What is Agentic Commerce? How AI is Changing the Way People Shop Online

The world of eCommerce has moved beyond using AI to merely help shoppers shop. Now, AI agents have become shoppers, shopping for customers.

Instead of browsing and scrolling through hundreds of products, consumers are now using AI-powered shopping agents to take the legwork out of purchasing.

In this blog, we look at how agentic commerce is changing the way people shop online, how it is changing customer journeys, and what Shopify brands can do to adapt to this new.

Let’s get started!

What is agentic commerce?

Agentic commerce is online shopping where an AI agent does research and comparison of products, and purchases it. The shopper does not have to go through these processes. A shopper can set goals or limits for the AI agent, or the agent draws insights from the shoppers’ data and completes purchases. 

Here’s the difference between traditional eCommerce, AI-assisted shopping, and agentic commerce.

How does agentic commerce work: a typical customer journey

Here are the typical phases in a customer journey in agentic commerce:

1. A shopper describes a need or a goal. At times, they may ask a question. For example, ‘which is the best bicycle for children?’

2. An AI agent interprets their preferences and constraints by gathering data, past purchase history, preferences and limitations set by the shopper.

3. The AI-powered shopping agent discovers various products from different brands and compares them.

4. The AI shopping agent evaluates various factors, such as price, availability, delivery options, payment options, reviews, and more.

5. The shopper approves a recommendation or purchase based on those shared by AI.

6. The AI agent takes it forward to checkout, completing the transaction, and post-purchase tasks.

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6 ways AI is changing how people shop online

McKinsey research reveals AI-driven agentic commerce could drive $5 trillion in global retail sales by 2030, and 25% of transactions will be driven by AI agents rather than humans. So, let’s understand the different ways AI is changing how people are shopping.

1. Product query is moving from search to conversations

With traditional eCommerce, shoppers usually shopped with the help of keywords. And so, the product recommendations were only as good as the keywords. For example, ‘red party shoes’ would display all red shoes, for men, women, and kids, heels and others. And shoppers would further browse these recommended products to find the one they like.

But with agentic commerce, AI has made shopping a more conversational activity. Shoppers now tell the search tab details they might share with friends. For instance, ‘I am looking for red party shoes but I have flat feet so looking for something that is comfortable and won’t hurt when I’m on my feet for long’. 

Here’s what has changed:

• Shoppers describe needs in natural language: All shoppers may not know which product will meet their need or even if there’s such a product. They only know what their need or problem is. For instance, my room becomes warm at night, need something to keep it cool. Products such as curtains, air conditioners, fans, or cooling coating materials could be the solutions. AI can suggest these categories that the shopper may not even have thought about.

• AI interprets preferences and limitations: While keyword search may be limited to a few words, a conversation can help AI learn more about shoppers’ preferences, context, and limitations and provide more relevant product recommendations. 

• Product discovery through follow-ups become more intent-driven: Shoppers can share follow-up queries, which helps AI narrow down results. This also gives it a more personalized feeling, just the way in-store salespersons and shoppers converse to share a better understanding of what shoppers are looking for.

2. AI is replacing browsing with curated recommendations

In traditional eCommerce, shoppers browsed through hundreds of products in multiple categories and subcategories; used filters and went through pages of results. Not only did this require a lot of time and effort, but the results also depended on how well shoppers know how to navigate the catalog. 

With agentic commerce, the process of browsing thousands of products is getting replaced with curated recommendations. Here’s how it works:

• Instead of a catalog, shoppers see selected products: AI shows shoppers a small selection of products that is tailored to the shoppers’ preferences, rather than a full catalog.

• Comparison across brands and retailers: Shoppers can themselves compare products and brands, but their ability to do so can get limiting after a point. However, with AI-powered shopping, shoppers can discover products from across brands, not just one retailer. 

• Relevance becomes more important than ranking: In traditional eCommerce search, a brand that has a high-volume keyword might have more visibility. With agentic commerce, product relevance becomes more important and shoppers end up seeing products that are narrowed down to their specific needs. There’s a psychological shift in the shopping experience, from browsing to exploration. 

3. Product comparisons are faster and better

One of the most tedious parts of shopping online is comparing products, brands, and retailers. But not since AI has joined in. Traditionally, shoppers had to keep multiple pages and tabs open; and move to and fro between pages to run comparison. Add to this, the mental pressure of remembering what one read on which product page.

Here’s how agentic commerce has made product comparisons better with the help of automated AI workflows.

4. Shopping journeys are becoming more personalized

The idea of personalization in commerce has been around since the 1980s, coined as the term ‘relationship marketing’. But what has changed is the depth of personalization, thanks to AI. 

Earlier, personalized product recommendations were based on behavioral patterns, such as what you clicked in the past and what similar customers bought, apart from demographics. 

However, AI bases personalization on the above combined with many other aspects, including real-time information. Here are some:

• Preference: Once AI assistants gather knowledge about your preferences, for example, you shop for a family of six that includes different generations, and prefer specific colors, it remembers and shares more relevant suggestions.

• Context-aware recommendations: When shoppers search for products, AI takes note of the past data collected and makes recommendations based on context.

• Bundles: AI can assemble products with a purpose instead of a generic set of things.

• Use-case tailoring: Different shoppers may be looking for the same product to perform different functions. AI knows which product to suggest for which use.

5. Checkout is moving closer to the point of discovery

In traditional eCommerce, product discovery and purchase are stages that are quite far. For instance, shoppers search for products, find them, compare some, zero in on one, create an account, and then make a purchase. Here’s how AI reduces the gap:

• Fewer redirects: When shoppers move between sites, it’s easy to get distracted and abandon a site.

• Less repetitive input: Shopify stores retain saved details, such as payments and address, making it faster to complete shopping.

• Shorter decision windows: With AI, product recommendations and checkout can happen side by side, encouraging impulse purchases.

6. Brand visibility is expanding

For decades, brand visibility meant search engine visibility, and if brands ranked well, shoppers could find them. Now, many consumers research products through the help of AI - AI assistants and agents. Brands now have to appear in AI-generated recommendations. Here’s how AI has changed brand visibility:

• Product information that is complete, accurate, and with specifics for variants have a higher chance of being recommended.

• Reviews: AI reads what customers write. It analyzes both volume and substance, making it easier for brands to show up in AI-assisted channels.

• Policies: Shipping, returns, warranties, and guarantees - these aspects are important for shoppers and they often search products based on them. AI has the ability to compare one against the other when sharing recommendations.

How can Shopify brands adopt agentic commerce?

Here are a few strategies that Shopify brands can implement for adopting agentic commerce.

1. Make product data structured, complete, and machine-readable

AI agents read structured data, such as titles, descriptions, images, pricing, shipping speeds, etc., and recommend products. Hence, products with poor product data are hard to match shoppers’ requests. Here are some tips to follow:

• Use consistent terminology

• Product information saved in images does not get read

• Ensure product page URLs are proper

2. Strengthen product discoverability across channels

To ensure your products appear across AI channels, you must first understand the requirements of different channels. Here’s what you must do:

• Review your Shopify settings and assess which AI channels receive your data

• Run tests on AI platforms, just the way shoppers would search, for instance, product category prompts (best shampoo for dry hair)

• Track if your brand name appears, what is written about it, and if the facts are right

• Keep your brand story consistent everywhere so that AI channels gather consistent information 

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3. Optimize product pages for questions, not just keywords

AI-agent search pages need to answer questions because customers are asking questions, not just searching for keywords. Here are some tips:

• Put content that answers key questions right on top, making it easier for AI agents to pick up your pages

• Describe who the product is for and for what purpose so that its use case and fit are clear to AI

• Include comparison points because AI tools are often asked for comparisons

• Although mentioning limitations and cons might seem like it will have a negative impact, it actually can mean lesser returns

• Create FAQs and brand policy pages that AI can refer to easily 

• Write the content in plain language, avoiding complex terms

4. Build a commerce infrastructure that can support AI-led transactions

AI tells customers what it finds in your store. Hence, for example, if AI tells shoppers you can deliver a particular product within a specific time, if your brand does not deliver, it shows badly on your brand. Here’s a agentic commerce checklist to follow for adopting agentic commerce:

• Check your readiness by ensuring real-time inventory, accurate pricing, product availability, shipping information, returns and refunds, etc. 

• Ensure inventory sync if you have multiple locations and warehouses

• Price consistency across the site and other channels

• Place a test order through an AI channel and notice if there are any gaps from discovery through to post-purchase experience

What agentic commerce means for Shopify brands

Here are some facts, numbers, and predictions of what adopting agentic commerce could mean for your Shopify brand:

Your Shopify product pages are not the only discovery touchpoint

With 64% of shoppers using AI to find products (according to a study by Ryder), your website is no longer the only discovery touchpoint. What does this mean for Shopify stores?

AI forms opinions and accordingly narrows down search, hence, your product pages now become a verification step. Hence, your page merely needs to confirm what AI has said, not persuade the shopper to buy. 

Product data turns into a critical growth factor

Your products turning up on AI channels depends on how well-structured, clear, complete, and trustworthy your product data is. If there’s a gap in your product information, for instance, pricing, availability, delivery, etc., on your website or other channels, it will impact your AI search.

Prepare for agentic commerce but do not assume it affects every purchase

Agentic commerce is growing, but it still hasn’t reached a place where AI agents are making all purchases. While AI is influencing what customers are seeing, the information they’re reading, it is not completing all transactions. Checkout models are still shifting and evolving. 

Wrapping up: How prepared is your Shopify brand for agentic commerce?

AI in eCommerce is changing the way people shop, and hence, Shopify brands are adapting to the shifts. And agentic commerce continues to evolve.

Shopify brands that want to integrate agentic, have to think beyond integrating AI tools. Because agentic commerce requires strategic intervention - from product data to improving discoverability to ensuring smooth operations. For this, brands might need expert assessment and need to hire external Shopify agencies that understand agentic.

If you’re a Shopify or Shopify Plus brand that wants to adopt agentic commerce and the power of AI, reach out to XgenTech.