Synthetic Buyers: PwC and Bain on a New Tool for E-Commerce

A new approach to studying customers is taking shape in the e-commerce industry: synthetic customers (also called synthetic buyers). These are artificial intelligence models that simulate how real customers are likely to react to a price, an ad, an interface and the product itself, according to analysts at Bain and Market Logic.

How this differs from classic analytics

Classic e-commerce analytics has long been the foundation of online retail. It tracks what a shopper searched for, which product cards they clicked, where they abandoned the cart, how they responded to discounts and which products they bought together. But it has a fundamental limitation: it almost always explains what has already happened. A new price, an ad creative, a product card or a category launch is usually tested «in the field», after the budget is spent, the product is live, and the team is only starting to understand how customers respond. As Market Logic notes, at many companies customers change faster than product roadmaps and the results of classic research get updated.

What synthetic buyers are

Synthetic buyers are AI models that simulate the preferences, doubts and attitudes toward price, advertising, interface or product that real customers hold. Such models let companies test scenarios in advance: how an audience will perceive a new product, whether a specific promotion will build trust, at which step a user may abandon a purchase, and why a particular segment sees no value in an offer. PwC calls this approach an «invisible focus group».

• The term is used by analysts at Bain (synthetic customers/synthetic buyers) and PwC («invisible focus group»)
• Market Logic notes that at many companies customers change faster than product roadmaps and the results of classic research get updated
• Synthetic buyers test hypotheses before launch, covering price, advertising, product card and new category
• The approach is described as a shift from a «launch, then look at the results» model to a «check the reaction first, then decide» model

Risks and limitations

The approach does not replace real research on its own. It complements it at a stage when a full test on a live audience is not yet possible or is too expensive. A synthetic buyer simulates a likely reaction based on accumulated data about real customer behavior, so the quality of the forecast depends directly on how representative and fresh that data is.

That is why Bain and Market Logic describe the approach as a way to test hypotheses faster and more cheaply in the early stages, not as a full replacement for traditional surveys, usability tests and pilot launches. NN Group, which specializes in UX research, uses a similar term, «synthetic users». This shows that the idea of modeling user reactions through AI is being discussed in several adjacent disciplines at once, not only in e-commerce.

What this means

Synthetic buyers are not just a new kind of analytics. They are a new way to work with uncertainty in a market that changes faster than classic research can keep up with. For e-commerce, this means being able to test a strategy before entering the market, not only through surveys and pilots but also through a simulation of buyer behavior based on data, rather than only analyzing the results of sales that have already happened.

FAQ

What are synthetic buyers?

They are artificial intelligence models that simulate the likely reaction of real customers, including their preferences, doubts and attitudes toward price, advertising, interface or product, in order to test a hypothesis before market launch.

Who introduced the term «invisible focus group»?

PwC analysts call the synthetic buyer approach an «invisible focus group» in their material on the use of AI in retail.