Defining Conversational Commerce
Conversational commerce refers to the use of AI-powered assistants, messaging platforms, voice interfaces, and chat-based experiences that allow consumers to discover, evaluate, and purchase products through natural conversation rather than traditional browsing or search. In practice, this means consumers can interact with an AI assistant (such as ChatGPT, Alexa, Google Assistant, retailer chatbots, or messaging apps) and ask things like:

• “What’s a good dairy-free creamer for coffee that doesn’t contain soy?”
• “Please reorder the protein bars I bought last month.”
• “Assemble a White Lotus-inspired gift basket of local Sicilian items with a total cost of $120. Tell me why you recommend each product, and how it connects to the show.”

Notably, this can look like serving up options in response to a search or offering new impulse opportunities. For consumer-packaged goods (CPG), conversational commerce represents a shift from shelf-based discovery to dialogue-based discovery. Eventually, these sites are likely to initiate shopping or to serve up brands. For example, a platform might ask whether the user would like gift ideas as part of a query around baby shower themes – or to know the best deals on educational toys for Black Friday. In practical terms, instead of navigating menus, filters, and product pages, the consumer simply states their need or provides context clues, and the system recommends products, explains options, and facilitates purchase in a conversational flow.

In Layman’s Terms: How Conversational Commerce Works
At its core, conversational commerce combines three capabilities:

1. Natural Language Interfaces: Consumers describe needs using everyday language rather than selecting categories or filters.
2. AI-powered Product Understanding: AI systems interpret consumer intent and match it to relevant products using product data, reviews, and contextual signals.
3. Transaction Enablement: The assistant (or AI “agent”) can complete purchases, add items to carts, reorder products, or route consumers to retailers.

This experience can occur across several channels:

• AI assistants (ChatGPT, Google Gemini, Perplexity, etc.)
• Retailer chat interfaces
• Messaging platforms (WhatsApp, SMS)
• Voice assistants
• Embedded AI shopping tools on retailer websites

How Has Product Discovery Evolved Across Formats?
The traditional digital commerce experience is navigation-driven, while conversational commerce is intent-driven. Conversational commerce is guided, personalized, and iterative rather than self-directed and search-based. Impulse opportunities can be generated in all formats using physical aisles and traffic, digital shopping widgets, or AI-based prompts. Here’s how each shopping mode functions:

• Shelf Commerce (physical retail shelves) – The retailer defines the category. Consumers physically walk aisles organized by categories defined by retailers. They visually scan products and compare packaging manually using low and high engagement processing to select and deselect. Shelf placement, packaging, brand awareness, and trade promotion drive brand success.
• Search Commerce (retailer search bars and digital shelves) – Consumers define the category by entering a search term (brand, SKU, category, product descriptor, etc.) and scroll through results and product pages. The sites use algorithms to serve up preferred brands based on investment levels and conversion probability signals. Shoppers compare products using retailer “you may also like” suggestions, A+ comparison charts, or manual research. Search ranking, digital shelf optimization, ratings & reviews, retail media. A+ content and comparison charts can also assist in driving brand success.
• Conversational Commerce (AI assistants and interfaces) – Consumers describe needs in natural language and receive curated recommendations and simple comparisons. Brand success drivers include product intelligence, relevance to consumer intent, trusted brand signals (especially from credible / credentialed 3^rd parties), and AI-readable product data.

In other words:

• Retail era: Visibility drove sales
• Search era: Discoverability drove sales
• Conversational era: Credentialing, contextual relevance, and agentic recommendation engines augment store and search paths to drive sales

What Steps Should We Take Now to Get Ready?

1. Focus on eCommerce Fundamentals: While discovery will vary, the back end of conversational commerce will run through traditional eCommerce platforms – and SKU or ASIN strength will feed into retail recommendation agents. Brands must have best-in-class eCommerce fundamentals in place. This includes strong data hygiene, profitable assortment, adequate inventory, competitive pricing, and strong alignment with retail operational requirements. Brands should also be investing to drive traffic, Share of Voice, and conversions, as all 3 metrics help maintain strong SKU ranks and page 1 visibility.
2. Create Content That is Best-In-Class and On Time: Brands must have effective systems that deliver well-defined toolkits for basic eComm content and optimized A+ content. Current shopper satisfaction, which is often driven by content that helps shoppers navigate to the right item, is critical. Additional requirements for incremental content could overload brands already struggling with sub-optimal systems. To achieve this, brands must have go-to-market organizational structures with clear decision-making and processes that are designed to deliver strategic, equity-driving content on time. Strong product descriptions, tags, ratings, and reviews are key today. Meta tags and contextual insights will become the base requirements. Eventually, AI platforms will read A+ content, reviews, and more to make recommendations – and brands need to be sure they are able to add this content as it becomes necessary.
3. Use Frameworks to Evaluate New Demand Creation Opportunities: While not yet launched, some AI platforms have announced plans to integrate advertising into the user experience. Our Simpactful experts believe retailers will also begin surfacing new conversational commerce demand creation tools. These will undoubtedly result in new costs-to-serve. As was once true with retailer search, DSP, and audio ads, brands need to be ready with frameworks and beta-testing approaches to determine worthy investments.
4. Adopt an Experimentation Mindset: Unlike eCommerce, we expect the adoption of Conversational Commerce to happen quickly, given the signals of major retailers and Holiday 2025 shopper behavior. Winners will embrace change and adapt quickly. Doing so will require an expectation and celebration of experimentation (even if experiments fail).

Want to win in AI Commerce? Simpactful can help! Our team of eCommerce experts brings deep experience across strategy, retail operations, and marketing. We are skilled in benchmarking brand eCommerce practices against future-state requirements, identifying and addressing operational gaps, and providing hands-on support and coaching where needed. Simpactful’s team has worked at retailers, managed brands across eCommerce channels, and directly managed DTC businesses, giving us the perspective to quickly spot opportunities and redesign organizations and workflows for what’s next. Contact us today at contact@simpactful.com or 925-234-6394. Visit www.simpactful.com.