How Starbucks is using Neural Networks!?

Yes, you read it right! Coffee king Starbucks is also using a neural network and AI approach for its marketing, rewards, store location, menu updates, etc.

So, let’s see how Starbucks is using the power of Neural Networks.

With 90 million transactions a week in 25,000 stores worldwide the coffee giant is in many ways on the cutting edge of using big data and artificial intelligence to help direct marketing, sales, and business decisions.

Rewards and mobile App:

When Starbucks launched its rewards program and mobile app, they had a drastic increase in the data they collect and could be used to get to know their customers and extract info about purchasing habits. The mobile app has more than 17 million and the reward program has 13 million active users. These users alone create an overwhelming amount of data about what, where, and when they buy coffee and complementary products that can be overlaid on other data including weather, holidays, and special promotions. So, they might use the recommendation system behind the scene. There are many recommendations engines for this.

Marketing:

The same intel that helps Starbucks suggest new products to try also helps the company send personalized offers and discounts that go far beyond a special birthday discount. Additionally, a customized email goes out to any customer who hasn’t visited a Starbucks recently with enticing offers built from that individual’s purchase history to re-engage them. As mentioned above the emails are also sent on the basis of the recommendation engineers working purely on NN.

Determining new store location:

It’s common knowledge that the right location is essential to succeed in retail. The Starbucks market planning team doesn’t rely on their gut feelings to determine where stores should be located but taps into the power of data intelligence through Atlas, a mapping and business intelligence tool developed by Esri. This tool evaluates massive amounts of data, such as proximity to other Starbucks locations, demographics, traffic patterns, and more, before recommending a new store location. This system even predicts impact to other Starbucks locations in the area if a new store were to open. Even though it feels like there’s a Starbucks on every corner (and some so close to each other you might imagine that they would cannibalize sales from one another) rest assured the data told them to build it.

Menu updates:

Some Starbucks locations serve alcohol, but the company decided which ones would offer “Starbucks Evenings” based on areas the data was signaling would have the highest alcohol consumption to support the success of the menu update. Data also drives special limited-offering menu items based on what’s happening at the time. In one example, when Memphis, Tennessee was enduring a heatwave, Starbucks launched a local Frappucino promotion to entice people to beat the heat! And, although there are 87,000 drink combinations available at Starbucks they continue to monitor what drinks sell the best to continue to make menu modifications.

References: https://www.forbes.com/sites/bernardmarr/2018/05/28/starbucks-using-big-data-analytics-and-artificial-intelligence-to-boost-performance/?sh=6bc8aa0765cd

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C|EH | Cybersecurity researcher | MLOps | Hybrid Multi Cloud | Devops assembly line | Openshift | AWS EKS | Docker