Amazon recently opened a convenience store that operates without cashiers or self-checkouts at all—thanks to AI.
It works like this:
You enter the store, take items from the shelf, and walk out. The store has cameras and sensors that detect what you've taken. Then, Amazon bills your credit card for all your purchases.
An Amazon VP told Reuters that the “technology didn’t exist” to do this. Amazon spent years creating it. “It was really advancing the state of the art of computer vision and machine learning.”
Both computer vision and machine learning are AI technologies. Amazon's store is another example of how our lives are becoming more machine-assisted. You use Netflix, Siri, Alexa, and other AI tech, tools, and apps dozens of times a week.
This is all cool, but why does it have implications for marketers? Because marketing is going to soon be as machine-assisted as modern life. And Amazon's AI-powered store provides one glimpse of what the age of machine-assisted marketing will look like.
1. Data is king and queen. And the entire court.
Every single action in Amazon's store is trackable. Over time, Amazon will generate tons of data on what people buy, just like it does with its online storefront. AI and machine learning will extract insights into consumer behavior from this data. These insights could help Amazon win big over competitors.
Data is the end game for AI—and the reason for playing in the first place. Marketers need to understand this.
You need lots of good data to unlock AI's full potential. If you don't have it, you need to find a way to get it. You may need to buy it or collect it or partner with someone who has it or find a public set of data to use. But without data, your AI tools won't get far.
And without some type of AI advantage, you could face some unpleasant competition. Amazon generates more data than traditional brick-and-mortar competitors. It uses that data to tailor its products and services to attract even more shoppers. This gives the firm even more data to work with, which creates an even wider moat against other stores.
2. Find pain points and quick wins.
The concept of an AI-powered grocery store is cool. But only time will tell if this is actually a use case that makes sense for Amazon.
As Devin Coldewey writes in TechCrunch:
"It’s a bit overkill, I think, to replace a checker or self-checkout stand with a hundred cameras that unblinkingly record every tiny movement. What’s to gain? 20 or 30 seconds of your time back? Lack of convenience has hardly been a complaint for this market — it’s right there in the name: 'convenience store.'
Like so many ways companies are applying tech today, this seems to me an immense amount of ingenuity and resources being used to “solve” something that few people care about and fewer still consider a problem."
This could very well be true. Amazon's AI-powered store might just not solve a painful enough challenge for consumers.
Marketers should take note. Just because you can use AI for something doesn't mean it makes sense to. Marketers should avoid trying to fit AI into everything they do. Instead, look for problems you're already trying to solve. Then, see how AI could fit in. Otherwise, you might just create a complex, costly solution to something that isn't a problem.
Instead, start by assessing use cases and quick wins. What tasks are repetitive and ripe for automation? What pain points are you trying to solve on a daily basis? Where could you use help with productivity and performance?
3. Don’t underestimate the tech.
It's unclear where Amazon is going with this concept. It might transform retail. Or it might be an expensive flop.
Either way, the tech Amazon created is impressive. It signals how fast AI is progressing. While it's still early days, we're seeing rapid advancements in what AI can do and how well it can do it. Progress doesn't always happen evenly across AI technologies or industries. But it is happening.
Marketers need to prepare themselves for significant technological advances in our industry. It's critical to start understanding AI now. That includes the tech behind it, the tools that use it, and potential marketing use cases for it. Because while it's still early, it's moving fast.
And one day, we could wake up and see that, like the grocery store cashier, our role is suddenly obsolete.
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. An avid writer, Mike has published hundreds of articles on how to use AI in marketing to increase revenue and reduce costs. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). He is also the author of Bitcoin in Plain English, a beginner’s guide to the world’s most popular cryptocurrency.