The Future of Shopping: A Shopping Cart With a Recommendation Engine

Photo credit: r. nial bradshaw on Flickr.Retail experts know that when customers use shopping carts in brick-and-mortar stores it increases the average number of items sold per transaction.

It is therefore not surprising that stores are looking for ways to make the shopping cart an even more integral part of a customer’s shopping experience.

Walmart is one of these stores.

If you do a quick search online, you will see several of the patents that Walmart has filed in recent years involve ways of adding technology to their shopping carts.

However, it was one patent that was filed in September of 2017 that really caught my eye. The patent allows Walmart to know when specific items are placed in a container.

Although this patent doesn’t say that it will be used with a shopping cart, it could be. And, if used in conjunction with a customer’s smartphone, it could give Walmart the ability to recommend items that customers might want to purchase in a brick-and-mortar store in the same way that Amazon does when customers are shopping online.

In other words, it would give Walmart the ability to use a recommendation engine to deliver suggestions to customers shopping in their brick-and-mortar stores.

What Is a Recommendation Engine?

As I pointed out in a post in 2016, “In the context of what I am referring to, it is an information filtering system that helps a business recommend items to customers that they might be interested in. For additional information, Wikipedia has a good explanation.”

“If you want to see an example of a business effectively using a recommendation engine to help its customers find products, visit Amazon.com,” the blog post continues. “The Amazon.com recommendation engine uses a combination of several input data, including past purchases, product ratings, and social media data.

When you visit your online cart on Amazon.com, it automatically recommends other items based on what other customers who bought the items currently in your online shopping cart purchased in the past. (In fact, Amazon.com recommends other add-on items even before you get to your shopping cart.)

Bringing the Recommendation Engine to the Brick-and-Mortar Store

Amazon and other online stores effectively use recommendation engines to increase sales online.

However, offline it gets more difficult.

With the exception of maybe Amazon Go stores, most stores don’t know what the customer is currently purchasing until they get to the cash register.

And, once a customer gets to the cash register, it’s probably too late to get them to add another item unless it is being kept in a location nearby or the deal offered is really good.

Currently, having customers talk to sales associates is the best and often only way for the store to suggestive sell add-on items to customers in a brick-and-mortar store based on what the customers are currently purchasing.

Even if the customer is shopping with his or her smartphone in one hand, suggestive selling is limited to information collected from past transactions or online behavior (if the store has tracked that) and some demographic data. Mobile coupons, rebates, and targeted ads work, but again, there really isn’t a way to know what the customer is currently purchasing.

That is, unless you use some sort of sensor to track them. That is why Walmart’s patent could be so valuable.

If Walmart develops the technology that they patented and puts it into a shopping cart, they would have the ability to know what customers are currently buying and could therefore send advertising messages to them that would recommend items that are often purchased with the customer’s current selections or that the customer might be interested in.

Granted, this wouldn’t be the first time this was tried out.

In 2012, Microsoft teamed up with Whole Foods to test a shopping cart that would help a customer be sure that they bought everything on their shopping list and even warned the customer that an item had gluten in it if the customer had let the system know that was one of the things that he or she was trying to avoid.

It appears that the Microsoft/Whole Foods smart shopping cart didn’t make it past the testing phase. However, I think this was due to the fact that they tried too many things at once. In fact, some of the features seem to be solving problems that just don’t exist.

It also might have been ahead of its time or just not a good fit for the brand.

Final Thoughts

It might be some time before we see a shopping cart like the one described in this post.

However, the store that finds a way to do it correctly will definitely increase sales.

And, who knows, it could be another way for stores to sell paid contextual advertising to brands that are trying to reach customers in the offline world based on where they are, who they are, and what they are buying.

As I mentioned earlier, Walmart has filed a patent that would make a very important part of the process possible.

If there is a person in Bentonville who is working on a shopping cart that can do this, I’d love to write a post that gives more details. There are a lot of cool possibilities. And, if Walmart isn’t working on this or hasn’t thought of it yet, which I find hard to believe, please feel free to steal the idea. Or even better, contact me, as I have some additional ideas that might be useful.

Photo credit: r. nial bradshaw on Flickr. (Creative Commons Attribution 2.0 Generic license – CC BY 2.0.)

Chad Thiele

Marketing analyst and strategist, content curator, applied sociologist, proud UW-Madison alumnus, and an Auburn-trained mobile marketer. My goal is to help businesses identify trends that will help them achieve their marketing objectives and business goals. I'm currently looking for my next career challenge. Please feel free to contact me anytime at: chadjthiele@gmail.com.

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