We give recommendations to our friends, family, and colleagues constantly in conversation—about restaurants, financial advice, recipes, entertainment, you name it—and they leave a lasting impression. Now, thanks to new technologies, brands can replicate this staple of human experience online through the emerging practice of conversational commerce. Global heavyweights like Amazon and Walmart have already entered the fray, and Juniper Research predicts that conversational commerce channels will facilitate over $290 billion in sales this year. With advances in AI—and personalization technology purpose-built to leverage it for identifying and responding to unique customer needs—that number is bound to grow, especially as brands discover new opportunities for its use.
Imagine a fully conversational website that engages customers on a personal, rather than transactional, level: A site visitor looking for an easy-to-use coffee machine that can brew a latte on par with their neighborhood coffee shop could be welcomed to the homepage with the prompt, “Hey, I’m here to help you find what you need. What can I get you today?” with the option to respond. They could then simply type: “I want barista-level coffee without having to add milk, water, and coffee every time.” The site would go on to respond in real time, surfacing coffee machines that deliver exactly what they’re looking for. And with large language models (LLMs), the experience could identify and respond to subtle signals behind the search to deliver not just want the customer says they want, but what they actually want, floating recommendations for a full-blown espresso machine.
This future isn’t as far away as brands may think, and waiting too long to invest in foundational conversational commerce experiences could mean falling behind as competitors tap into the potential of this breakthrough technology. In this article, we’ll cover the basics of conversational commerce and its most common types, highlighting examples of how you can apply it to your website today as the first step toward building a truly cross-channel conversational commerce strategy, whatever your industry. Plus, we’ll share why it’s such an important outlet for delivering empathy-driven experiences that enable customers to feel truly seen and understood.
Let’s dive in.
Conversational commerce is where messaging/chat and shopping collide. A type of eCommerce, it takes on a variety of forms: voice assistants, automated chat, and messaging apps are the most common. Often powered by natural language processing (NLP) systems and artificial intelligence, this technology can ingest and decipher speech and text to communicate with consumers—just as humans do.
That means it can go beyond the transaction and help site visitors solve issues, discover products or services, or help with compiling wish lists. Perhaps most importantly, conversational commerce enables brands to deliver hyper-personalized messaging and recommendations for people interested in specific products or services. This creates a fluid, convenient and human-centric shopping experience, bolstering customer satisfaction, brand loyalty, sales, and growth.
The technology is defined by three core attributes:
Conversational commerce is primed to become a major customer service channel within the decade. The proof is in the pudding: 49% of U.S. adults have used an AI chatbot for customer service in the past 12 months, according to data from Google and Ipsos. And the NPR and Edison Research 2022 Smart Audio Report found that 62% of U.S. adults use a voice assistant on any device.
Breakthroughs in natural language processing and similar technologies have only accelerated conversational commerce’s momentum, garnering greater engagement from customers. The days of generic customer service interactions for site or app visitors—defined by basic greetings such as “How can I assist you?”—are long behind us. Now, we can finally speak to machines as we would a good friend, and they, in turn, can understand us. What’s more, the demand for more human-like interactions is on the rise. In 2023, ChatGPT set the record as the fastest-growing web platform ever. And a recent report from Khoros reveals that 75% of consumers prefer an authentic human voice over a perfectly crafted brand message.
Simon Kahn, VP of Marketing at Google, predicts: “Gone are the days when brands control–and consumers receive–the message. Consumers of today want conversation and co-creation.” Brands that meet these expectations have the power to reshape product discovery, brand engagement, and online shopping as we know it.
Now that we’ve unpacked the importance of conversational commerce, let’s go over the different kinds of conversational commerce—and why you might pick one type over the other.
Whatever form of conversational commerce you choose, they all share the same fundamental principles that help narrow the endless stream of choice for customers. The most appropriate version to use will depend on a brand’s end goal.
Chatbots typically use a messaging pane, providing templated conversations hosted on a company’s website or mobile app. They’re among the easiest conversational commerce solutions to implement, since they’re often delivered out-of-the-box and require minimal coding or technical expertise.
Many brands have also integrated chatbots into real-time, text-based applications like Slack, WhatsApp, Messenger, iMessage, and WeChat to provide a more conversational and seamless experience for users. By leveraging these popular messaging platforms, brands can tap into the familiarity and ease of use of these apps, while also cultivating greater engagement focused on the individual user’s needs.
Historically, chatbots have followed a limited range of conversational paths, which helps brands collect data from users in an orderly fashion and unlock deep insights into customers’ preferences. Yet, due to their rigidity, they’ve often been limited to customer support functions. However, recent breakthroughs in AI have flipped the script. Consumers now embrace entirely new ways of searching for products, even turning to ChatGPT for purchase guidance. With the advent of AI-powered conversational experiences like Shopping Muse, customers can now have a natural, free-flowing conversation like they would with live chat, but without the need for a human on the other end. This cutting-edge conversational experience uses natural language processing combined with deep learning models to analyze contextual and behavioral data and swiftly personalize recommendations for each site visitor, allowing them to seamlessly interact with the brand and navigate large product catalogs with greater efficiency.
Soon, we’ll see these personal “AI assistants” expand into verticals like Department Stores, Home and DIY, and Cosmetics. They’ll also be able to be accessed across channels via places like search, product detail pages (PDPs), no-result pages, and cart pages, reflecting the local language and currency.
For brands outside of retail, templated chatbots can be leveraged to reap more robust customer data—and in turn, improve ROI. Here are a few sample use cases for different industries:
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Live chat is a type of customer support service that enables users to engage in text-based, real-time conversations with a company’s support team or sales representative. Users typically converse via an embedded chat widget on the company’s website or mobile app, with the goal of providing more timely responses once connected to a representative.
Live chat is considered one of the most humanistic conversational commerce experiences because it involves a real person on the other end who can guide the conversation and provide personalized assistance to the user. It should be noted that chatbots and live chat are often used in tandem to maximize human resource efficiency and reduce wait times for customers. In practice, this is relatively simple: a customer is first served a chatbot to see if their query can be resolved quickly and, if it is too complex, their inquiry is then routed to a live customer assistant. This gives brands the best of both worlds.
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Quick review: live chat |
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A voice assistant is a software program that performs tasks or services for a user, given via a spoken prompt. In the early years of voice assistant technology, customers were sometimes easily misunderstood, and thus hesitant to use it. But voice assistants have grown more popular over the last decade, since natural language processing technology has empowered voice assistants to listen and respond like a real human. Today, more than 42% of Americans now own a smart speaker or other voice-enabled devices.
Voice assistants can now provide bespoke responses or suggestions based on context or user history. Over the next few years, as the experience becomes even more tailored to their preferences, customers will likely place even more orders through voice assistants. The rise of Generative AI and advanced machine learning algorithms, for example, is already making voice ordering a quick and convenient experience.
Voice assistants are now applied across a broad array of industries:
Retailers that don’t have the resources to invest in cutting-edge voice ordering tech still have ways to get in on the trend. For example, they could create an Alexa Skill (a voice-activated app for Amazon’s personal smart assistant) to provide verbal recommendations and offers, connecting the online web shopping experience to customers’ smart devices with minimal friction. Skip to the 30-minute mark of this webinar on Taking digital personalization to the physical world for a live demo.
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Quick review: voice assistants |
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Understanding conversational commerce—and its many forms—is crucial to keeping up with consumers’ ever-evolving appetite for personalized, emotionally resonant interactions. By keeping up with these expectations, brands stand to reap a wide range of benefits, which include:
Improved customer insights: Think about how much info is conveyed about an individual through a single conversation. Add other contextual information—such as geolocation, time of day, and weather data—and brands can start to get an accurate picture of a customer right off the bat. Businesses can then use this data to craft better omnichannel experiences, easily guiding customers towards content and products they’re interested in, when they want them.
Reduced friction: Customers face more choices, options, brands and products than ever. With so many choices, customers crave guidance so they can be confident with their purchasing decisions. But with conversational commerce, customers no longer have to type vague queries into a search bar and cross their fingers for relevant results. The call and response set-up means customers get what they need faster, reducing the friction that leads to decision fatigue. Overall, this creates a fun, one-to-one shopping experience that feels more human.
Scalability: With AI-driven conversational experiences, brands can offer the one-to-one benefits of live chat without limits of agent ability. AI shopping assistants, for instance, can handle thousands of complex customer interactions simultaneously, 24/7. Not only that, but they can be integrated across multiple channels and touchpoints, such as mobile apps, brand websites, and more. This means global audiences can receive hyper-personalized, conversational recommendations at a scale that has, heretofore, been impossible to deliver.
Greater empathy: As users interact with your conversational commerce channels, your brand can empathically surface reviews, specifications and more in a way that feels tailored, natural, and human. By doing so, they feel like your brand is invested in finding the right product for them, rather than trying to close a sale. This nurtures a deeper customer-brand relationship, and in turn, enhances trust and loyalty, encouraging customers to come back for more in the future.
Improved performance: Conversational commerce can use guided selling principles to help create personalized, human-centered experiences tailored to each stage of the purchase journey. Past interactions can also be used to train either AI or human representatives, meaning these experiences become even more tailored and relevant over time. What’s more, customers are free to explore and use conversational commerce tools without the limitations that can complicate human experiences, like time, language, or knowledge level. The result? Smarter product recommendations that boost conversions, unlock increased engagement, and drive revenue from cross-sells and upsells.
Conversational shopping experiences that leverage purpose-built AI to deliver even more personalized results are the future of conversational commerce. They will empower brands to intuit customers’ needs and connect them with products they actually want—all in a way that feels like chatting with a knowledgeable friend.
For companies that have yet to capitalize on the benefits of conversational commerce, capturing attention from ready-to-engage users is easier than you think. AI-powered shopping assistants like Shopping Muse are not only changing how people find products and interact with your brand, but they’re also plug-and-play solutions. Additionally, out-of-the-box chatbot templates, which are built for customers to interact and self-report their affinities using predetermined conversational paths, are a simple way to streamline product discovery. Alexa Skills can also help brands provide verbal recommendations and offers on customers’ smart devices—even if they may not have the resources or bandwidth to invest in state-of-the-art voice ordering technology.
After implementation, brands should A/B test to validate and refine their experiences overall, and then continually optimize each variable tied to their conversational commerce channels and touchpoints. From there, brands can identify additional personalization opportunities, layer them into their preexisting roadmap, and innovate as they go.
