11+ Best Use Cases of AI in E‑Commerce

Introduction

E‑commerce has been advancing slowly in the past few years, and the pandemic has only accelerated this process. With more people shopping online than ever, e‑commerce owners now both have an opportunity to attract far more potential customers and also many challenges to face.

From growing customer demands and increasing numbers of support questions to attempts at fraud, anyone who owns an online shop has a lot on their plate.

To handle all those tasks without cutting corners, many online retailers have decided to use artificial intelligence devices to help them learn more about their clients and provide outstanding customer service.

Could you also use AI in your shop? Here are a few ways in which artificial intelligence could also improve customer experience in your store.

How is AI transforming the e‑commerce industry?

By the beginning of 2021, e‑commerce sales hit almost $5 bn, and by 2024, experts say that will have jumped to over $6 bn per year.

We shouldn’t be too surprised by that – customers have been demanding a flexible but straightforward and convenient way to shop for years now. And online shops are convenient:

• They are available 24/7
• Shoppers can research a product and price range from the comfort of their homes.
• People can buy products in just a few clicks using online payments and have them delivered by courier or parcel locker.

It’s not surprising that there are already over two bn online shoppers, and the number is quickly growing. But those customers have also gotten pretty savvy. Now that they have thousands of online shops from which to purchase products, they won’t settle for anything less than a perfect shopping experience.

This is where artificial intelligence-powered tools can be helpful for all sizes and types of e‑commerce companies. There’s far more to AI than just being a fancy toy for large companies. It can impact every part of your e‑commerce business, from inventory management to customer service.

According to Accenture, artificial intelligence can enhance business productivity by up to 40%. and 87% of global business organizations believe that AI will give them a competitive advantage. What makes it so powerful, though? The ability to gather and analyze a vast amount of data to find patterns and then take action accordingly.

AI in e‑commerce examples

Thanks to machine learning algorithms, AI devices also get “smarter” the more they interact with customers and the more data they have to process. Using big data from your customers’ previous purchases and interactions, you can pinpoint what they want and deliver messages that resonate with them.

For example, AI can predict customer shopping patterns based on the products they purchase and send them personalized mail with an applicable discount. But those tools can do so much more – here are a few examples of how to use data gathered by AI to boost your e‑commerce store customer experience.

1. Recommendations tailored to your individual customers

With personalized product recommendations, shop owners can personalize customer interactions and provide more relevant online shopping experiences that will drive higher conversion rates, average order values, and customer loyalty. And AI‑powered recommendations can help tremendously here.

💡 How does Netflix do it?

For example, Netflix’s recommendations engine (NRE), powered by AI, is worth $1 bn per year. How does it handle providing detailed and tailored recommendations to millions of subscribers?

NRE uses algorithms to filter content based on each user’s profile. It can filter over 3,000 titles at a time using 1,300 recommendation clusters to pinpoint the exact titles that a user might be interested in.

By analyzing data from each customer visit and click, the recommendation engine can “understand” that person’s preferences and create hyper-personalized recommendations for each of them. And it doesn’t matter how many customers you have – the engine can instantly match a given customer to the right products or offers.

2. Dynamic pricing optimization

The right price for your product depends on several factors, such as your competitors’ prices, manufacturing costs, and client demand. Researching this all takes time, especially if you have many products.

What would you say if AI could do it for you and automatically change pricing based on its data? Because it can, and it’s called Dynamic Pricing.

With it, you can price your products at the optimal price at any given moment, taking into account your costs and your competitors’ prices through big data. Additionally, such systems can predict when to raise the price of a product and when to launch a sale if it has access to the correct data.

AI can also change the prices for hundreds or thousands of products in your store, saving time on manual adjustments. How could you use it in practice?

For example, increasing your prices when your competitors’ stocks are low. When consumers want a product right away, but it’s unavailable on one website, they will more than likely be willing to pay a higher price if they know they can get it from your store sooner.

💡 How does Amazon do it?

Amazon is one store that fully utilizes a Dynamic Pricing Strategy. Whenever its competitors offer promotions or discounts, they regularly adjust their product prices by up to 20%.

However, it does so gradually to ensure maximum profitability based on sales forecasts. This allows it to remain the cheapest and maintain control over its profit margins.

3. Chatbots for enhancing customer service

Keeping up with customer requests can place significant pressure on support teams. Customer support teams have their hands full every day, whether it’s answering pre-purchase questions, helping with checkout issues, or dealing with returns and exchanges. What’s more, customer expectations are now much higher than ever.

An “immediate” response within 10 minutes is rated as necessary or very important by 90% of customers. So a great way to boost your customer support while freeing up your support team of too many tasks is by using virtual assistants or chatbots on your website.

You can offer customer support even during weekends and holidays with AI‑powered chatbots. While your human support team is away, a chatbot can answer simple questions or perform simple tasks, route customers to suitable knowledge base materials, or allow them to leave messages for agents and schedule callbacks.

While these bots are not entirely self-sufficient, they can answer around 80% of daily questions, allowing live support agents to focus on more complex issues. You can also use chatbots to automatically collect customer feedback by, for example, asking them to fill out short surveys and then automatically collecting the answers.

4. Customer segmentation

In this survey, 80% of audiences said they prefer doing business with a brand that personalizes their user experience. Here, segmenting your audience is key to delivering tailored marketing communications.

Moreover, segmentation tactics can increase your marketing campaigns’ productivity, effectiveness, and ROI. For example, look at Campaign monitor – their report found a 760% increase in revenue from segmented campaigns.

Those revenue numbers come from personalized marketing promotions, devising sales strategies to increase conversions from each segment, developing products that address the specific needs of particular segments, etc. But if you had to create groups for your customers manually, that would take far too long.

Here’s also where AI can lend a hand. By analyzing the data it has, artificial intelligence tools can swiftly create customer segments for you based on the similarities it finds.

Moreover, they can analyze the data without any prior assumptions or biases, such as that young males should be the primary target for video games. At the same time, women are more interested in fitness products. Thus, AI can give you a far more accurate picture of your audience.

Many of those tools can also create entirely new segments for you by highlighting parts of your audience that could be overlooked by you or your team, even if they worked on the same data.

5. Smart logistics

Like many industries, logistics can significantly benefit from using AI‑powered or “smart” devices and automating various repetitive tasks. The purpose of smart or intelligent logistics is to use real-time information gathered through sensors, RFID tags, or similar to manage inventory levels better and predict demand.

A good example is using smart warehouse shelves that sense weight and pressure and sharing this info with warehouse management systems. With radio-frequency identification (RFID) or barcodes, companies can keep their inventories up-to-date by tracking when items are received, stored, picked, and shipped.

Businesses can thus increase production efficiency while preventing overspending, as there will be no risk of ordering more items than necessary because of a mess in the inventory.

AI can also allow you to keep track of all your products throughout the entire supply chain, from the manufacturer to your store, not just those already in it. Using a tracking system with integrated RFID and GPS technology, you can locate your products or supplies and even monitor in what conditions they are stored or transported.

As such, AI devices can be helpful if you have a lot of suppliers and vendors to keep an eye on. By doing so, you can minimize the likelihood of late deliveries or accepting damaged products.

6. Sales and demand forecasting

E‑commerce companies regularly use forecasting to manage inventories, plan logistics and warehouse space, and determine pricing strategies. Yet accurately predicting demand is only getting more challenging because historical sales data are no longer enough, even when combined with seasonal data.

Many brands have turned to AI for sales predictions to make demand forecasts more accurate and reliable. Rather than just using historical data, AI makes sales and demand predictions using real-time data, including demographics, weather, the performance of similar items, and online reviews or social media. Machine learning will also improve forecasts over time with more available data.

💡 How does Danone do it?

Among the companies that have implemented a machine learning system to improve demand forecasts are Danone. In addition to creating more accurate estimates for their short-life products, their machine learning system also improved planning between departments such as sales, supply chain, finance, and marketing.

This system also improved efficiency and inventory balance, helping Danone achieve its targeted service levels at the channel and store levels.

7. Voice search

Voice search is an increasingly popular way for consumers to interact with their devices, and this trend is impacting the way people shop online. According to a survey by Perficient, 55% of consumers are using voice search to research products, while 44% have used it to add items to their shopping lists.

In addition, Gartner predicts that by 2023, voice commerce will reach $80 billion globally. To capitalize on this trend, e‑commerce companies will need to ensure that their websites and product listings are optimized for voice search, including using natural language, optimizing for long-tail keywords, and providing clear and concise answers to common questions.

Furthermore, as voice search technology continues to evolve, there may be opportunities to integrate voice assistants into the shopping experience, such as providing personalized recommendations or allowing customers to place orders using their voice.

💡 How does Sephora do it?

A good example is the voice search offered by Sephora. In 2017, it launched one of the first Google Assistant actions, allowing users to book beauty services, play quiz games, and listen to beauty podcasts.

Users of Google Assistant can now shop at Sephora, and those with Google Home can even use Sephora’s Skincare Advisor tool to find nearby stores, get skincare tips, and determine their skin type. Users can also ask Google Assistant to play a Sephora makeup tutorial through Google Home.

8. Visual search

Visual search is another innovative feature many e‑commerce platforms are gradually introducing to attract more customers. This involves using artificial intelligence to enable shoppers to search online based on images instead of text or keywords.

For people who don’t know precisely what they’re looking for or type the wrong search terms into the search bar, this is extremely useful in helping them find relevant products faster and easier.

💡 How does Pinterest do it?

Pinterest’s Lens feature is an excellent example of this. With it, users can search for items in a photo they’ve taken with their phone’s camera or upload existing pictures from their camera roll.

In 2020, the visual search engine registered 459 million monthly active users who would instead search for new brands or products via visual search than regular search.

9. Tackle fake reviews

In the online shopping world, customer reviews are crucial to building trust. Since users cannot physically see what products look like before they buy them, they build up opinions based on reviews and ratings left by current and past buyers or users.

Approximately 31% of online reviews are fraudulent, according to a report by Fakespot, a developer of AI technology that can recognize fake reviews. For this research, Fakespot analyzed studies from more than 2m active online stores on Shopify and leading e‑commerce platforms such as Amazon, Walmart, BestBuy, eBay, and Sephora.

But self-learning artificial intelligence is becoming very good at identifying all sorts of fake reviews. These systems can analyze text patterns, writing styles, and formatting to immediately mark those that seem suspicious.

They can also compare reviews in the blink of an eye and flag those that seem fake. This could be just what e‑commerce industry needs to start winning the never-ending battle against fake reviews finally.

10. Detect cases of fraud

According to the UK’s Office for National Statistics (ONS), nearly 63k consumer frauds were reported in the first half of 2020, of which around 41k were related to online shopping and auction fraud. What’s even more worrying is that during the first half of 2019 and the first half of 2020, online shopping and auction fraud increased by 37%.

As customers slowly shift from in-store to online purchasing, e‑commerce businesses are particularly susceptible to these attacks due to the increasing volume of transactions, orders, and deliveries.

However, AI-based fraud detection and prevention tools can help merchants gain the upper hand. After analyzing all available data and understanding the context, AI tools don’t have much trouble spotting and blocking suspicious transactions.

For example, a user might place many orders in a short space of time, enter an unrecognized address in the relevant field, or skip over basic information required for delivery. AI can detect all such cases and alert business owners to potential fraud attempts.

These engines can also analyze multiple ID or credit card parameters using AI to combat the use of fakes. This technology can also prevent promo code and loyalty program abuse by catching users of multiple accounts or proxy servers to make various purchases.

11. Auto-generated product descriptions

Even for experienced copywriters, writing product descriptions that are both persuasive and SEO-friendly is not an easy task. The more products you have to sell, the longer it might take to write unique descriptions for each.

How about reaching out to AI‑powered tools for those? Of course, they are not on the level of professional copywriters, but when it comes to simple product descriptions, AI can quickly create engaging, unique, and optimized content based on the specifications.

Additionally, most AI tools now can use copywriting principles like AIDA (attention, interest, desire, action) to write like a human and also cleverly add keywords to fit the text naturally. While AI-generated product descriptions are not yet widely accepted by the industry, it’s probably just a matter of time considering how fast such tools armed with natural language processing are improving.

12. And what about Chat-GPT?

Chat GPT-powered conversational AI can help e‑commerce businesses provide personalized and natural customer interactions. With the ability to understand natural language and context, Chat GPT-powered chatbots can assist customers with complex queries, suggest products based on their preferences, and even provide customized recommendations.

This approach can help businesses build better relationships with their customers and bring personalized shopping experiences. By implementing Chat GPT-powered conversational AI, e‑commerce businesses can streamline their customer service operations and provide a more satisfying shopping experience for their customers.

Conclusion

With so much potential already visible, AI will become more important for e‑commerce owners. This technology can provide many benefits that other technologies cannot offer – from saving you and your team time on various tasks to boosting your customer experience far beyond expectations.

Add to this helping you fight rising levels of fraud, improving your internal logistics, changing product prices on the go, and providing you with far more valuable data than ever before.

In addition to these AI technologies, Chat GPT-powered conversational AI can revolutionize the way businesses interact with their customers.

Do you still doubt this will change the e‑commerce world and how customers find products online? If you don’t already use some of the before-mentioned solutions to power your business, now may be a good time to start.