practices. With IoT and big data, APIs are increasingly bridging the gap between insights gathered online and in the physical world. Watching how SwiftIQ is enabling these technologies is useful for businesses in any industry to get a better look at what is over the horizon.

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