It’s pretty well established that AI is the future of computing (well, at least the future of a great deal of computing thought, focus and emphasis). If it lives up to the hype, it will most certainly change the face of human history. Whether it’s a force for good, built and deployed ethically, etc. all remains to be seen; this has been one of the problems preventing many everyday consumers from bridging the intellectual gap between the promise of AI and the reality of it — how is it actually impacting their lives? That can be hard to answer in a lot of use cases because so much of the advancements we’re chasing in AI are years away from fruition. But, some companies — like Starbucks — have actually built AI best practices into their businesses today and show a way forward for intelligent apps, the next generation of mobile development.
Starbucks was one of the first major consumer brands to weaponize mobile in its favor. Starbucks’ rewards app was simple in its conception, but ruthlessly effective. So much so, the brand now counts 17 million people as app users, and the reward program has 13 million active users. Add its 25,000 retail locations to the mix and you have a massive data-collection operation to harness and activate. But as many of the early proponents of ‘Big Data’ came to find out, having all that data is particularly useful unless you can make sense of it — something AI excels at.
Starbucks has always been great at personalizing individual user experiences at its stores via its app. As a feature of accessing Starbucks’ rewards program, users authorize the brand to gather a lot of info about their coffee-consumption habits — that can be anything from their preferred drink to what time of day they’re usually ordering. This manifests itself when you visit a new store, for instance; that store’s point-of-sale system is able to identify any particular customer through their individual smartphone and Starbucks app, which can then provide the barista with their preferred order.
That personalization is great for users, and has driven a ton of business and loyalty to Starbucks. But what’s the next step in serving customers better? Making sense of all that nascent data to improve every brand touchpoint with its customers. For Starbucks, that comes via its digital flywheel program, “a cloud-based artificial intelligence engine that’s able to recommend food and drink items to customers” who might not have even thought they were in the market for additional items, according to Forbes. “It’s so sophisticated that the recommendations will change based on what makes the most sense according to the day’s weather, if it’s a holiday or a weekday, and what location you’re at.”
Or, if you haven’t been to your local Starbucks in a while, the company can automatically send out a customized email with enticing, personalized offers specifically built from that individual’s purchase history to re-engage him or her.
That’s putting the power of AI to work for your business.
Besides it being kinda cool, or you being a fan of Starbucks’ coffee, these subtle advances might not mean much to you or your business. But it’s a really good example of the next, iterative step in AI integration into our everyday lives. Starbucks isn’t solving complex physics theorems or beating the world’s best Go player; they’re trying to make their mobile app that much better. This is the next step in mobility — intelligent apps. Baking in machine learning and artificial intelligence into mobile apps in such a way that it improves that app and its users’ experiences can have huge effects on brand affinity, sales and digital loyalty. This is but one way to do that. At ENO8, we specialize in building intelligent apps or upgrading legacy apps to that standard. Intelligent apps are working for Starbucks; imagine what it could do for you…
Jeff Francis is a veteran entrepreneur and founder of Dallas-based digital product studio ENO8. Jeff founded ENO8 to empower companies of all sizes to design, develop and deliver innovative, impactful digital products. With more than 18 years working with early-stage startups, Jeff has a passion for creating and growing new businesses from the ground up, and has honed a unique ability to assist companies with aligning their technology product initiatives with real business outcomes.
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