What is conversational commerce and why it’s changing the way we shop

This information is accurate as of April 2026.

Conversational commerce uses messaging, voice, and natural language interfaces to support commerce. Instead of browsing static web pages, clicking through product catalogs, and filling out forms, customers discover, evaluate, and buy products through real-time, two-way dialogue. The term was coined by Chris Messina, the product designer who also invented the hashtag, back in 2015. His original framing still holds up: "Conversational commerce is about delivering convenience, personalization, and decision support while people are on the go, with only partial attention to spare."

What's changed since 2015 is the technology behind it. Generative AI, large language models (LLMs), and sophisticated natural language processing (NLP) have helped turn conversational commerce from a niche experiment into a growing category. Multiple research firms project 12 to 14.8% compound annual growth through the end of the decade.

The category is still early, but the brands getting the infrastructure right now will have a meaningful advantage as adoption accelerates.

Conversational commerce runs across four primary channels.

Messaging apps like WhatsApp, Facebook Messenger, WeChat, Instagram DMs, and SMS provide the most widely adopted channel. Meta's WhatsApp Business Platform now exposes APIs for marketing messages, conversational automation, and payments within chat. Business messaging traffic is projected to grow from two trillion messages in 2025 to roughly three trillion by 2030.

AI assistants powered by NLP and machine learning handle everything from product recommendations to full purchase flows. A Statista survey found that 36% of shoppers say recommendation tools always influence their purchase decisions, with another 25% saying they frequently do.

Voice assistants like Alexa, Google Assistant, and Siri bring commerce into spoken-language interactions. Google and Shopify announced the Universal Commerce Protocol to support agent-driven checkout across AI surfaces.

Live chat and hybrid interfaces blend human agents with AI, handing off depending on the complexity of the interaction.

The difference from traditional ecommerce is fundamental. Traditional ecommerce is one-way browsing. Conversational commerce is a two-way dialogue where the assistant refines recommendations through conversation and often completes the purchase without the customer ever leaving the messaging interface.

As Forrester Principal Analyst Emily Pfeiffer puts it, "Customers are asking questions rather than entering search terms. They are using natural language and nuance, learning to refine further rather than start over."

Conversational commerce looks different depending on the business model, but the pattern is spreading across retail, restaurants, grocery, banking, travel, and B2B buying.

The clearest proof that conversational commerce changes buying behavior comes from brands that have already shifted from broadcast messaging to two-way dialogue. DTC accessories brand Proof Wallets achieved a 21x ROI from customers who engaged in SMS conversations after switching from one-way SMS blasts to conversational SMS. Founder Dana Peters described the shift: "Before, SMS was used to send one-way messages, announcing product drops or mass-distributing discount codes... With Shopper, we can actually have natural conversations in our brand voice."

At enterprise scale, the personalization demands ratchet up dramatically. As early as 2016, Starbucks deployed hyper-personalized reward offerings to loyalty program members, generating 400,000 variations that more than doubled customer response rates compared to prior segmented email campaigns. The approach has since expanded across the brand's digital channels.

According to McKinsey's State of Fashion 2026 report, shopping-related generative AI searches grew 4,700% between July 2024 and July 2025.

QSR offers some of the clearest quantitative benchmarks for conversational commerce. Taco Bell rolled out Voice AI to 500 drive-thrus, the largest activation in the industry. QSR Magazine's 2025 Drive-Thru Report found that AI locations achieved a 71% suggestive selling rate versus 58% at human-staffed locations. AI took the entire order in 72% of interactions, with 81% order accuracy.

Papa Johns announced an AI partnership with Google Cloud to deliver personalized offers, content, and timing based on learned preferences. CEO Todd Penegor's framing is telling: "We're not just reacting to orders, we're anticipating our customers' needs and proactively providing tailored recommendations and offers."

The strategic driver behind many QSR conversational commerce investments is data ownership. As Modern Retail documented, third-party delivery apps "share exceedingly little information about customers with restaurants," making it "difficult to build any kind of customer loyalty system." WhatsApp-native ordering restores brand visibility into individual customer behavior.

Grocery brands are moving quickly. Albertsons deployed "Ask AI," a conversational search tool, while growing its loyalty program to 48.7M members. Target launched a ChatGPT app in November 2025, and Instacart became the first grocery partner to offer embedded shopping within a ChatGPT conversation.

But the grocery personalization gap remains real. Grocery Doppio's research found that data silos and poor strategy remain the primary blockers.

Adoption varies sharply by vertical. In banking, nearly 40% of customers have not interacted with even basic customer service assistants. Travel brands are experimenting aggressively, with Air India's "eZ Booking" letting users complete reservations by texting an AI agent, though Skift reported in March 2026 that a mismatch persists between industry investment and customer readiness to delegate booking.

B2B has moved fastest. According to Forrester, 61% of business buyers already use or plan to use a private generative AI engine to support purchasing. Buyers shortlist vendors, create RFPs, and recommend pricing through these tools. 

The channel changes how incentives can be delivered. One case study documents a hospitality brand's WhatsApp assistant handling a service request, then immediately offering 10% off the next booking, valid for only two hours, within the chat. That kind of time-limited, contextual offer only works in a conversation.

But delivering the right incentive in a conversational context requires something most brands do not yet have. They need the ability to evaluate a customer's full profile, current session context, and promotional eligibility in real time. Then they need to return a personalized response within the cadence of a messaging exchange.

Research by Talon.One and Harvard Business Review shows that 62% of organizations saw increased sales from personalized promotions. That explains why conversational commerce puts so much pressure on the decisioning layer behind the chat experience. If the offer logic, loyalty entitlements, and customer context cannot work together in the same moment, the exchange feels generic.

Forrester's analysis identifies a critical architectural constraint. In owned brand experiences, the system can authenticate the customer and provide loyalty entitlements. Third-party answer engines like ChatGPT and Google Gemini cannot guarantee loyalty benefit attribution without integration to a merchant's identity systems. For brands that have invested in a loyalty program, owned channels are where conversational commerce and loyalty strategy converge.

McKinsey's research on personalization at scale identifies the primary failure mode. Companies optimize for reach when they should optimize for relevance. Deploying a WhatsApp integration without fixing that tendency recreates the same problem in a new channel.

That directional shift also shows up in the Talon.One and HBR study, which highlights a growing strategic focus on promotions, discounts, and loyalty programs. The goal is to make each offer more precise.

Forrester goes further, warning that self-service risk will harm customer experience in 2026 as cost-cutting drives premature deployment.

So what do the experts recommend?

Get the data house in order first. McKinsey states directly that "maturity depends" on the maturity of technology, data integration, and organizational setup. Across every vertical researched, the primary operational barrier is customer data trapped in silos across POS, ecommerce, loyalty systems, and CRM platforms. Without connected data, the system cannot be genuinely helpful.

Build context-rich AI agents, not scripted chat flows. Accenture draws an explicit distinction between AI agents equipped with company-specific data versus fixed conversational flows. Only the former builds trust.

Design human escalation as a feature, not a fallback. Deloitte frames this as a trust requirement: "Customers need to understand when AI technology is involved, what its purpose is, and how to exit the loop to get in touch with a human."

Measure against incremental conversion, not message volume. Conversational commerce should reduce the volume of promotional noise a customer receives while increasing the impact of each interaction. Track whether the conversation changed behavior, not whether a message was delivered.

Protect your loyalty program relationships. BCG's analysis of agentic commerce identifies a clear strategic choice. AI assistants on brand-owned platforms strengthen customer relationships more than ceding the conversational layer to third-party agents. Who owns the customer data from a ChatGPT-facilitated purchase remains publicly unresolved.

Conversational commerce is moving toward something bigger: agentic commerce, where AI agents go beyond informing decisions and start taking actions on behalf of the customer, from booking flights to reordering groceries to restocking office supplies. Emerging platform partnerships, agentic checkout flows, and embedded shopping experiences within conversational interfaces are all early signals of this shift.

Gartner projects that 70% of customers will use a conversational AI interface to start their service journey by 2028. Consumer Benchmark Survey data from Forrester shows that 24% have already used ChatGPT. Customer adoption is real but not yet mainstream. The brands that will benefit most are the ones building the underlying infrastructure now: real-time data integration, personalized incentive logic, and loyalty program continuity across channels.

Commerce is becoming a conversation. The brands that connect their incentives infrastructure to that dialogue will earn loyalty. The rest will keep broadcasting into the void.