Conversational Commerce is the interaction between customers and businesses through various online channels. These interactions often include product questions, support queries, personalized recommendations, and reading reviews—all in real-time.
In today’s ecommerce landscape, no conversation about customer engagement is complete without acknowledging the rapid advancements in AI, machine learning, and large language models (LLMs).
TIRED: Outdated chatbots that gave canned, irrelevant answers, forcing users to type "representative!" over and over again in frustration. Traditional search functions that required exact keyword combinations, often returning irrelevant results.
WIRED: AI-powered, multi-modal conversations that understand context and semantics. Smart recommendation engines that predict what you need before you even ask for it.
But what does all this mean for Shopify merchants, and how can you use conversational commerce to increase conversions?
Let’s take a look at the evolution of conversational commerce with insights from Sebastian Hooker, co-founder of Nimstrata and ex-Googler, to understand how far we've come and where we're headed.
The Early 2000s: Keywords Dominate the Conversation
In the early days of ecommerce, structured keyword search dominated platforms like eBay and Amazon. Search engines relied heavily on word frequency and positioning in product descriptions to deliver results. At the time, brick-and-mortar retailers struggled to transition their catalogs online without substantial investment in custom technology or by listing on major marketplaces.
For most retailers, conversational commerce was out of reach unless they built their own search infrastructure—often yielding underwhelming results.
The 2010s: Natural Language Processing Takes the Lead
As ecommerce platforms like Shopify, Magento, and BigCommerce rose in popularity, search capabilities began to evolve with natural language processing (NLP). NLP shifted the focus from exact-match keywords to user intent, understanding the meaning behind searches. This was a game-changer, but retailers still spent countless hours manually merchandising search results to meet customer needs—a labor-intensive process, particularly for stores with large catalogs.
During this time, conversational commerce became more accessible for small to medium-sized retailers, though still limited by the tools provided by their chosen ecommerce platforms.
The 2020s: AI and Shopify Redefine Conversational Commerce
Today, ecommerce platforms like Shopify have democratized online retail, enabling nearly anyone to create an online store. Meanwhile, AI technologies like large language models (LLMs), semantic search, and real-time product discovery algorithms have brought a new era of conversational commerce to Shopify merchants. AI allows businesses to personalize search experiences in ways previously only available to ecommerce giants like Amazon.
Shopify merchants can now implement conversational commerce features that offer customers a highly personalized, two-way dialogue with their product catalog, refining search results and boosting conversions.
With the rise of AI tools like ChatGPT, customers are becoming accustomed to intuitive chat interfaces across digital platforms. Soon, they’ll expect the same seamless, conversational buying experience from Shopify stores.
Preparing for the Next Leap in Conversational Commerce
So how can Shopify brands prepare for the future of AI-driven conversational commerce? Sebastian Hooker from Nimstrata offers these key tips:
- Ensure Consistency in Product Data: Structured data like product tags and metafields should be accurate, human-readable, and consistent across your product catalog.
- Understand Your Current Search Conversion Rates: Before adopting new conversational commerce technologies, benchmark your existing search performance. This will help you assess the impact of new tools through A/B testing.
- Identify Key User Journeys: Review common user paths on your site to find opportunities for AI-powered enhancements. Start small and iterate your way to success, remembering that simple and intuitive journeys often convert best.
Bonus for Shoplift Customers: Nimstrata is offering an exclusive Search Relevance Audit for Shoplift customers. Visit Nimstrata for a detailed report on gaps in your product discovery experience and an evaluation of your store’s readiness for conversational commerce.
