The Motley Fool Industry Focus podcast continues its celebration of 25 years of Motley Fool investing wisdom by looking ahead at what the next 25 years will bring.
In this segment, Fool analyst Vincent Shen discusses the gold mine which Amazon.com (AMZN +2.68%) has the potential to uncover through the expansion of its automated Amazon Go store: granular customer data.
A full transcript follows the video.
This video was recorded on June 26, 2018.
Vincent Shen: Going back to the consumer experience in the store, what we were talking about with Trax reminded me a little bit -- the concept, at least -- of Amazon Go. This is the convenience store that made headlines earlier this year when Amazon opened it to the public. If you recall, what makes the store so unique is that there are no checkout lines at Amazon Go. Instead, customers swipe into the store, they connect the shopping basket to their accounts, and then they just take whatever they want off the shelf and walk out.
People have already referred to this as the store of the future. I've seen some recent headlines saying that companies like Walmart and Microsoft are trying to find similar competing systems to this Amazon Go model. So, maybe there is some stickiness here to the idea.
But, what Amazon Go has built out ultimately makes for a smoother, faster trip to the store for the consumer. They also argue that employees can better spend their time focused less on the point-of-sale and more on service. That initiative, at least for Amazon, is getting expanded outside of the original Seattle locations to, potentially, Chicago and Los Angeles, as well.
Before we get too sidetracked on that, I think the key innovation here is related to Trax in terms of the interaction with products at the store. Amazon Go, in terms of the sensors they built that track what people take off the shelf, or put back on, or whatever they put in their bag or their basket or whatever it may be -- they collect data on that. I think it shows exactly how, or at least closer to how, people interact with different products.
An analogy I'd bring up here, the one we were talking about before we into the studio, was Netflix. I've seen complaints recently in some of the TV and film communities and blogs I follow about the quality of Netflix originals, for example, and other content in the library. They'll say the originals are no good, it makes no sense that the company can spend billions of dollars per year on what makes up a lot of what they consider bad movies. Frankly, Netflix knows, I think, what its subscribers watch better than even the subscribers themselves sometimes. Everything from how the content is consumed to when, on what device, did you finish the episode, how about the entire season, did you pause a movie and go back or end up abandoning it -- all of these things, all of these trends in the genres, the popularity of specific actors and directors, can be analyzed based on the platform that Netflix has built.
I know that retailers, for example, would kill for that kind of granular data. If a department store -- like Nordstrom, for example -- could see how people navigate the racks at their store, what they pick up, what they actually try on, the brands, colors, having that kind of granularity would be an incredible boon for these companies. I feel like Trax, Amazon Go, they're building out the technology that's getting to a point where we're getting closer and closer to that being a possibility, that level of sophistication. I think it's going to be very powerful, in terms of the companies matching the products they're putting in their stores with the demand of what consumers want, and ultimately that being a better experience for everyone involved.
