📈 Merchandising Audit Checklist: Learn how to optimize revenue and set new sales records!
✨ Get it FREE ✨

AI in Ecommerce: 6 Ways To Empower Your Shopping Experience

AI is revolutionizing ecommerce. Learn how AI is being used to personalize online shopping, engage customers, and drive maximum sales.

Updated: February 15, 2024. Published: 

Artificial intelligence (AI) is no longer a niche technology meant only for those with exclusive knowledge or expertise. When ChatGPT launched in late 2022, it brought generative AI into the forefront of our daily lives. Today, it’s still the fastest-growing service, with 100 million weekly users


AI ecommerce is improving online shopping experiences - ai chip


AI technology advancements aren’t just revolutionizing how we find information on the internet or who we talk to when we’re bored (like Amazon’s Alexa). They’re also transforming the ecommerce industry by helping merchants create better and more personalized shopping experiences. 

AI-powered ecommerce is poised for unprecedented growth, over $11 trillion over the next four years. But there’s also stiff competition: estimates are that between 12 and 24 million ecommerce sites exist.

Within this competitive field, it is more important than ever to understand the powerful ways in which AI and machine learning (ML) can be used for online retail.


Rebuy-icon-primary Use Cases of AI for a Personalized Shopping Experiences

  1. Sales and Demand Forecasting 

  2. Customer-Centric Searches

  3. Dynamic Recommendations & Pricing

  4. Customized Product Descriptions

  5. Smart Customer Support

  6. A Modern Shopping Cart & Checkout Experience


Customers increasingly expect ecommerce companies to make personalized product recommendations to fit the customer’s lifestyle, budget, and preferences. ML allows a retailer’s ecommerce experience to be agile and adaptable from person to person at every digital touchpoint.

In ecommerce, everyone shopping on your site is a little bit different. Your website can use automation and AI tools to reflect those differences with an intelligent shopping experience that engages potential customers.

1. Sales and Demand Forecasting 

One way to elevate your merchandising efforts is to anticipate what shoppers will want before they ask for it. Using AI’s data analysis capabilities significantly enhances sales and demand forecasting in real time for online retailers. Moreover, they will help your business with inventory management and supply chain preparations. 

AI uses advanced data analysis of past sales, market changes, trends on social media, economic indicators, and even weather patterns to predict what products you should prioritize. For example, if your predictive AI model identified a pattern of higher bathing suit sales in May, you’ll want to make sure your inventory levels match that higher demand. This way, customers won’t be disappointed and look elsewhere if you run out of stock. 

2. Customer-Centric Searches

AI can also help you improve the search engine on your ecommerce website. 

With the right data collection, your business has access to a lot of information about your online shoppers. Data like their location, gender, and buying habits can all help you tailor customers’ search experience. 

For example, say you have an outdoor clothing ecommerce store with a global audience. A personalized customer journey immediately registers that a site visitor identifies as male, is located in the northern US, and has buying habits related to winter sports such as skiing. It’s currently December, and they start typing in the letter “j…” The search results should automatically start displaying links to product pages with the word “jacket.”

However, if a similar customer located in, say, Australia plugs in the same letter, their search results might be “jeans” or “joggers.” It shouldn’t assume they want a jacket during their summer season. If you don’t adjust this, they’ll feel isolated from your brand when they get recommendations for ski gear over swimsuits. 

For each season, your website should reflect relevant preferences with collection sorting based on customer data. That’s why it’s critical for ML to develop deeply tailored insights into each customer experience. 


Two creative millenial small business owners working on an AI ecommerce strategy using a digital tablet while sitting in staircase


3. Dynamic Recommendations and Pricing

ML allows dynamic changes on your website and recommendations that reflect changes in trends, seasons, and market demand. As customers shop, expose them to the right product recommendations. If a customer already has socks in their cart and a static display is set up to recommend socks, you’ve lost an opportunity to show them a compatible product.

Using ML tools on your ecommerce site enables you to offer a more logical upsell or cross-sell option. A tool can automatically read what’s in the customer’s cart and find a trending, compatible product based on the user’s information. This tells the customer that your brand understands who they are and what they need before aiding in new product exploration. 

liquid death PDP cross-sells

Dynamic pricing segmentation is another way to influence and improve the user experience. With dynamic pricing, you can automatically change the price of your products based on demand and user data.

For example, if your data shows that you have a segment of customers who frequently seek out sales or lower prices, you can offer them discounts or lower the price on items they’ve shown an interest in. On the other hand, if you have a segment that is willing to pay a premium for convenience or exclusivity, you can display higher prices with expedited shipping options. 

4. Customized Product Descriptions

The content on your product pages should be customized for the shopper viewing the page. Using the right language, images, and tone increases the likelihood that a shopper will end up purchasing the product. AI handles this dynamic content adjustment automatically. 

Using the right keywords and consumer data, AI optimizes the page for the viewer and search engines, making the page more likely to appear in search results for relevant queries. If a product is trending or there's a change in consumer sentiment, AI can modify the description in real time to highlight relevant features or benefits that boost SEO. It can also conduct A/B testing to determine which versions of the product's descriptions perform better in terms of shopper engagement and conversion rates. 

AI can also personalize the descriptions to complement other items a shopper has browsed or shown an interest in. For example, if a customer frequently buys workout pants with pockets, AI can highlight the pocket feature as a key bullet point in the descriptions of similar products.

5. Smart Customer Support

Personalization shouldn’t end at purchase. To build loyal lifetime customers, extend personalization to off-site experiences, including technical support, returns, and follow-up. 

A. 24/7 Customer Service Worldwide with ML Chatbots

Customers expect answers to their questions instantly. A smart bot can be an effective solution to frequently asked customer queries so customers always have access to answers — even when your team is sleeping.

Conversational chatbots act like virtual assistants no matter where your customers are located. These ML-powered chatbots are effective technical support solutions for customers in Bangkok who need to know if you ship there, as well as UK customers who want more information on a specific product.

B. Returns with Unique Recommendations

The returns process doesn't need to end with the customer only sending something back. It should instead recommend another product that might better fit the customer's needs.

If someone returns a pair of ski pants because they don’t need them anymore and the site recommends woolen socks, it feels disconnected and unhelpful. But when a customer returns ski pants because they didn’t find them warm enough, your website should be able to:

  • Categorize that the customer made a return.
  • Note the function of the pants.
  • Understand that the customer needs warmer pants for lower temps.
  • Offer recommendations based on the categories.

With machine learning tools, the process is automated and lightning-fast. The customer would immediately get a response like: “We’re sorry these ski pants weren’t as warm as expected. Here are some highly rated waterproof ski pants for lower temps.”

C. Product Discovery Follow-Ups

Personalization is equally important with other interactions, such as SMS or post-purchase email campaigns. These marketing campaigns can be triggered by predictive AI models to offer compatible products within the follow-up. For example, for the customer who recently bought ski pants, the marketing message might automatically display a matching ski jacket.

During the summer, your follow-up campaign should be able to help push the discovery of relevant products to that customer. If you try to sell the same ski pants they just bought, it may feel like you don’t know the customer. But if your messaging reflects buying habits and seasonal changes, it builds trust, lifetime value, and loyalty. Something like, “We’re sad to see ski season go, but check out our new line of camping gear,” reflects the changes in season, behavior, and needs.

6. A Modern Shopping Cart and Checkout Experience


Rebuy Smart Cart™ uses AI in ecommerce to improve online shopping experiences.


Another place to display intelligent product recommendations is in a modern shopping cart. A modern shopping cart typically involves an AI system that tracks customer behavior and other data to adjust recommendations or offers based on that information. The goal is to simultaneously maximize sales while increasing customer satisfaction and retention

For instance, Rebuy Smart Cart™ automatically displays recommended products and special offers to customers based on such things as customer interactions and purchase history.

With Smart Cart, merchants can implement features that encourage the shopper to go through with a purchase. Discount widgets, gift-with-purchase offers, a tiered progress bar, intelligent upsells, and a switch-to-subscription option all prompt the customer to finalize their purchase.

An intelligent, AI-powered shopping cart helps streamline and accelerate the checkout process, reducing cart abandonment and creating a more successful shopping experience.

Delight Your Customers with AI-Powered Personalization

AI algorithms and ML tools help to read and understand data, personalize customer experiences, and adjust to trends and changes in the ecommerce market. This helps you better understand your actual consumers without any extra effort on your part.

With this knowledge, you can increase customer engagement and transform their online shopping experience for the better.

AI-powered personalization should touch every interaction of a customer’s lifecycle, from shopping on a site to product discovery and technical support. Is it time to find better AI solutions for your ecommerce business? If so, try Rebuy free for 21 days and transform your basic online store into an intelligent shopping experience.




Interested in partnering with Rebuy? Let's do it.

Try Rebuy free and see why the world’s top brands use Rebuy to accelerate sales growth.

To keep up with the latest trends, platform updates, and more, follow us on LinkedIn.

Similar posts