Many retailers, convenience stores, and quick service restaurants are making 2020 the year that they focus on digital innovation. Why? In today’s fast-paced, busy world where technology rules our lives, you’re either thinking outside the box, or you’re stuck inside the box (with no way out!).
Technology within the restaurant space has evolved drastically over the last decade. One day you’re ordering at a counter –> the next you’re using a kiosk –> the next you’re using a mobile app, with no need to even leave your car to get a quick meal. So, what comes after mobile apps? Welcome to artificial intelligence (AI) and machine learning (ML).
AI/ML is all about optimization. Whether you’re prioritizing a list of choices customized to the user, making recommendations, or identifying cohorts based on user behavior, it is all about optimizing the experience.
Organizations of any kind (retail, restaurants, financial services, healthcare, etc.) that already have – or can easily acquire – large volumes of data on their users should be looking to use AI/ML to make sense of that data, and once you can make sense of it, you can begin to process it and extract the hidden value through AI/ML processes.
AI/ML in Real Life
AI/ML has already helped millions of people, making the impossible a reality. You may not even realize it because it has successfully entered our lives without ever interrupting our experiences. In fact, they’ve made our experiences better, faster, and easier.
Take Starbucks, for example. Starbucks records your order, allowing the coffee company to build the robust data set needed to enable context-specific recommendations, star dash challenges based on previous orders, and customized loyalty rewards. Essentially, Starbucks remembering your order is step 1 in creating an experience driven by context-aware AI.
As a society, we’re using AI/ML everyday, and the companies that are putting energy and focus into this kind of innovation are leading the world to easier, more efficient experiences. Companies not thinking about this are already miles behind.
Magic at McDonald’s
In 2019, McDonald’s purchased artificial intelligence (AI) company, Apprente, to make their drive-thrus more effective (among multiple other investments in digital organizations and innovative solutions). By using technology to optimize their drive-thru menus based on the time of day, weather, traffic, and the customer’s order, McDonald’s is upping its game, all to boost customer spend. The ability to implement personalization driven by crowd-sourced data across their ecosystem shows that while McDonald’s may not know exactly who is in the car at the drive through window, they can accurately predict – with a model trained on millions or billions of records of purchases – the time of day, weather, and other such information to create a focused, more personalized experience for their clients. Thus, reducing the issue of too many choices and allowing their customers to move through the drive through more quickly.
The market seems to agree that technology is a good investment in future growth. Last year, McDonald’s reported a 22% increase in its stock, suggesting that ongoing innovation efforts are paying off – both from a revenue perspective and with customer experiences. This is a lesson that all organizations should learn from. People are going to choose any company – their take out order, their financial partner, their fitness program – based on the brands that know and cater to their needs because their experience will be more personalized to them, and therefore easier in their busy life.
Thinking Outside the Box with AI/ML to Create Magic in Your Business
With vast capabilities, AI/ML can be implemented in a variety of ways to reach your organization’s greater goals. The following questions will help you think through how you can improve your business by including AI/ML in your strategy:
Assessing Your Place on the AI/ML Spectrum
From powerful, general purpose models which are easy to use and deploy (i.e., Amazon Personalize) all the way to crafting new Machine Learning models using Tensor Flow, and everything in between, it’s important that you find out where you are on the AI/ML spectrum, and where you want to be so that you can strategize, plan, and invest accordingly.
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