High-value Retail
Buyers know more
Nishit Mehta on how to price, sell, and build for AI-informed shoppers in high-ticket retail.
Having become CEO of my family’s diamond business in Hong Kong at 19 and now overseeing 112 jewelry stores across the US, both jobs ran on the same assumption: the salesperson always knew more than the buyer about cost, quality, and fair price.
Sales training, commission plans, and markups all grew out of that gap. AI search has now closed much of it, in jewelry and in every other high-ticket category, and any retail budget still based on it deserves a hard second look.
A shopper walking into a car dealership, a luxury boutique, or an appliance store today has often already had a long chat with an AI assistant. It has compared global competitors, checked wholesale and commodity prices, and scraped Reddit threads for known defects. By the time they meet a salesperson, the old ‘let me walk you through the options’ script feels like a formality.
The knowledge gap is closing
In 1970, George Akerlof wrote about markets where sellers know more than buyers, using used cars as his example, work cited when he shared the 2001 Nobel Prize in economics.
AI has narrowed that gap sharply, and the ‘educator’ sales script, where the associate explains the basics, is now obsolete. My advice: assume the customer already knows your margins. Train floor teams to confirm and sharpen the research shoppers already did. Price as if a competitor’s quote is open on the customer’s phone, because often it is. Prices that hold up to a quick fact-check close deals.
The content-for-traffic deal is broken
For about 15 years, retail SEO ran on a simple trade. You published a buying guide, ‘How to Choose a Mattress’ or ‘How to Buy a Diamond,’ and Google sent you visitors.
AI summaries have changed the terms of that deal and pushed more searches toward what marketers call zero-click search. Pew Research Center tracked the browsing of 900 US adults in March 2025 and found Google users clicked a traditional search result in eight percent of visits when an AI summary appeared, compared with 15 percent when none did. Links inside the summary got clicked in about one percent of those visits.
The guide you paid for gets paraphrased at the top of the page, and the reader never reaches you. Retailers end up handing their expertise to AI for free.
Two competitive moats still hold: brand affinity, customers who search for you by name; and proprietary utility: tools whose output depends on your data and the shopper’s own inputs, which an AI can’t rebuild from text it found elsewhere.
Digital utility is the new retail counter
La Joya has built small interactive tools like the Holistic Budget Quiz, which starts from a buyer’s real income and fixed costs, and the Future Value Calculator to show what the money a buyer keeps by going lab-grown could grow into if it were invested over five years.
Ask an AI assistant a complex, personal financial question, like how much to spend on a ring on your salary, and generic text can’t answer it well. The assistant acts as an agent and points the person to a calculator that can, sending over the qualified visitor a written guide once brought in.
Picture a furniture retailer offering a room-fit planner, a car dealer modeling ownership costs for one buyer’s situation, an electronics store estimating energy savings from a household’s actual bills, or a brokerage mapping commute times and prices by neighborhood. Each answer changes with the person, and an AI can’t replicate that experience, so it is more likely to link to you.
These tools also capture intent. A shopper who willingly shares a budget, a timeline, and a top priority is telling you where they stand. Every retail sector now must make the same move and start building interactive, data-capturing utilities.
What this shift means for retail leaders
- Information asymmetry no longer protects margins in high-consideration retail, because shoppers arrive with AI-assisted price and product research
- Informational content such as buying guides earns fewer clicks, since AI search summaries answer the question directly on the results page
- Brand affinity and proprietary interactive tools are the two retail assets AI search cannot easily replace
- High-ticket sales teams now earn their value by verifying and refining what customers have already learned
- Automotive, real estate, furniture, electronics, and fine jewelry can all apply the same model by turning their expertise into interactive tools
Where high-ticket retail goes from here
A growing share of customers now learn what they are buying from an AI assistant before they reach the store counter, so the retailers who do well will be the ones with transparent prices and tools that help a shopper decide. After three decades in jewelry, I welcome that, because it rewards businesses that were already open with customers.
Nishit Mehta is the founder of La Joya, an ethical fine jewelry brand specializing in heirloom-quality, IGI-certified lab-grown diamond jewelry. A third-generation diamond expert with over 30 years of global experience, he has served as CEO of Diamart Ltd in Hong Kong, senior leader at Gitanjali Gems Limited overseeing more than 100 US retail stores, and founder of Azure Ltd, a direct-to-retailer supplier across Europe, the Middle East, and America. His mission: to democratize luxury without compromise.
Website lajoyajewelry.com | Instagram: @lajoyadiamonds
