What Your Own Buying Decisions Can Teach You About Customer Discovery

Look at one recent purchase and trace how you found the options, what you researched and why you chose. That can help you spot questions your own customers may need answered. I think the people who immediately understand what I'm building at Protocol Text are already noticing those changes in their own buying decisions.

Start with the decisions you've noticed changing

Looking at my own behavior, I have AI doing a lot of research for me. I'm also watching how people interact with the internet. Seeing that happen in real time is what changed my opinion about where this is going.

My observation is that a familiar brand can become a starting point while research leads someone toward more specific, “hyper-targeted options.” By that, I mean choices that fit a particular combination of needs, preferences and constraints.

That's my experience and outlook. It doesn't tell us how often your customers use AI or where most of your work comes from. But it gives you a useful place to start: examine a decision you can actually remember, rather than assume everyone follows the same path.

Reconstruct one purchase from recommendation to decision

Choose something you bought recently where you compared options. Write down what happened in order. If you still have the messages, searches or notes, use them instead of relying entirely on memory.

Here's a hypothetical example. Imagine your washing machine stops working, and a neighbor recommends a repair company. You now have a name. You still need to know whether that company services your machine and can come at a workable time.

You might search the company website or ask an AI tool to help compare repair options. That introduces questions you hadn't considered, such as whether the provider works on your particular model and how the diagnostic visit is handled. Any answer that affects your decision still needs checking with the provider.

Another company might explain those details clearly while the recommended company leaves them unanswered. You haven't necessarily stopped trusting your neighbor. You have more information to weigh.

For your own purchase, record:

• Discovery: Where did the first name or option come from?
• Questions: What did you need to know before taking it seriously?
• Comparison: What made an option fit or fall off the list?
• Decision: What finally gave you enough confidence to act?

Include anything unresolved. Maybe you called because the website didn't answer an important question. Maybe you chose despite a gap because someone you trusted had direct experience.

Separate getting recommended from being ready to choose

A recommendation puts a business in consideration. The information someone finds afterward helps them decide whether it fits.

In the hypothetical repair example, a name alone doesn't explain model compatibility or the visit process. A provider could be a good fit and still leave the person unable to tell. Clear information gives that person something concrete to evaluate.

This is where I'd be careful with the exercise. Your purchase is one example, shaped by your urgency, budget, habits and access to information. Use it to generate questions, then compare those questions with actual customer conversations. Don't turn one AI response or personal preference into a claim about your whole market.

Turn those questions into a service-information audit

Now look at your business information through the same sequence. Here's a practical audit you can try, rather than a claim about how every customer buys:

• Fit: Can someone tell which services you offer and which situations you can help with?
• Exclusions: Have you explained relevant limits, including work you don't take on?
• Process and evidence: Can someone understand what happens after contacting you and see relevant examples you have permission to share?
• Uncertainty: Which answers require an inspection, consultation or more details from the customer?

Start with a question that could rule your business in or out. Put an accurate answer where someone researching that service can find it. If the answer depends on something, explain what it depends on. You don't need to pretend every decision can happen without a conversation.

More specific matching is the direction I believe in

I think there's a future where businesses can share their values, consumers can share theirs, and something acts as a matchmaker between them. In the interview, I used shoes as an example: someone wanting handmade shoes made by a Christian, without child labor, at a certain price point.

That's a belief about where matching could go, not a promise that AI can verify every claim or produce a perfect recommendation today. For service owners, the practical point is to explain the real details that distinguish a good fit. Part of our job at Protocol Text is explaining that direction plainly enough for people to understand what they can do with it.

FAQs

Does AI-assisted research replace word of mouth?

I wouldn't assume that. Someone may hear your name from a neighbor, then use search or AI to investigate further. Make useful, accurate information available for that follow-up, so the person can check whether the recommendation fits the work they need.

Should I write my website for a machine instead of a person?

Write clear, accurate explanations that people can evaluate. Describe the service, relevant limits and what happens next in familiar language. There's no special format I can promise will control recommendations. The information should still help someone who reads it directly and wants to make a decision.

Does one search result show how most customers choose?

No. It shows what appeared in one search, with a particular question and context. Treat it as an observation that may suggest something to investigate. It doesn't establish market-wide behavior, show how often customers take that route or guarantee your business will appear again.

What if many of my customers discover me offline?

Use those conversations to learn what people ask before choosing you. Then make consistent answers available when they follow up online or contact your business. You can improve that follow-up without assuming online discovery has replaced the referrals, relationships or local encounters that brought them to you.