Data Science Technologies Improving CX for eCommerce

The era of bombarding consumers with generic advertisements is now a thing of the past.

A significant majority, seven out of 10 consumers, now anticipate brands to deliver personalized ads and product recommendations. When this level of personalization is lacking, a staggering 76% of consumers become frustrated, as revealed by McKinsey’s research.

To put it simply, eCommerce personalization relies on data to present customers with tailor-made products and exclusive deals. Rather than having shoppers sift through a long list of products, personalization utilizes a customer’s purchase history and browsing behavior with the brand to suggest the most suitable items they are likely to purchase.

Imagine yourself as a customer searching for new clothes, and you finally come across an apparel eCommerce store that offers some shirts you like. As you contemplate buying one of these shirts, the web page proactively suggests some attractive pants that perfectly complement your selected shirts.

You’re more likely to buy those. Right?

In fact, as per the same McKinsey report mentioned earlier, a significant 78% of consumers are inclined to make repeat purchases from companies that implement personalization in their strategies.

Where AI, ML, and NLP Comes In?

It’s crucial to understand that achieving the desired benefits of personalization, such as increased customer satisfaction, brand loyalty, and sales, relies on precise execution. The process necessitates sifting through vast amounts of customer data, a task that is beyond the capability of manual processing and analysis by humans alone.

This is where the invaluable role of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) comes into the picture for eCommerce brands. Leveraging these advanced technologies enables businesses to extract valuable insights from the abundance of customer data, facilitating accurate and effective personalization strategies.

Intelligent Commerce is Not a Choice, It’s a Necessity

Data science technologies, including AI, ML, and NLP are already revolutionizing customer experiences throughout industries, and eCommerce is not an exception.

When implemented the right way, these technologies can do miracles for eCommerce. Let’s discuss them.

Personalized Product Recommendation

As an eCommerce merchant, one of your primary objectives is to cultivate loyalty among your existing customers, as upselling to them proves to be more lucrative than acquiring new ones.

The implementation of AI-powered personalized product recommendations becomes instrumental in achieving this goal. When your customers visit your website, the AI algorithm adeptly captures their buying behavior, past transactions, demographics, interests, and other relevant data.

Leveraging this information, the website then presents each visitor with unique and relevant suggestions, significantly increasing the likelihood of them making additional purchases beyond their initial intent.

Netflix is at the forefront of recommendation technology. The streaming giant’s cutting-edge recommendation engine, known as NRE (Netflix Recommendation Engine), employs advanced algorithms to analyze data from individual members’ viewing histories. By doing so, it generates highly personalized movie and TV show recommendations, catering to each user’s unique preferences and interests.

Always Available Customer Service

Creating a delightful customer experience involves two key components: personalization and outstanding customer service. Nowadays, customers have high expectations, with a whopping 70% percent of them anticipating swift assistance within a mere five minutes.

Enter AI-powered chatbots to the rescue! Before you brush off the idea, thinking of them as robotic and monotonous, it’s essential to understand that today’s chatbots operate on cutting-edge AI technology. These advanced chatbots are designed to mimic human interactions, moving far beyond generic, scripted, rule-based conversations. Their ability to imitate human-like responses elevates the customer service experience to a whole new level.

In the realm of modern AI chatbots, a sophisticated array of techniques, including NLP (Natural Language Processing) and sentiment analysis, are utilized to grasp not only the explicit meaning but also the context, emotions, and subtle nuances embedded in each customer query.

This comprehensive understanding empowers the chatbots to engage in more impactful and contextually precise conversations with customers, enabling them to efficiently address and resolve their issues.

While basic customer inquiries are well within the capabilities of most eCommerce chatbots, the true innovation lies in chatbots that go beyond the basics and function as shopping assistants.

A prominent illustration of this is seen in Sephora, a cosmetics retailer. Not only does Sephora’s website chatbot handle typical queries about returns and exchanges, but it also serves as a virtual assistant. By engaging customers in personalized conversations, the chatbot gathers information about their skin tone and makeup preferences, allowing it to offer tailored recommendations for products that best suit each individual’s needs and preferences.

Dynamic Pricing

Implementing machine learning in pricing strategies has become essential yet time-consuming for eCommerce brands. However, it enables them to dynamically adjust prices in real-time, considering factors such as manufacturing costs, competitor prices, market demand, and seasonal variations.

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The advantages of AI-based dynamic pricing extend to consumers in various ways:

• Ensuring fair prices by constantly monitoring competitors and making price adjustments accordingly.
• Providing personalized real-time discounts based on individual customer behavior. For example, if a customer consistently shows interest in a product, a dynamic pricing algorithm can offer them a time-limited discount to entice their purchase.

Amazon stands as a prime example of leveraging AI-based dynamic pricing effectively. The eCommerce giant utilizes machine learning to update prices for millions of products multiple times a day. By factoring in product demand, stock availability, and customer behavior, Amazon consistently delivers the most competitive prices to its customers.

eCommerce Can Flourish with AI, ML, and NLP

Be it marketing or operations, data science technologies will surely change the game. Embracing these technologies at an early stage can provide brands with valuable insights into their competitive edge in the short term and enable them to lead in optimization ahead of their rivals.

The technology is readily available today, and astute retailers are swiftly and effectively implementing it in their practices.

In the end, cutting-edge technologies like AI and ChatGPT have the potential to bring retailers remarkably closer to achieving true, personalized experiences across all communication channels. This, in turn, strengthens customer relationships, fosters unwavering brand loyalty, and propels businesses to new heights of success.

Sanjeev Verma is the Chief Executive Officer (CEO) of Biz4group, a leading AI development company based in Orlando, Florida. He is responsible for leading Biz4group’s global business strategy and operations. Sanjeev is an AI enthusiast and has been involved in the development of AI and IoT solutions for over 20 years. He is passionate about using technology to solve real-world problems and loves to read and write about disruptive technologies.