The flyer story that changed my sense of effort

You’ve tested a marketing idea when you can explain what offer reached which people, how they could respond, and what happened within a planned limit. A tiring day tells you how much effort you spent. By itself, it doesn’t tell you whether the idea got a fair test.

By Eric Yim, Protocol Text, a marketing services business based in Lincoln, Nebraska.

The remembered story: 500 flyers versus 150,000

When I think about the amount of work that it takes to be successful, I think about a story I remember Alex Hormozi telling about selling gym memberships. I’m retelling it from memory, so these are remembered counts, not independently verified campaign results.

He had a mentor who told him to put out flyers. He made a design he thought was super awesome, put together an offer, and printed about 500. Then he spent a whole afternoon distributing them. It was hot. He was sweaty. He came back expecting the offer to crush.

A day went by with nothing. Then two days. He waited a whole week. No calls. Nobody came in.

He called his mentor, frustrated that the flyer advice hadn’t worked. The mentor asked about the offer, which I remember as a four-week gym offer, then asked how many flyers he’d distributed. Alex was proud of the 500. It had taken his whole afternoon.

In the story, the mentor started laughing. Their comparison was 5,000 flyers a day for 30 days just to test one offer. That’s 150,000 flyers.

That contrast changed my sense of effort. What felt substantial to one person was much smaller than another operator’s test. It takes a lot of volume, time, and effort that people may not understand. But those remembered numbers don’t establish a requirement for your business, and more volume doesn’t ensure success.

Separate the work you felt from the evidence you collected

Printing, walking, and waiting all feel like work because they are. The decision is harder: did enough of the intended audience encounter an understandable offer through a working response path?

A distribution count tells you what went out. It doesn’t prove that people noticed it, needed it, or understood what to do next. No calls is an observation. It doesn’t explain the cause on its own.

I’d also be careful about copying the scale of that story. In the interview, I talked about large brands using awareness marketing because people already know them. A small provider trying to fill available work has a different decision to make. There are different strategies for different companies at different stages.

Build one small test you can actually review

Here’s a hypothetical example, not a client campaign: an independent cleaner wants to test an offer for a one-time home cleaning in one service area.

I’d propose writing down the test before distributing anything:

• Offer: Describe what the cleaning includes and any important limits. Don’t promise work the business can’t deliver.
• Audience: Choose one defined area the cleaner can serve. Record where distribution actually happens.
• Response: Ask people to request availability through one identifiable contact path. Check that it works before starting.
• Distribution: Use the same flyer, offer, and contact path across the planned deliveries. Record quantities and dates, separating planned distribution from completed distribution.
• Affordable limit: Set a maximum spend and number of working hours the business can afford without depending on new bookings.
• Review point: Choose a date that leaves a stated response window after the final delivery. Decide beforehand what would justify another test.

Keep a simple log of inquiries, service fit, and bookings. An inquiry outside the service area still counts as a response, but it doesn’t count as a suitable booking. Those distinctions matter when deciding whether the problem is getting attention or turning that attention into work.

Holding the main details steady makes the result easier to interpret. Changing the offer, audience, and contact method halfway through leaves you guessing about which version produced the response.

Decide what the result supports before doing more

This test could show that the particular offer and distribution produced attributable inquiries or bookings within the recorded window. It wouldn’t establish that flyers work everywhere, that another neighborhood would respond similarly, or that a larger campaign would perform the same way.

If nothing comes back, inspect the contact path first. Then compare actual distribution with the plan, check whether the audience fits the service, and read the offer for unclear scope or next steps. A broken form needs fixing before more distribution.

If suitable inquiries arrive but don’t become bookings, look at what happened after contact. If bookings arrive, check the delivery capacity and economics before increasing the test. None of these results automatically calls for more volume.

Let feedback arrive before you perfect the setup

I’ve said that optimizing too much on the product has hurt me. Trying to make something perfect before talking to people can postpone validation. A test needs a clear, accurate offer and reliable tracking, but an elaborate setup can become another delay.

At the review point, choose between correcting a concrete problem, testing one change, repeating cautiously, or stopping. Base that choice on what you observed and can afford.

Questions about test limits and tracking

When should a test stop before its planned review date?

Pause if the offer is inaccurate, the response path breaks, the budget limit is reached, or the business can’t fulfill the offer. Correct the concrete issue before continuing. Record when the problem occurred so you don’t treat the affected period as a clean test.

Do repeated views from the same person count the same as reaching new people?

They answer different questions. Repeated views measure additional exposure, while reaching new people broadens the audience. Record what you can actually measure. If a platform reports total views without identifying unique viewers, don’t relabel those views as the number of different people reached.

What if I cannot tell where inquiries came from?

Add a consistent source question when someone contacts you, or use an identifiable response path for the test. People may not remember accurately, so keep uncertain answers marked as uncertain. Don’t assign every new inquiry to the experiment simply because it arrived during the same period.

What if I have room for only a few additional customers?

Design the test around that capacity. Limit distribution and spending, keep availability accurate, and decide when to pause before you take on work you can’t deliver. The remembered high-volume example illustrates a difference in scale; it doesn’t dictate a capacity-constrained service business’s plan.