The $100 Experiment: Micro-Budgets That Teach You More Than Research

Published September 18, 2025

Why $100 beats another week of research

There’s a point where more reading just makes you confident, not correct. Ask me how I know. A tiny budget, pointed at a clear question, can teach you more in 48 hours than a month of “planning.”

$100 is small enough to be painless. Big enough to get a real signal. Also? It forces you to focus. No endless tinkering—just ship, spend, learn, adjust.

What is a $100 experiment?

Simple: a time-boxed, money-capped test designed to answer a single question.

One question: “Will people click ‘Request Demo’ for this offer?”
One channel: search, social, newsletter swap, cold email, partner blast.
One artifact: a landing page, a short video, a Typeform, a Calendly.
One metric that decides: CTR, CAC to email, demo booked, reply rate.
One stop rule: when you hit $100 or the metric is clearly yes/no.

That’s it. No dashboards, no grand theories. Just enough signal to decide the next move.

Guardrails (so you don’t set money on fire)

Write the hypothesis. If you can’t write it, you’re not ready.
Predefine success/fail. Example: “If CAC-to-email < $4 or 3+ demos book in 48 hours, proceed.”
Freeze scope. If you’re tweaking creatives every 20 minutes, it’s not an experiment, it’s avoidance.
Ship in a day. Max two. If it takes a week, you picked the wrong test.

Ten $100 experiments you can run this week

Search ads → 1 landing page → email capture. $10/day for 10 days.
Paid social (one audience, two creatives) → Calendly. Book at least 2.
Newsletter sponsor swap (free) + $100 gift cards for 5 interviews.
Cold email sprint: 100 hand-picked, 1-sentence pitch, $100 in Clearbit/Clay credits.
Retargeting only: did they care enough to come back? $100 says yes/no.
Price test: put $19 vs. $49 on two otherwise identical pages. Ad-spend split.
Feature promise test: same product, two headlines. Which promise wins?
Onboarding “nudge”: $100 in credits for in-app messages/tooltips. Does activation jump?
Partnership poke: $100 bounties for 5 creators to try and tweet an honest take.
Content wedge: write one post meant to rank competitive keywords, then boost it with $100. Do signups come from search + paid assist?

How to design the loop

Hypothesis → 2) Artifact → 3) Traffic → 4) Metric → 5) Decision. That’s the loop.

Hypothesis: “Ops managers will book a demo if we promise 2-hour onboarding.”
Artifact: 1-page site with a proof snippet and ‘Book Now’ button.
Traffic: 3 keywords, exact match. Or 1 lookalike audience. Keep it tight.
Metric: demo bookings. Not likes, not time-on-page.
Decision: greenlight next step, pivot promise, or stop.

Repeat weekly. Boring, yes. Boring works.

Reading the signals (without lying to yourself)

Weak clicks, strong demos: promise is right, audience probably right. Scale cautiously.
Strong clicks, zero conversions: curiosity without intent. Rework the offer or narrow the ICP.
Low CTR, high conversion: your ad/subject line is off, the product pitch might be fine.
Great replies… that go nowhere: you’re asking for too much too soon. Add a smaller step.

If you need to squint to call it a win, it’s not a win. It’s okay. That’s the point of $100—cheap clarity.

Common traps (I fall into these too)

Changing two variables at once. Now you’ve learned… nothing.
Declaring victory on soft metrics. “People liked the video!” Cool. Did they buy?
Chasing edge cases. One whale said yes is not a market.
Spending $100 to justify a build you already wanted to do.

Set a calendar reminder for the decision moment. Then actually decide.

A 7-day $100 playbook

Day 1: Write hypothesis, define success/fail, pick channel, draft the artifact.
Day 2: Ship it ugly. Publish the page. Create the campaign. Don’t overthink.
Days 3–6: Let it run. Minor fixes only (typos, broken links). Take notes.
Day 7: Decide. Scale, pivot the promise, or stop. Document the lesson in two sentences.

Do four of these in a month and tell me you didn’t learn more than last quarter’s research bender.

The meta-win

$100 experiments build a muscle: bias to action. You stop worshiping ideas and start trusting data (even small, noisy data). You also collect artifacts—pages, scripts, segments—that compound. Next time is faster.

Final note

If you want help picking high-clarity experiments and turning results into weekly momentum, you’ll fit right in at Indie10k. We share playbooks, compare notes, and keep each other honest—kindly, but firmly.