Why Do You Need Synthetic Users

It’s Monday morning. Your product team is waiting on feedback for a new packaging design before production. The creative was finalized two weeks ago, recruiting started 10 days ago, and the study won’t field for another week—results won’t arrive until the week after.

Meanwhile, your competitor just launched a similar product. Every day of delay costs money.

Sound familiar?

For most market researchers, this scenario is all too real. Stakeholders want insights faster, budgets are tighter, and business moves quicker—while traditional research methods remain limited by time, cost, and scale.

This is where synthetic users move from interesting concept to practical solution.

Problem 1: Speed—The Waiting Game

The traditional bottleneck: Market research operates on a timeline measured in weeks and months, not days.

• Recruiting quality participants: 1-3 weeks
• Fielding the study: 1-2 weeks
• Analysis and reporting: 3-5 days minimum

That's a best-case scenario of 3-4 weeks from concept to insight. In practice? A comprehensive study often takes 6-8 weeks.

A Research by Sprig shows that teams using continuous discovery methods report 2x faster release cycles and 30% higher feature adoption compared to traditional quarterly research approaches.

When research can't keep pace with decision-making, companies either move forward without insights (risky) or slow down to wait for data (costly).

How synthetic users solve this:

Synthetic users compress weeks into hours. You can:

• Test a concept with 500 simulated consumers overnight
• Iterate based on feedback by Tuesday morning
• Re-test your refined version by Wednesday
• Validate top performers with a targeted human study by end-of-week

The speed advantage isn't just about convenience—it's about making research feasible for decisions that couldn't wait before.

Problem 2: Cost—The Budget Barrier

The traditional constraint: Quality research is expensive, forcing teams to ration insights.

Industry benchmarks show:

• Online surveys: $5,000-$15,000+ per study
• Focus groups: $7,000-$20,000+ per group
• In-person surveys: $20,000-$50,000+
• Participant recruitment: $100-$300 per qualified recruit

A 2024 McKinsey survey of 100+ marketing decision-makers at large CPG and retail brands found that 34% cited lack of desired budgets as their top barrier, while 26% of market researchers report budget limitations as their primary obstacle.

The consequence? Teams test only high-stakes initiatives, leaving smaller bets and early ideas unvalidated. Innovation becomes conservative because experimentation is too expensive.

How synthetic users solve this:

Synthetic users dramatically reduce the marginal cost of each additional test.

Instead of choosing between testing 3 concepts at $15K each ($45K total), you can:

• Test 10 concepts with synthetic users (days, not weeks, at a fraction of the cost)
• Identify the top 3 performers
• Invest your $45K budget into a robust validation study of those finalists with real humans

When EY tested synthetic users against their annual brand survey, they got 95% correlation with real survey results at "a fraction of the cost." The math is compelling: same quality of directional insights, dramatically lower investment.

Problem 3: Iteration Blockage—The Linear Research Trap

The traditional constraint: Research is sequential, not iterative.

Here's the painful truth about traditional research: Every iteration requires starting the entire cycle over.

• Concept Test 1 → Wait 4 weeks → Learn it's not quite right
• Refine concept → Concept Test 2 → Wait another 4 weeks
• Three iterations = 12 weeks before you have a validated winner

Most teams don't have 12 weeks. So they do one test, make their best guess at improvements, and launch—hoping they got it right.

How synthetic users solve this:

Synthetic users make iteration not just possible, but practical.

You can run test-learn-iterate cycles multiple times per week instead of once per month:

Traditional:

Test → Wait 4 weeks → Learn → Launch

With Synthetic Users:

Test → Learn overnight → Refine → Test again → Learn → Refine → Test again →
Validate with humans → Launch

This isn't just faster—it's qualitatively different. It transforms research from a one-time checkpoint into a continuous feedback loop.

Problem 4: Access to Specific Segments—The Recruitment Challenge

The traditional constraint: Niche audiences are expensive and time-consuming to recruit.

Need to understand how "frequent organic snack buyers in urban areas who prioritize sustainability" would react to your packaging? Good luck.

The more specific your target segment, the more expensive and time-consuming recruitment becomes. And if you need insights across multiple niche segments? The costs multiply quickly.

How synthetic users solve this:

Synthetic users can be configured to represent any demographic or psychographic profile:

• 200 Gen-Z urban shoppers
• 300 suburban parents who buy premium grocery brands
• 150 health-conscious millennials with gluten sensitivities

You can test the same concept across different segments simultaneously, understanding how reactions vary by audience—without recruiting a single participant.

[Diagram placeholder: Traditional research funnel (10 concepts → budget allows testing 2) vs. Synthetic user approach (10 concepts → test all → validate top 3)]

Beyond Research Teams: Expanding Access to Insights

Here's where synthetic users become even more interesting: They don't just make researchers faster—they democratize access to consumer insights across your organization.

Marketing teams can pre-test email subject lines, ad copy, or social media messaging before spending media budgets.

Sales teams can validate pitch decks and value propositions with simulated customer personas.

Product teams can get early directional feedback on feature concepts without waiting for research bandwidth.

This doesn't replace your research team's expertise—it augments it by handling lower-stakes questions, freeing your team to focus on strategic, high-impact studies.

The "Virtual User Base" Concept

Think of synthetic users not as a one-time tool, but as an on-demand, reusable research asset.

Imagine building a library of synthetic personas representing your key customer segments:

• "Sarah" - 34-year-old urban professional, shops at Whole Foods, values sustainability
• "Mike" - 52-year-old suburban dad, price-conscious, buys in bulk at Costco
• "Priya" - 28-year-old health enthusiast, early adopter, shops online frequently

These personas can be "consulted" whenever you need quick directional feedback—like having a focus group on standby 24/7.

As you validate their responses against real studies over time, they become increasingly calibrated to your specific market and product category.

💡 The Researcher's Advantage

Synthetic users don't replace your judgment—they amplify it. You spend less time waiting for data and more time interpreting insights, crafting strategy, and guiding stakeholders toward smarter decisions.

📌 Key Takeaways

✅ Speed: Compress weeks of research into hours, enabling faster decision-making and iterative testing

✅ Cost: Dramatically reduce the marginal cost of testing, making comprehensive exploration financially feasible

✅ Iteration: Transform research from a linear, one-shot process into a continuous feedback loop

✅ Segment access: Test across multiple niche audiences simultaneously without recruitment bottlenecks

✅ Democratization: Expand research capabilities beyond the research team to product, marketing, and sales

✅ Strategic focus: Free researchers from data-waiting to focus on interpretation and strategic guidance

➡️ What's Next?

Now that you understand the problems synthetic users solve, you're probably wondering: How do they actually work? What's happening under the hood?

In Chapter 4: How Do Synthetic Users Actually Work?, we'll demystify the technology—giving you a clear mental model of how synthetic users simulate consumer behavior without getting overly technical.