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3 ways AI can make Ecommerce more customer-focused

Rodney Laws
|
4
min read
3 ways AI can make Ecommerce more customer-focused

What’s the key to ecommerce success? What’s the vital ingredient that allows one seller to assume a commanding lead over its similar rivals?

 

Is it having great products?

 

Apple has fantastic products, certainly. However, from a technological point of view, there are more impressive and affordable alternatives available. So, is it branding that gives Apple the edge? That gets closer to the truth, but it still isn’t quite there.

 

The answer is ultimately very simple: delighting customers.

 

Apple knows exactly how to keep its customers happy. It delivers slick user experiences. It provides a massive digital ecosystem. It uses marketing to make people view its products as status symbols. In the end, how much it charges doesn’t matter as much to its fans.

 

Are you running an ecommerce business (or planning to run one)? You might wonder how you can do more to impress your customers through your service. Well, AI (the real kind, not the science-fiction kind) can offer some potent assistance.

 

Let’s take a look at how AI technology can work to make your store more customer-focused:

It can provide comprehensive 24/7 support

We live in a time of immense shopper freedom. Not only do you not need to visit a store in person, but you can also buy at any time. Wake up in the middle of the night wanting to buy something? Google calls those times micro-moments. Your smartphone is right there next to you. You can find the right product, place an order, and go back to sleep within minutes. This isn’t great for people with bad impulse control, admittedly, but it’s objectively more convenient.

 

It’s also true that international retail allows people from different countries to buy from the same sites. If you live in the United States, you can easily order something from a German site. Consider these two things: impulse buying at odd times, and buying from countries with different time zones. A problem you can easily run into is a lack of support.

 

When you go to a physical store, you expect there to be someone who can help you. Tell you where to find a product type, or give you some suggestions. What happens when you go to a site in the middle of the night and no support assistants are awake? That’s where AI can help out. A well-designed chatbot built on the Engati platform can handle basic support requests.

 

Chatbots can’t deal with all requests, obviously, but they don’t need to. Any complex issues can be logged and passed to human support assistants. Provided the shopper knows their issue is definitely being addressed, they can probably wait a while for a response.

It can help sellers keep their inventories relevant

Customers, understandably, want the online stores they frequent to have the latest and greatest products. They don’t want to need to look elsewhere, particularly when the point of a site is curation. That’s the case with dropshipping, a model that handles stock and shipping for you. There, your role is solely to pick out the best products for your customers.

 

How do you keep your inventory relevant? You can do manual research, but that’s laborious. Machine learning can do a much faster and more comprehensive job. By analyzing retail trends, it can suggest products relevant to your niche. A great example of this type of service is Sell The Trend. It can actually hook into dropshipping sites to immediately add proposed items.

 

Knowing that the retailers they like will consistently have updated inventories will make customers happier. There are other benefits for them, too. They can spend less time reaching out to ask when new items they’ve heard about will be added. They can also recommend those sites to their friends with more confidence.

It can offer dynamic recommendations

I mentioned that shoppers like in-store support, and that’s because it’s personal. But why can’t you have personalised support without human assistance?

You can. Through AI, you can offer each customer personalized recommendations based on their order histories and preferences. Someone who often buys snacks can be recommended snacks. Someone who favors a particular brand can be informed about new products from that brand.

 

That’s just the beginning, though. It can get so much more in-depth. The more an AI system learns about someone, the better it can meet their interests. Perhaps one buyer spends the most money after they get paid each month. The system can recommend high-value items at that point, and low-value items shortly before it.

 

Amazon pioneered dynamic recommendations, quickly making them common to ecommerce, but they can still be done better. While the use of private data is relatively limited now, future systems will be able to do remarkable things. Customers will receive marketing materials suggesting things they didn’t previously know they wanted.

 

Some people object to this kind of thing. They find it intrusive and presumptuous. Others have no problem with it, and I fall into that camp. You’re going to be marketed to regardless. Why not have the most relevant ads and product suggestions? No one is forced to buy anything. And going by the wild success of sites like Amazon, this is the common view.

 

Wrapping it up

AI has already done a lot to make ecommerce more customer-focused, but there’s more to come. Dynamic recommendation systems will get more advanced. Sellers will get faster at adapting their inventories to suit the zeitgeist.

 

Most importantly, customer support services powered by chatbots will get faster and more sophisticated. Overall, it’s a great time to be an online retail customer.

About the author

Rodney Laws is an ecommerce platform specialist and online business consultant. He’s worked in the ecommerce industry for nearly two decades, helping brands big and small achieve their business goals.

You can get his advice for free by visiting EcommercePlatforms.io and reading his detailed reviews. For more tips and advice, reach out to Rodney on Twitter @EcomPlatformsio.


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