Synthetic Customers: Accelerating Innovation With AI

In markets where success hinges on getting the next product launch right, companies face a paradox: They must innovate rapidly while deeply understanding their customers, yet, traditional research and product testing are often too slow, expensive, or narrowly focused to keep up. This is where synthetic customers are beginning to change the game.

Built with generative AI and machine learning, synthetic customers are AI-generated proxies that emulate human preferences and decision-making. They simulate how real customers might respond to a new product feature, pricing shift, or marketing campaign, enabling companies to test and iterate at a speed and scale previously unimaginable.

At Bain, we’re seeing firsthand how synthetic customers, when layered onto real customer feedback, uncover insights that sharpen decision-making while significantly reducing research costs and timelines. Tests that once took months and large budgets can now be completed in weeks — or even days — without sacrificing rigor.

Synthetic Customers in Action

A major telecom provider recently used synthetic customers to explore underserved, value-focused segments while maintaining its premium positioning. By combining traditional customer research with synthetic testing, the company evaluated hundreds of combinations of features, price points, and promotional strategies. The result: an optimized launch plan delivered with greater confidence and at lower cost. As new data and signals were integrated, the models improved in accuracy, aligning more closely with real-world outcomes.

Beyond product and pricing strategy, synthetic customers are transforming frontline operations. Sales and service teams can train with synthetic personas that mimic real objections and behaviors, building the agility to meet evolving customer needs.

Linking Synthetic Customers to Customer Advocacy  With NPS

One of the most promising use cases is predictive Net Promoter Score (NPS) modeling. As the creators and stewards of NPS, we see synthetic customers as a natural extension of how organizations can better understand what drives customer advocacy.

Synthetic models can simulate how proposed changes to a product, service, or experience might affect customer sentiment, enabling companies to forecast NPS before implementing changes at scale. For instance, a retailer considering a new checkout experience can predict how different segments will respond, estimating shifts in promoters, passives, and detractors before rollout.

This ability to test “what if” scenarios helps organizations anticipate reactions and avoid costly missteps. It also reinforces a focus on the drivers of loyalty and advocacy, which is critical in an era when every point of NPS improvement can translate into meaningful revenue and retention gains.

Where to Begin

Synthetic customers are a powerful capability, but they’re not a substitute for the real voices and emotions of customers. Success depends on a disciplined approach:

Start with clear objectives, whether forecasting NPS, testing a product concept, or refining campaign messaging.

Invest in high-quality proprietary data — the insights are only as good as the data and model design.

Augment, don’t replace traditional research, especially where emotional nuance matters.

Begin with low-stakes use cases — validate and refine before applying models to critical decisions.

As organizations gain confidence, they unlock the potential to accelerate innovation without sacrificing customer centricity. Design teams can gather feedback at every step, marketers can optimize campaigns before launch, and finance teams can model revenue scenarios with greater precision.

Ultimately, companies that embrace synthetic customers thoughtfully will gain an edge: deeper customer understanding, faster time to market, and more resilient innovation pipelines. And by linking synthetic testing to NPS, they ensure speed doesn’t come at the expense of loyalty.

In a world where expectations evolve rapidly, the ability to learn faster and act with greater confidence will distinguish leaders from the rest. Synthetic customers are not just a technological leap, they reflect a mindset of continuous learning and experimentation, grounded in what customers truly value.

And that’s a future worth building.