The Strategy Professional's Guide to Accelerated Discovery

When I was leading product at a design tools company, we had a saying: "The best product decisions are made closest to the user." It sounds obvious, but executing on it is surprisingly hard.

The problem isn't that product managers don't value user research—we do. The problem is that traditional research takes so long that by the time insights arrive, the product has already moved on. I can't count how many times I've received beautifully crafted research reports for features we shipped three months ago.

This is why I got obsessed with finding ways to make discovery continuous rather than episodic. And it's why I eventually became convinced that synthetic users are one of the most significant developments in product research I've seen in my career.

The Discovery Speed Problem

Let me paint a picture that will be familiar to any PM:

You're in a planning meeting. A stakeholder raises a question about user behavior. Everyone agrees it's important to understand. Someone suggests user research.

Then reality sets in:

• Recruiting participants will take 2-3 weeks
• Scheduling interviews adds another week
• Analysis and synthesis takes 2 more weeks
• By the time you have insights, you've already committed to a roadmap

So instead, you make your best guess, ship something, and hope the metrics tell you if you were right. This is how most product decisions actually get made. We just don't like to admit it.

How I Use Simulated Buyers in Discovery

At SocioLogic, I've developed a workflow that uses synthetic users to dramatically accelerate the discovery loop. Here's how it works in practice:

Phase 1: Rapid Hypothesis Generation

Before any planning meeting, I spend 30 minutes "interviewing" synthetic users about the problem space. I'm not looking for definitive answers—I'm looking for hypotheses worth exploring.

For example, when exploring a new feature direction, I might ask synthetic personas:

• "Walk me through the last time you faced [problem]. What did you try?"
• "What would need to be true for you to switch to a new solution?"
• "What do you wish [competitor] did differently?"

In 30 minutes, I can generate 10-15 hypotheses that would have taken weeks to uncover through traditional research. Not all of them will be right, but they give my team concrete starting points.

Phase 2: Solution Exploration

Once we have solution concepts, I use synthetic users to stress-test them. I describe the proposed solution and ask:

• "What's your initial reaction?"
• "What concerns would you have?"
• "How does this compare to what you're doing today?"
• "What would make this a must-have vs. nice-to-have?"

This isn't validation—it's exploration. I'm trying to understand the landscape of reactions we might encounter, identify potential objections, and refine our approach.

Phase 3: Message and Positioning Testing

This is where synthetic users really shine. I can test dozens of positioning variants in a single afternoon.

At a previous company, testing three different product descriptions would require recruiting three different user panels to avoid bias. That's expensive and slow. With synthetic users, I can test 20 variants in two hours and identify which directions are worth pursuing with real users.

Phase 4: Validation with Real Users

And here's the crucial point: synthetic user research doesn't replace real user research—it makes it more effective.

Instead of spending our real-user research budget on exploration, we now use it for validation. We arrive at user interviews with better hypotheses, better questions, and better prototypes. The research we do is more focused and more valuable.

Practical Tips from My Workflow

After months of using this approach, I've developed some best practices:

1. Create diverse persona sets: Don't just create your ideal customer. Include skeptics, competitors' customers, and edge cases.
2. Ask open-ended questions first: Before showing solutions, understand the problem from the persona's perspective.
3. Look for surprises: The most valuable insights are often the unexpected ones. If a synthetic user raises an objection you hadn't considered, explore it.
4. Document everything: I keep a running log of synthetic user "quotes" that inform our product decisions. They're useful for stakeholder communication too.
5. Triangulate with data: Synthetic user insights should align with your behavioral data. If they contradict, investigate why.

The Mindset Shift

The biggest change for me wasn't tactical—it was philosophical. Discovery is no longer a phase of product development. It's a continuous activity that happens throughout the product lifecycle.

When a question comes up in a meeting, my default response has changed from "let's add that to the research backlog" to "let me explore that quickly and report back."

This shift has made our team faster, but more importantly, it's made us more confident. We're not guessing anymore—we're making informed bets based on systematic exploration. And that's what great product management is all about.