How to boost your eCommerce sales with machine learning

Netflix’s algorithm recommends series based on your interests.

Amazon analyzes your purchase history to show you related products. 

Spotify creates playlists with similar songs to the ones you normally listen to. 

These are just a few examples out of the infinite possibilities of machine learning: a technology shaping the future of online shopping, which many eCommerce stores are already implementing. 

But what exactly is machine learning about? And, more importantly, how can it help you make more sales?

You’re about to learn all of it in this post. 

Are you interested?

Well, buckle up because it’s on in 3, 2, 1… 

👉 What does machine learning have to do with eCommerce?

Let’s begin in the beginning. 

Machine learning is one of the branches of Artificial Intelligence. 

Specifically, it’s a branch that studies automatic machine learning. 

The goal of machine learning is to develop information systems capable of learning and evolving on their own, without human intervention teaching them. 

The process is basically this: 

  • An algorithm collects an enormous amount of data.
  • It analyzes such data to detect patterns. 
  • It draws conclusions out of those patterns, modifies behaviors, and optimizes processes in order to be more efficient. 

It may sound a little abstract when put like that. 

But don’t worry; here’s a concrete example. 

✅How machine learning works: a case study

Chatbots are one of the eCommerce tools that benefit from machine learning the most. 

Imagine this scenario: 

  1. A person goes on your website and asks the chatbot: “What are your shipping costs?
  2. The chatbot replies, “The cost for standard shipping is $3.99.” 
  3. Then the person asks: “Do you apply a discount for wholesale orders?
  4. To which the chatbot replies, “For orders over $50, shipment is free of charge.

Now, imagine this same situation (a person asking for shipping costs then inquires about discounts for wholesale orders) happens many times. 

In other words, there’s a pattern. 

The chatbot detects it and decides that, from now on, whenever a person asks about your store’s shipping costs, it’ll show both standard shipping and wholesale order costs. 

And it will do so automatically… without you having to ‘teach’ it how to do it. 

This skill has incredible potential for any eCommerce store. 

👉 4 aspects of your eCommerce store you can strengthen thanks to machine learning

That’s enough theory for now. Now let’s see the real deal. How can you use automatic-learning AI to optimize your eCommerce’s stores processes (therefore minimizing expenses and boosting sales)?

There are many options, but we have grouped them in 4 big categories: 

  • Customer experience
  • Stock management
  • Sales strategy
  • Customer loyalty 

Let’s see each of them. 

✅ 1. Customer experience 

Customer experience is the overall perception a person is left with after interacting with your business. 

Let’s see how machine learning can help make this perception a positive one. 

➡️ Chatbots that better understand users

A chatbot is a salesperson available 24/7, which makes it a must-have to improve customer service in an online store. 

And if it is also capable of learning on its own, then all the better.

The previous example is nothing but the tip of the iceberg. Thanks to machine learning, a chatbot can: 

  • Identify users’ most constant queries (and display them as FAQs, for example).
  • Increasingly improve its understanding of polysemous words, synonyms, ordinary language, and offer a more adequate, context-based response to messages. 
  • Develop a more natural and interactive language. 

Chatbots that are capable of learning are referred to as ‘open’ and represent a very interesting option to offer high-quality customer service.  

machine learning ecommerce ventajas

➡️ Personalized search results for each customer

Let’s imagine two different people visit your eCommerce store on the same day. 

  • The first person looks straight for the internal search engine and types “smartphones”. After browsing the results for a while, they choose one and buy it. 
  • The second one scrolls the browsing menu, clicks on the “laptops” category and ends up buying one. 

A few days later, they both visit the website again and type ‘case’ in the internal search engine. 

Now get this: 

  • The person that bought the smartphone gets smartphone cases in the first results.
  • Conversely, the search engine returns laptop cases to the second person. 

This is possible if you have an AI-powered internal search engine capable of implementing machine learning. 

It’s amazing how these search engines are capable of understanding your customers in order to offer them personalized results based on their search history, previous purchases, etc. … 

This benefits the shopping experience and increases conversion. 

ATTENTION: if you’d like to have a search engine such as the one we’ve just described, don’t miss the end of this post 😉  

✅ 2. Stock management

We’ve already reviewed PIM issues elsewhere —software designed to control your eCommerce store’s stock.

What if we combined PIM with machine learning?

That would mean your system could: 

  • Detect and predict specific lapses in which there would be spikes in demand for you to be on top of it and not run out of stock. 
  • Notify you about products whose sales are dropping so you can prevent stockpiling. 
  • Automize shipments to suppliers.  

Stock control is a critical eCommerce task because something ‘as small’ as running out of a specific item for a couple of days can make you lose sales.  

Here are a couple posts that might interest you about this same topic:

✅ 3. Sales strategy 

An AI-powered application of machine learning can also help you increase visibility and sales. 

We’ll break that down for you. 

➡️ Real-time price update

Imagine you could know at all times: 

  • Whether your competitors are rising or dropping their prices.
  • What offers they have on.
  • When there will be an increase (or decrease) of sales. 

And out of that information, you could real-time update the prices of your own products. 

Of course, it is virtually impossible for a human to keep these factors under control 24/7. 

But an AI-powered system can surely manage. 😉 

For example, let’s say you have a home goods eCommerce store. Every year, as Earth Day or any other ecological event approaches, sales of eco products increase. 

With AI, you could spot that pattern and predict future spikes of demand.  

It’s not only that. Prices would automatically increase or decrease according to fluctuations in demand so you can obtain the highest possible profit. 

This is called dynamic pricing strategy and it’s a very advantageous technique. 

➡️ Cross-selling optimization

Cross-selling is a strategy that consists in offering users various related products so they buy them all together. 

So how can machine learning be useful here?

Imagine you now own a photography eCommerce. 

After analyzing every transaction on your eCommerce, AI tools detect a pattern. When customers buy a reflex camera for the first time, most of them also shop along:

  • A wide-angle lens.
  • A telephoto lens.
  • UV filters. 

In that case, whenever a person is looking at a reflex camera’s card, the site will display such items as related products. 

✅ Customer loyalty programs

There are many ways in which machine learning can help you increase your retention rate, and we’re about to see two of the most interesting ones. 

➡️ Anticipating product returns 

What if you could read a customer’s mind and know when they’re about to click the “return product” button?

For example, maybe your eCommerce store’s AI detects that the same user: 

  • Has asked about your return policy via chatbot. 
  • Has visited the product card of a recently-bought product.
  • Is viewing similar products. 

Thanks to AI, the same pattern has been detected in other customers before, and it’s most likely that they are also thinking about returning the product. 

So it’s possible to anticipate that situation and: 

  • Send the customer an email asking whether they’ve had any inconveniences with their purchase and would like to change it, explaining the alternatives they have. 
  • Show them other similar products, in case they want to swap products. 

So, even if in the end they decide to return the product, they will love the care they have received so much, it’ll be even more likely they’ll buy from you again. 

➡️ Predict the churn rate

AI is also capable of identifying when a loyal customer is about to stop buying in your eCommerce store.

For example, it’s possible they:

  • Visit your website less frequently. 
  • Make smaller purchases every time. 

If you know this, you can set in motion different actions to bring that customer back: send out an exclusive discount, show new products they might be interested in… 

Note: if you’re interested in this matter, here’s a thorough post on how to reduce the churn rate. 

que es el machine learning ecommerce

👉 Are you prepared to set your eCommerce store to ‘machine learning’ mode? 

There’s only one question left to answer: 

How can I implement artificial intelligence and machine learning in my eCommerce store?” 

The simplest thing is to find an external software provider that uses this technology. 

Doofinder is a perfect example. 

Doofinder is a smart (AI-based) search engine capable of autonomous learning. 

This allows personalizing search results for every customer, as we mentioned above. In addition, it is also capable of:

These features (amongst many others) increase sales of eCommerce stores using Doofinder up to 10% and 20%. 

Would you like to know everything it can do for you? 

> Then click here and try Doofinder for free in your eCommerce store for 30 days.  (opens in a new tab)” rel=”noreferrer noopener” class=”rank-math-link”>>> Then click here and try Doofinder for free in your eCommerce store for 30 days.