From Search to Synthesis: The Changing Customer Journey in the AI Era

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For years, ecommerce ran on a simple system. 

Brands paid for attention online, shoppers clicked links and sponsored ads, and if it was all done right, a purchase took place. The grey area between that search bar and checkout page meant marketers could step in with SEO, optimised PDP pages, and targeted ads to engage the right people at the right time.

Today, that system of shopping is shifting — fast.

Consumers are still buying products online, they’re just changing the ways in which they’re doing it, increasingly relying on AI to help them find, curate, and purchase products all within their preferred LLM apps.

During her presentation at eTail West, Amera Khalil, Director of Sales at Commerce taught us how quickly this shift is happening. 

“The ability to compare is really important for the consumer, and if you start giving them information that is not relevant and it’s not the TL;DR, they’re not going to listen.” — Amera Khalil, Director of Sales, Commerce

Here are some of the key takeaways from the session that brands can use to elevate their ecommerce presence in the AI era. 

From search, click, browse, buy to ask, get curated answer, buy

The shift from keywords to natural language changes more than ad strategy. It changes infrastructure.

“The search bar is dead.” — Amera Khalil, Director of Sales, Commerce

Her statement may seem dramatic to hear if you’ve invested years of time and resources into perfecting your SEO strategy. But think of the shift happening online in terms of language.

Search hasn’t disappeared. It’s evolved. Instead of typing a few keywords into a search bar, shoppers are now telling AI tools exactly what they’re looking for in full sentences. They share context, preferences, and specifics, expecting AI-driven shopping agents to understand the nuance and serve up curated options that fit.

“Customers are looking for some different things and what they’re looking for is context, not just keywords.” — Amera Khalil, Director of Sales, Commerce

That shift from shorthand keywords to full-sentence intent changes everything. This isn’t a cosmetic update to search behaviour. It requires product data that goes beyond colour and size — data rich enough in context, nuance, and relevance for an LLM to interpret, prioritise, and present with confidence.

The traditional four-step funnel was predictable. Search, browse, PDP, and checkout. Rinse and repeat. Waste time poring over reviews. Close tabs and abandon carts when information reaches a point of overload. This is how AI shopping changes things for the better.

Consumers have moved from sifting to synthesising. They expect AI to summarise the trade-offs and present the best options instantly. If your product data cannot support that synthesis, it does not surface.

For marketers, this reframes the investment in data. Comprehensive feeds are table stakes. The competitive edge lies in whether your data is intelligent enough to win inside an AI’s recommendation layer.

AI shopping is a behavioural shift, not a channel launch

“I hear many people come to me and say, ‘Amera, it’s just a channel.’ It’s not just a channel. This is a change in your customer behaviour.” — Amera Khalil, Director of Sales, Commerce

It is tempting to treat AI like another channel to plug into the stack, alongside marketplaces and social commerce. But that mindset misses the bigger shift.

This is a change in customer behaviour.

Yes, OpenAI belongs alongside Google, Meta, and TikTok Shop. But presence alone doesn’t create performance. 

Brands need to elevate structured product data into something smarter — inventory synced in real time, reviews and creator content integrated, social signals distilled into context an LLM can interpret instantly. That’s the move from data management to intelligence orchestration.

Khalil mentioned a powerful question that client Shirley Gao, Chief Digital and Information Officer at PacSun, asked her: “How do I make my data intelligent?” 

The real-world answer required multiple systems working together, including BigCommerce as the platform, Feedonomics for product feed syndication, and additional partners, to enable on-site checkout directly within Perplexity.

When consumers begin their purchase journey inside AI applications, the traditional signals marketers rely on (including traffic, on-site engagement, and assisted conversions) lose visibility. Demand still exists. It simply converts elsewhere.

Forward-thinking brands are restructuring their data strategies accordingly. That means:

• Enriching product information beyond basic attributes

• Syncing real-time inventory and pricing across systems

• Ensuring payment and checkout capabilities can operate within AI environments

• Consolidating reviews, social proof, and content into structured, accessible formats

The evolution is from data management to intelligence orchestration.

Checkout inside AI is already happening

To show this shopping experience in action, Khalil demonstrated a live example, searching for PacSun jeans on Perplexity. 

In seconds she started receiving intelligent product recommendations, chose a size, picked a payment method, made the purchase, and received a confirmation email without ever leaving the Perplexity app. The experience looked and felt like shopping at a PacSun storefront, yet she never visited the brand’s website at all.

“Now Perplexity does it for me, it takes like three minutes.” — Amera Khalil, Director of Sales, Commerce

Supporting this new shopping experience requires tight coordination across ecommerce platforms, feed management systems, payments, and inventory infrastructure. Real-time accuracy becomes mission-critical. A mismatch in availability or pricing breaks trust instantly.

Khalil estimates that 20 – 50% of traditional website traffic could migrate to AI-assisted purchase paths in the coming years. At the same time, projections suggest AI-influenced consumer spend could approach $750 billion by 2028.

While the exact figures may fluctuate, the direction will not.

The final word

Khalil’s message to the room was simple: brands have the opportunity to transform the purchase journey — but only if they are willing to rethink the traditional funnel, shifting from fragmented discovery to more intentional, AI-aligned experiences.

Strategies built for keyword-driven discovery must adapt to conversational commerce. Measurement frameworks centered on sessions and pageviews need augmentation with AI-attributed conversions. Feed management designed for search and social must evolve to support AI-native transactions, as well.

Brands willing to invest in intelligent product data, with the help of platforms like BigCommerce, can enable commerce wherever customers choose to transact, ensuring they will not lose customers.

They’ll just meet them where they moved.

Watch the TL;DR version of this conversation.