E-commerce

Enhancing customer engagement: The role of conversational commerce
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Second only to personalization, conversational commerce has been a hot topic of conversation (pun intended) amongst retailers for the better part of the past decade. The concept of conversational commerce started in 2014 when Amazon introduced the Echo and we all began to ask Alexa about the weather forecast, top news stories and to help us set a timer to cook the perfect egg. However, the promise of an enhanced shopping experience through conversational commerce was still very nascent, and the shopping experiences were less than underwhelming except when you were trying to reorder a previous purchase.

Humans just did not know how to speak to artificial intelligence, and the AI was dependent upon very structured queries, or ‘prompts.’ We know that Prompt Engineering is critical to successfully engaging with artificial intelligence, especially Generative AI. “Prompt engineering is the practice of designing and refining prompts—questions or instructions—to elicit specific responses from AI models. Think of it as the interface between human intent and machine output.”

Fortunately, we have come a long way from those days of “I’m sorry I don’t understand” to a world where humans can engage with machines through natural language. These breakthroughs in technology; computing capability, large language models (LLMs) and natural language processing are key to truly delivering on the promise of conversational commerce as it was first coined in 2015 by Uber’s Chris Messina.

What are the benefits of conversational commerce? You don’t have to look too far to find research from analysts and agencies who indicate that by leveraging conversational commerce a retailer can expect to increase conversion rates, lower cart abandonment, improve customer service and retain more satisfied customers. As per the poll commissioned by Anderson Consulting, almost 62% of internet customers stated that they would purchase more products online if live customer support was available and the retailer provided relevant advice, guides and comparisons including reviews. Moreover, the research indicated that a more conversational approach also reduced shopping cart abandonment by up to 30%.

What does conversational commerce look like? We have seen what conversational commerce can look like in the examples of live chat bots where a shopper can interact with a bot in real-time to resolve customer support issues and respond to basic product queries. But with Generative AI and new natural language capabilities being introduced to the market, conversational commerce is taking on a whole new meaning to enhance the customer experience and increase engagement.

By harnessing the power of AI, natural language processing (NLP) and machine learning (ML), conversational commerce technology can now deliver on the promise of optimizing product recommendations, enhancing search functionality, and tailoring content to meet individual customer preferences.

In the past, merchants had been at the mercy of pre-determined business rules that leverage only a few parameters or data points (margin, inventory level, price) to merchandise product results pages for both search and browse. Now, merchants can tap into the massive increase in computing power, NLP, and ML to truly optimize category and product detail pages that are tailored to each consumer, engaging in a digital conversation throughout the buying process. We will continue to see retailers embed assisted shopping capabilities into their web experiences to facilitate these conversations.

Conversational commerce capabilities will extend to the merchandising practices of cross-sell and upsell, leveraging the same technologies to present better product recommendations as well as product comparison engines and buying guides.

Let us consider online buying guides which until recently have been pre-curated packages or bundles of products. With Generative AI assisting conversational commerce, a consumer buying guide can be assembled “on the fly” including multiple variations and a more personalized experience.

Imagine you and your partner have decided to renovate the guest bathroom of your home, but you would rather not hire an expensive designer. You would like to choose the fixtures and plumbing that your contractor will need to complete the job. Where do you start? You are not interested in visiting multiple showrooms and you prefer to complete this task online. Wouldn’t it be fantastic if there were a Home Improvement retailer that could walk you through a digital shopping experience that engaged you in a conversation that led you through a series of queries and responses which included product comparison capabilities so you could choose the ideal product. What is the size of the bathroom? Would you like a shower or shower/tub combo? Should the vanity have one or two sinks? Do you prefer a chrome or brass finish?

By its nature, this digital conversation would be the same dialogue a consumer would have if they were to engage with a sales associate or designer in a brick-and-mortar location or a customer service representative in a call center. While this example references one of the more detailed purchases, we can envision how conversational commerce will enhance product discovery and the shopping experience across multiple categories while also reducing product returns if we can do a better job of understanding customer expectations. Not merely a simple product listing.

Which brings us back to the topic of personalization, these days the holy grail of commerce. According to a 2022 Forrester study, only 13% of companies were planning to reduce their marketing investment in content management and personalization technologies. Meanwhile, in the same study, 36% of consumers indicated that ‘nothing will motivate me to share more personal information’. So how can a brand do a better job of personalization if more than 1 in 3 consumers are not interested in sharing more personal information?

Enter “conversational commerce”, a mechanism that does not rely on data that is stored in a customer data platform, but rather leverages the signals and inputs from a consumer in the moment, with context. The most basic form of this type of ‘in-context’ data are the queries that originate from a shopper’s search. According to the 2023 The Future of Ecommerce report, 69% of consumers go straight to the search bar when they visit an online store. With 7 out of 10 consumers immediately leveraging on-site search, the opportunity is ripe to engage with shoppers in a product conversation. However, it is a wonder that more retailers are not optimizing search to facilitate a more relevant conversation. As indicated in the Future of Ecommerce report, 80% of consumers have exited a site because of poor-performing search. Improving search as the steppingstone to a mature conversational commerce web site is low hanging fruit for every retailer to invest in. As highlighted in the Algolia State of Search Report 2023 businesses see search as one of the top drivers of revenue, demand, and improved customer experience. The benefits are clear when 70% of shoppers are more likely to purchase if the search results are personalized to them.

The future of conversational commerce and GenAI will leverage consumer queries, search and zero-party data that is explicitly shared during the shopping journey to improve personalization without tapping into the sensitive issue of personal identifiable information. However, conversational commerce can vastly improve for those consumers who are willing to share their personal identifiable information in exchange for an enhanced personal shopping experience.

With conversational commerce technologies in place, the most significant outcome will be that consumers will finally experience the shopping experiences they have been looking for; personalized, frictionless and without compromising security. In today’s online landscape, trust is something retailers must actively earn rather than passively expect from customers. Conversational commerce empowers retailers to provide online consumers with a human-like experience, fostering a genuine rapport that cultivates a strong sense of trust.

About the authorMichael Klein

Michael Klein

Principal, Klein4Retail

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