Twelve Leads Can't Tell You Anything

Years back, Groupon exploded across a lot of martial arts schools at the same time. Same offer, same deal, same kind of buyer, dropped into very different operations.

Schools that already closed 80 percent or better on their normal leads closed great on Groupon too. Schools whose normal close rate sat around 50 percent, which some owners think is fine and it isn't, closed those exact same Groupon leads at very low rates.

And complained incessantly about how terrible the Groupon leads were.

Same lead. Same offer. Opposite outcomes. The variable was never the lead!

The Lead Gets Blamed First

When something underperforms, the input is the easiest thing to blame and the least likely to be responsible. We're worse at this than we think: people explain outcomes by the qualities of the thing in front of them and reliably underweight the situation it landed in (Ross, 1977).

The lead is the thing in front of you. Your operation is the situation you dropped it into, and that's the one nobody wants to look at.

I ran schools for years before I trusted the number more than my gut. My gut was a liar with good intentions. It counted the leads it liked and forgot the ones it didn't, then acted surprised when the math never added up.

Twelve Leads Is Not a Sample

An owner gets twelve leads in a month. They spend the month tuning the follow-up sequence on those twelve. Rewriting the phone script. Testing a new booking page. Analyzing which of the twelve went cold and why.

Twelve leads can't tell you which source works. They can't tell you which rate is broken. They can't tell you whether the month was a fluke or a trend, and it definitely can't tell you whether the new script beat the old one.

We are extremely bad at knowing this about ourselves. Tversky and Kahneman named it the belief in the law of small numbers: people expect a small sample to look like the population it came from, and they draw confident conclusions from runs far too short to support them (Tversky & Kahneman, 1971). It isn't innumeracy. Their subjects were trained researchers. The intuition survives knowing better.

The number that fixes this isn't a conversion rate. It's volume.

In my schools the working threshold is 100 to 200 leads a month. Below that you're reading noise and polishing a trickle. Above it, patterns hold still long enough to mean something, and a single rained-out event stops moving your whole month.

That's the martial arts number, from martial arts schools, and yours will be different. The principle is the same everywhere: you need enough activity that one bad week can't move the number. Until you're there, the job is volume. Not optimization. Volume!

Owners run this backwards and I understand why. Optimizing feels like skill, and building volume feels like admitting you don't have enough yet.

"Qualified" Is a Word That Won't Hold Still

You've been editing the number too.

Watch what "qualified" actually means the moment an owner says it out loud.

Qualified means I think this one will buy. Qualified means I liked them on the phone. Qualified means they didn't give me a weird feeling. Qualified means quota was up this week, so I feel generous. Qualified means quota was down this week, so now I'm strict.

Five definitions. And the same person runs three of them in a single week.

A number you redefine by mood can't be tracked over time, and a number you can't track over time can't tell you ONE useful thing. The second you sort leads into real and not-real in your head, one at a time, you've handed your marketing data to your mood, and your mood changes by the hour. That substitution is well documented: faced with a hard question, people answer an easier one without noticing they swapped it (Tversky & Kahneman, 1974). Will this person buy is hard. Do I like them is easy.

As an engineer in my first career I would have loved a qualified column. Two numbers, total inquiries and the good ones. After decades on the mat I've learned it isn't helpful… it's just a place to put the leads I didn't like the look of.

Count every raised hand. Including the ones that will never buy.

Quality Is a Property of the Source, Not the Person

Jay Abraham drew this line decades ago, and it's the distinction I still use (Abraham, 2000). A suspect merely fits your demographics and geography and does nothing. A prospect raised a hand: answered an ad, filled a form, called, asked you a question at a party. A lead is a prospect.

Which means the cousin who lives 45 minutes away is a lead. The kid already training somewhere else is a lead. The caller you couldn't fully understand is a lead. All three raised a hand, and none of that is you being generous.

Quality is real. It sits one level up from the person, at the source that produced them.

A community event produces prospects with weak geographic fit, which is exactly where that 45-minute cousin came from. A search ad tied to your zip codes produces prospects who screened themselves for distance before they ever called. Both worth measuring. You measure it at the SOURCE, across dozens of hands, never by staring at one caller and deciding their fate.

Throw out the qualified column and put a list of sources where it was. Then follow each hand down the path and measure what survives each step.

In my schools that path is lead, appointment, show, first lesson, enrollment conference, enrolled, renewed. The three rates I want every school hitting: 90 percent or better from lead to booked appointment, 80 percent or better from booked to showed, 80 percent or better from showed to enrolled. Those are historical, from schools I ran, and we hit them when the process was right.

Your stages are different and your rates will be different. What transfers is having stages at all, and measuring between them, so a vague "good lead" becomes a specific "good source." A specific source is something you can act on.

Four Questions Before You Kill a Channel

One of your rates is ugly. Before you shut anything off, run it through four questions, in order, because the order IS the discipline.

A. Can I improve the rate? Did you miss steps? Is the script tight, the appointment confirmed, the reminder sent? Does the team need training, or more reps on training they already had? Most weak rates die right here, because most weak rates are a process problem wearing a marketing costume.

B. Is a lower rate simply correct for this source? Not every source should convert like every other one. A discount lead from 20 miles out will never close like someone searching your zip code, and neither one touches a referred walk-in. If a channel converts lower and still turns a profit, that's the right rate for that channel, not a failure.

C. Is it seasonal, or was it one bad day? Did you run the event and it rained? As Grand Master Oliver says, Murphy's Law is real. One data point isn't a trend. Give it another honest run before you draw a line through it.

D. Only now: is the strategy actually weak? After A, B and C, if it still doesn't produce, abandon it with a clear conscience. You earned that by measurement.

Skip straight to D and you'll throw away channels that were really a training gap, a fair rate you misjudged, or a rained-out afternoon. Quit ten things by feel and you've got nothing running and no idea why.

The Same Error With No Uniform in the Room

In an agency, it's the client who says the leads are terrible. Sometimes true. Usually the leads went into a follow-up process nobody has looked at in a year, and the agency is about to lose the account over a conversion problem it doesn't own. It's also the agency running a two-week test on a channel and declaring it dead on a handful of conversions.

For a founder selling their own product, this argument already has branding. MQL and SQL is the qualified column with a nicer name on it, and the definition drifts with the quarter exactly the way it does in a school. Tight quarter, tighter definition. And a founder with a few dozen signups a month who is A/B testing their signup page is tuning a rate they cannot read.

For a local service business, it's the estimate request from too far out, the price shopper, the caller who was never going to book. Every one of them a raised hand, and every one of them filed under "not a real lead" so it never gets counted, which means the source that produced them never gets evaluated either.

Three different businesses making the same error. Deciding from a sample that can't decide anything, then blaming whatever's easiest to see.

What You Actually Control

Two things. The marketing you choose to run, and what you do with the leads it produces.

You can't move the far cousin closer. You can't make the price shopper rich. Spending your energy there is a way of avoiding the two things that are genuinely yours.

When your best leads convert badly, the leak is your process, and fixing a process costs nothing. No extra ad spend. No extra headcount. You convert more of what you already paid for, and it's more fun to run!

The Groupon schools that did well didn't have better Groupon leads. They had a process that was already working before Groupon showed up.

Count your leads for the next 30 days. All of them, every raised hand, filed under the source that produced it, with no column for how you felt about them. If the total comes in under 100, you don't have a conversion problem to solve yet and you can stop worrying about your scripts. You have a volume problem, and that's a different month's work.

If you want to walk through what your number turns out to be, reply to this or come talk to me. The school-owner version of all this, with the full stage list, is in my article on what counts as a lead.

References

Abraham, J. (2000). Getting everything you can out of all you've got: 21 ways you can out-think, out-perform, and out-earn the competition. St. Martin's Press.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. Advances in Experimental Social Psychology, 10, 173–220. https://doi.org/10.1016/S0065-2601(08)60357-3

Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110. https://doi.org/10.1037/h0031322

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131. https://doi.org/10.1126/science.185.4157.1124