The role of AI in understanding and influencing the behaviour patterns of e-commerce customers

Our age of convenience and connection, and the technology that powers it, has found a natural home in the global consumer marketplace. And, as Salesforce illustrate, e-commerce is a profoundly lucrative space:

• 56% of organisations expect the majority of their revenue to come from e-commerce in the next three years
• 73% of shoppers use multiple channels – including Google, social media platforms, and email – for online shopping
• Approximately 21.8% of the world’s population shops online
• 95% of all purchases are expected to be transacted via e-commerce by 2040.

Changing consumer expectations, stiff competition for market share, and ease and availability of data, have meant e-commerce businesses are increasingly integrating artificial intelligence (AI) applications across a variety of business functions. Articles by Springer and IEEE explore in more detail how advancements in the field of machine learning and artificial intelligence have led to an increase in sales and innovation.

The possibilities presented by these technologies – which mimic human functions and abilities, and often seem able to read our minds – are transformative, from product recommendations and virtual assistants, to anticipating purchase intentions ahead of time and developing a seamless user experience.

What is the role of artificial intelligence in e-commerce?

For businesses and customers alike, there are huge benefits and advantages as a result of AI’s integration with e-commerce shopping platforms. For businesses, it improves efficiency and resource allocation, reduces costs, boosts sales, enhances customer experience, and supports data-driven, decision-making processes – all of which contribute to ensuring they remain relevant, competitive and profitable. For customers, it improves the way we shop online, adding convenience, efficiency, and enjoyment to our online shopping experiences.

The abundance of personal data tied up in digital e-commerce applications makes them ideal platforms for AI solutions. The four main types of AI technology that have transformed the e-commerce space are:

• Natural language processing (NLP). This enables machines to interpret and generate human language
• Machine learning (ML). This enables machines to use algorithms and customer data to make decisions and predictions
• Computer vision (CV). This enables machines to interpret information found in videos and images
• Data mining. This extracts insights from big data analytics for use in AI systems and machine learning algorithms.

In terms of e-commerce more generally, AI technologies support everything from supply chain management and process automation to an optimised customer experience.

Of course, marketers also require accurate insights into customer needs, behaviours and expectations in order to serve them the most relevant product content. AI analyses factors including psychometrics, patterns of buying behaviour, and demographics as customers browse the internet, using that data to build a highly evolved picture of an individual customer. What content are they most interested in? When do they tend to make purchases? What marketing tactics have worked previously?

But what do these technologies and insights mean for e-commerce brands, and how can they be used to influence consumer behaviour in practical terms?

How does AI shape customer behaviour and demand on e-commerce platforms?

An effective e-commerce digital marketing strategy is vital for all types and sizes of businesses, from early-stage start-ups through to huge, global shopping platforms – and AI is a critical element in its success.

Applications of AI in relation to buying behaviour and purchasing decisions include:

• Personalised product recommendations. AI and predictive analytics are instrumental in developing personalised marketing campaigns that are tailored to individual customers and target demographics. It helps businesses to present customers with highly relevant products and services – based on their previous purchasing behaviour, browsing behaviour, and other data sets – whether they’re on a website, checking their email, or browsing social media.
• Dynamic pricing. Factors such as demand, competition and inventory levels are taken into account by AI tech that changes prices in real-time, making them more attractive to consumers and encouraging purchases.
• Virtual shopping assistants. AI assistants help customers to make purchases by sourcing products, making recommendations, and comparing prices.
• Customer churn. Site bounce rate, abandoned browsing, and abandoned shopping purchases all indicate ‘customer churn’. Shopify reports that AI tools can help reduce churn by automating purchase completion emails, making it easier for customers to complete purchases, enquiring after abandoned shopping baskets, and offering loyalty discounts.
• Automation. Whether large or small, anything that removes barriers across the customer journey is highly valuable. In terms of online shopping baskets, pre-filled customer information is not only a great time-saver, but reduces the risk of customers failing to complete the last stages of purchasing.
• Chatbots. Used for answering questions, providing support, signposting, and helping customers to complete transactions, AI-powered bots support highly individualised, personalised and stress-free shopping experiences.
• Inventory management. Pop-up notifications that alert customers to the fact that ‘Only 3 items left in stock’ work to create a ‘scarce mindset’ that can prompt customers to purchase there and then, in order to avoid missing out.
• Fraud detection and prevention. As well as spotting suspicious transactions, AI can be used in other innovative ways. Negative reviews can impact whether or not a customer chooses to make a purchase or not. Global e-commerce giant, Amazon, explains in a case study how it uses generative AI to tackle fake reviews on its product listings. Its machine learning models ‘analyse thousands of data points to detect risk, including relations to other accounts, sign-in activity, review history, and other indications of unusual behaviour’.

By providing such a seamless, intuitive and personalised service, AI helps e-commerce businesses to increase customer satisfaction, fine-tune segmentation, build customer loyalty, increase individual spend, boost retention, and perform future research and data analysis to inform marketing tactics.

Are there challenges to using AI within the e-commerce industry?

As AI technology evolves, and its adoption increases, e-commerce businesses can take further advantage of the innovations – and competitive advantages – it presents.

However, it’s not completely without its challenges. E-commerce marketers must carefully consider issues of data privacy, biased AI algorithms, cybersecurity, high technology costs, and complexity of AI systems – and the skills needed to use them – when making decisions about integrating AI with their platforms in an effective, sustainable way that delivers return on investment (ROI).

Learn how use of AI and other technologies can help achieve business objectives

From boosting customer engagement to developing better user experiences, find out how AI can revolutionise the ways in which we do business.

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