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Home Retail News Technology

Seven ways AI is used in e-commerce

by Fiona Briggs
July 9, 2024
in Technology
Reading Time: 4 mins read

AI is more than the incredibly popular generative tools like ChatGPT; it’s also the natural language processing (NLP), data mining, and machine learning systems that work behind the scenes of website automation, customer service bots, search results, and more. You’ve likely encountered these AI tools while shopping online without realising it.

In the e-commerce industry, these abilities can enhance the shopping process for customers, as well as the productivity and profitability of online stores for business owners. When it comes to business operations, there are many ways AI can be used, and seven of the most common are outlined below.

1. Personalised product recommendations

Regardless of where you shop online, you’re likely to encounter product recommendations. This is a common feature in e-commerce stores to assist you with finding what you’re looking for and upselling other items to increase the size (and price) of your order.

AI integrations enable product recommendations to be tailored to you by analysing and predicting your shopping habits based on past purchases, searches, product views, and the behaviour of lookalike customers (customers with similar purchasing habits and history as you).

The impact of these personalised recommendations is significant, increasing revenue by more than 30% on average. It’s so powerful that nearly 50% of shoppers bought recommended items, despite having no initial intention to buy them.

2. Improved site search

Until recently, search engines relied on keywords to produce results. This method of searching required knowing the exact name of the item you were searching for and spelling it correctly if you wanted useful results. Today, search engines rely on natural language processing, which is much more intuitive of our queries — and forgiving of our spelling.

With natural language processing, the search results of an e-commerce website will be based on what you input and include synonyms, missing words or phrases, and the correct spelling. By including these additional elements while sorting through data, the results are substantially more relevant and much more likely to lead to a sale.

3. Customer support

Customer support is essential to e-commerce operations. Whether processing feedback or resolving issues, chatbots can take on many customer queries and resolve them without requiring a person to step in.

Chatbots incorporate multiple aspects of AI systems, including NLP and machine learning. As with a customer search, the NLP system will enable the chatbot to understand what a customer is asking, and the machine learning system will scour the data at hand for the correct response.

The time savings of a tool like this are considerable assets in business operations, but it has other qualities that make it extremely valuable as well, like an endless supply of patience, 24/7 availability, and ongoing learning and improvement.

4. Inventory management

Managing inventory is a massive undertaking that requires monitoring many moving elements, and not just the changing stock levels. Managing inventory also encompasses keeping accurate tabs on the entire supply chain, customer demand, order history, and special events (like a major sale or promotion). AI can assist with all these tasks.

Machine learning processes can look at current and past numbers for each element mentioned here (and any others needed) to make projections about inventory needs — like what items you need more of and how many of them you need to order or produce.

5. Fraud prevention

Whether you’re a customer or business owner, the threat of fraudulent activities or scams that compromise sensitive data is a common concern. This has led to solutions across industries for preventing fraud. For instance, customers of online casinos might avoid sharing their financial data by selecting a platform from a list of all operators with Paysafecard as one of their payment options.

One approach to prevent fraudulent activity for business owners and operators involves using machine learning. The technology can assess purchasing activities and flag any transactions that appear suspicious or unusual so that the necessary steps can be taken to protect the business and its customers.

6. Price optimisation

The e-commerce industry is highly saturated, and being strategic with pricing can give businesses a competitive edge. AI integrations can assist with finding the ideal price for your product by looking at competitor pricing and product supplies and by analysing your customers’ purchasing patterns.

7. Streamlined content production

Generative AI is a cutting-edge and exciting new tool that is getting incredible attention and capturing imaginations as people realise its capabilities. When it comes to e-commerce marketing, generative AI has the potential to be a powerful tool for streamlining content production and other marketing initiatives.

Tools like ChatGPT, Gemini, and Copilot can review and provide feedback on your current content and brand messaging. When crafting new content, these tools and others like DALL-E can assist with each step in the creative process, from ideation to final production. This saves significant time and can help strengthen the work produced in the process.

Conclusion

AI is increasingly utilised as people and businesses look for ways to update their workflows and use their time more efficiently. For e-commerce businesses, AI integrations are helping with efficiency and enhancing the overall customer experience. Whether businesses are using generative AI tools or the less visible machine learning or natural language processing ones, the impact of the tools adds up.

As AI continues to develop, its e-commerce applications will also likely increase, further streamlining e-commerce operations. But even now, the capabilities of AI are helping businesses grow their revenue and thrive at an astonishing rate.

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