Conversational commerce gives product teams a useful framework to guide how they improve the buyer journey without overhauling a product's entire interface. Tactics like embedded chatbots and automated messaging reduce friction and contribute to higher conversion rates, especially at high-intent moments.
This article will explore conversational commerce, how it works, its benefits and use cases, how it differs from social commerce, and more.
What Is Conversational Commerce?
Conversational commerce is the use of real-time messaging throughout the buyer journey to improve both customer support and purchase completion.
Chris Messina first coined the term in 2015, describing it as an intersection between messaging apps and online shopping. It began with early chatbots and human agents on e-commerce websites, and today includes more advanced digital commerce experiences across multiple channels using AI assistants.
Common channels include:
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Messaging platforms
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Website chat widgets
The primary goal is to remove barriers in the customer journey and, therefore, boost order volume. It enables in-the-moment interactions between brands and customers to address questions or to personalize recommendations.
For example, rather than having to click away to an FAQ page, a potential customer can chat with an automated agent that provides support on any page of the site.
Customers increasingly expect these types of interactions and higher levels of personalization. Recent research from Accenture found that 51% of consumers are now open to interacting with AI as part of the purchasing experience.
Brands are also incorporating real-time interactions into digital experiences, with 70% of large enterprises in 2024 reaching more than half of their customers through conversational platforms.
How It Works in Practice
Here are a few ways conversation-driven commerce works in the real world.
Messaging Apps
Messaging apps that enable this include popular options like Messenger and WhatsApp. Brands can use tactics like online ads to direct users into one-on-one chats on these platforms to recommend products and answer support questions.
In 2023, for example, Meta made it possible for businesses to launch ads that bring users directly to WhatsApp conversations with company accounts.
The benefits of using messaging apps include comfort and continuity. Since consumers already use these apps in their day-to-day lives, the familiar interface makes them easy and intuitive to use. If a consumer leaves the conversation, you can automate follow-up prompts to re-engage them rather than letting the conversation disappear completely.
Website Chat
Chat widgets on websites give customers the opportunity for real-time guidance and answers throughout the purchase process. While automation can handle most routine queries, hand-offs to live agents ensure the experience remains positive for users rather than annoying if their issues aren't resolved.
The key to a successful approach here is clear escalation paths and smooth transition processes. For instance, expecting users to repeat their query once a human agent comes to the chat can create frustration.Â
Chatbots and AI Assistants
When you add AI assistants into the mix, conversational commerce can scale beyond basic bot responses and fast hand-off to live agents when queries get more complicated. Since they can interpret intent, they have the capability to resolve support issues in real time.
A customer may have questions about shipping or payment during the checkout process. With preprogrammed responses and human agent wait times, they may simply abandon the cart. But AI chat can respond contextually and in real time, making the sale more likely.
Data integration and AI model fine-tuning are integral to making this a productive and frictionless experience for customers.
Voice Commerce
Voice assistants can extend the conversation into hands-free scenarios. Customers can link their accounts, so the voice assistants can access order histories, add items to their cart, and place orders. Post-purchase, they can usually track orders and provide status updates.
Nearly one quarter of global consumers say they use voice-activated smart assistants to make regular purchases, with a further 19% having previously used smart assistants to order at some point. Implementation requires accurate catalog and order system integrations alongside secure authentication flows.
Chatbots and AI in Conversational Commerce
Chat-driven commerce started with basic chatbots. Users could select specific pre-defined questions and steps to progress. In the background, product teams structured clear conversational pathways and static responses.
Early versions were more like interactive FAQs because the bots lacked true conversational capabilities. On the business side, they reduced ticket volumes for human support teams, but poorly-structured workflows could leave customers frustrated.
AI is quickly changing this dynamic. Conversation-focused commerce can now leverage advanced natural language processing (NLP) and large language models (LLMs), which introduce the ability to interpret context. Where chatbots previously relied on fairly rudimentary techniques like keyword matching and simple NLP, AI now has intent interpretation. This means chatbots can handle free-form questions and information and provide more personalized, human-like responses to customers.
During the discovery or research stage, AI can recommend relevant products or help articles, even when the user asks open-ended questions. While purchasing, bots can help with everything from sizing concerns to questions about payment options and return policies. In the post-purchase phase, AI assistants can track orders and handle questions about returns.
On the business side, this level of 24/7 support can drastically reduce the need for human intervention. Alongside the opportunity for cost savings, it also enables higher conversion rates as consumers are less likely to abandon carts or purchases. Recent research from Rep AI supports this, finding that out of the shoppers who respond to AI chatbots about abandoned carts, 35% followed through with their purchase. Â
Examples and Use Cases
The opportunities for implementing message-driven commerce in digital experiences are extensive. Here are a few examples:
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Product discovery: AI-powered chatbots can behave like virtual personal shoppers by guiding users on tailored journeys to suggest products they might like. Interactions can include product discovery, comparisons, and add-ons.
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Account onboarding: Account setup can require multiple steps and verifications, especially in regulated industries like banking. For example, a fintech app could use chat to guide users through Know-Your-Customer (KYC) verifications to reduce abandonment rates.
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In-app purchases: Conversation-driven commerce can boost upsells through in-app chats by seamlessly integrating these opportunities into existing customer interactions. For example, gaming platforms can use it to make personalized recommendations during purchases or help gamers troubleshoot payment issues in real-time.
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Appointment management: Service providers and healthcare companies can use chatbots to help customers or patients with appointments, from scheduling to gathering useful pre-appointment information, like reminders to sign HIPAA consent forms.
Top Platforms for Conversational Commerce
Conversational commerce is powered through the WhatsApp Business Platform, where brands can run ads that directly open a conversation with the business when a user clicks them. Brands can host entire product catalogs in the app for use in these conversations, alongside features like in-chat payments in certain countries. WhatsApp chatbots can guide users from discovery to purchase and even post-purchase customer support.
Facebook Messenger
Facebook tightly integrates Messenger with business pages, so users can start conversations from a brand's profile. Paid ads that drive users directly to Messenger conversations are also popular and can be set up with pre-populated messages or response options for users to boost their shopping experience.
Product teams can leverage the Messenger Platform API to automate responses and enrich conversations with media (like product images) to guide users to decisions without leaving the Facebook app.Â
Instagram Direct
A key feature on Instagram is Shoppable Posts, where brands and influencers can tag products in their content. Clicking the tag brings users to an in-app product page with a link to purchase. With conversational commerce, brands can send links to these products in chat for a shorter and less disruptive path to purchase.
Facebook Messenger and Instagram Direct are both managed under the same Meta messaging platform. While this means product teams can build once and deploy to both platforms, custom conversational flows for each platform help to maximize results, as user behavior and preferences can vary from one to the other.
WeChat has a network of Mini Programs that operate like lightweight apps inside the platform. This enables brands to set up entire storefronts and manage everything from payments to loyalty programs and personalized offers right from the app.
Conversational opportunities are present throughout these flows, with users able to message brand pages or open a chat with customer service throughout the purchase process. Â
Apple Messages for Business
Through Messages for Business, brands can take advantage of features like product catalogs and appointment scheduling, all integrated with Apple Pay to further simplify the purchase process. It requires integration through Apple's Business Register with conversation design using native iOS UI elements like list picker and time picker.Â
Voice Assistants
Popular voice assistants like Amazon Alexa, Google Assistant, and Apple's Siri enable voice commerce through mobile devices and smart speakers. Adoption may be lower than messaging apps for both brands and users, but conversational commerce is particularly useful here for streamlining re-orders within everyday household routines.
These platforms require official, specific integrations depending on the voice assistant, including:
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Alexa Skills
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Google Actions
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Siri Shortcuts
With these integrations, you can connect voice commerce capabilities with your catalog, order, and payment systems.
Web Chat
External platforms provide easy access to customers who use these apps continuously in their daily lives, but embedded web chat is still one of the most important platforms for conversation-driven commerce because the business owns and controls it completely, from data and security protocols to branding.
You can build web-based bots for your website or app through custom-built messaging APIs/SDKs or use a third-party provider. The most important considerations, however, include tight integrations with your CRM and other relevant systems.
Conversational Commerce vs. Social Commerce
Many people might consider the terms "conversational commerce" and "social commerce" interchangeable, but they describe different (if overlapping) approaches to digital sales.
Conversational commerce specifically focuses on real-time, answer-and-response interactions between brand and user. It can happen across multiple platforms with the goal of streamlining the buying journey that's already happening, whether it's at the discovery or post-purchase stage. It's between brand and consumer, allowing users to ask questions or get personalized guidance while shopping.
Social commerce, on the other hand, relates specifically to social media platforms. It's the ability to discover, research, and buy products on platforms like Instagram or TikTok without having to navigate away from the platform. Social commerce also applies more generally to the entire customer journey, covering elements like product discovery and comparisons via user-generated content and influencer posts.
Although they're mutually exclusive concepts, they do frequently overlap. A user might see an influencer post an Instagram Story, then send a direct message to the brand with questions about delivery times.Â
Benefits of Conversational Commerce
Improved Conversion Rates
Conversational touchpoints, especially in conjunction with AI chatbots with contextual capabilities, provide clarity and convenience at any given moment throughout the customer journey. Rather than waiting minutes, hours, or days, users get an immediate response to purchase-defining questions.
While this reduces cart or purchase abandonment rates, the positive user experience also has a compounding effect by encouraging return visits and repeat purchases. Similarly, personalized recommendations and guided shopping can increase average order values.
Drop-Off Reduction at Checkout
The final steps of the buyer journey are often the most risky. When payment methods seem unclear or finalizing the purchase requires too many steps, users are more likely to abandon it altogether.
Email follow-ups can encourage users to return, but conversational features go a long way towards reducing the initial abandonment and increasing successful conversions.
This is especially true when implementing chat-driven commerce via social media platforms because you reduce the users' need to leave the platform they are already on. Consumers are also increasingly purchasing directly on social media platforms. A HubSpot survey in 2024 found that 46% of respondents had purchased from Instagram within the last three months.
Ability To Provide 24/7 Support
High-quality, responsive customer support is a cornerstone of positive online user interactions. Users expect to be able to find help almost instantaneously when they encounter an issue.
They also increasingly expect to find assistance across multiple channels. In fact, according to the same survey, 17% of all consumers have used direct messages on social media to get customer support, with the figure as high as 30% among younger demographics.
Chabots, especially AI assistants, can ensure multiple channels are covered across all regions, 24 hours per day.Â
Lower Support Costs
Although many brands understand the importance of responsive, capable customer support, it also comes with high costs when relying solely on human agents.
The automation brands can employ through conversational AI chatbots drastically reduces the burden on human support teams.
Research conducted at one company with 5,000 customer service agents found that using generative AI increased issue resolution by 14% per hour and decreased the time spent dealing with an issue by 9%.
Not only does automation lower costs overall, it also means faster response times on more complex cases since human agents have far fewer generic queries to attend to.Â
Key Technologies Behind Conversational Commerce
The chatbot frontend is only a small piece of the tech picture. Here are some other tools and platforms that power this process.
NLP and LLMs
NLP models and LLMs power the interpretation of user intent, context, and meaning. This moves your conversational commerce strategy beyond keyword matching and simple, automated responses to back-and-forth support between the AI chatbot and the customer. Full integration with both product and customer data increases the accuracy and relevancy of responses.Â
Bot Frameworks
Bot frameworks are where the structure for building and managing conversational flows comes into play. They integrate with your AI models to handle state management and dialogue progression for consistent and scalable AI conversational capabilities.
Conversation Designers
Although they're not a piece of technology, your conversation designers' skillset is integral to your tech stack. They are the team members who map out flows and escalation paths and, critically, how to handle edge cases. Good conversation design means handling errors appropriately and protecting brand identity and consistency.Â
Messaging APIs
Messaging APIs and SDKs handle the technical delivery of real-time communication between AI chatbots and end users, connecting the app's interface to communication networks and back-end systems. They handle message delivery and device syncing and enable you to deliver this level of automation at scale. These tools allow you to power live conversations without building chat infrastructure from scratch, with SDKs further simplifying some of the UI work.
Integrations
The final layer of this tech stack connects the conversation infrastructure with other business systems, especially CRMs and order management software. Without the data gained from these integrations, your chatbot would be limited to answering basic questions. Support for specific orders or products would be extremely limited.
Making Conversational Commerce Work for Your Product
Building chat and conversation into the commercial experience for your customers smooths the path to purchase. With conversational commerce infrastructures, product managers have a framework for reducing friction without needing to reinvent the whole interface. The real challenge is selecting the right channels and ensuring clean integration with your core systems.
A well-oiled conversation-driven commerce workflow acts as a real-time, responsive layer in the product experience for customers to improve conversion rates and outcomes.
Successful implementation requires a thoughtful approach to conversation design and clear fallback pathways so that conversational commerce adds to the experience, rather than creating new hurdles.