Our experiment-driven process for tackling

Inside our experiment process

Observation first

Observation is step one. We note where avoidance starts, what triggers it, and how routines break down. This gives us a baseline to measure change.

Run low-stakes experiments

We brainstorm the lowest-effort tweak that could help, then apply it in a real-world setting. Each step is tracked, not just the outcome.

Share results openly

Finally, we review the impact. Did the tweak reduce avoidance? If not, we log the setback openly. Our notes are available for anyone curious about what actually happens.

Want more details on our experiments? See our case studies for examples, or reach out with your own questions. We welcome blunt feedback and real stories.

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A day inside our process

The day starts with a review of yesterday’s friction points—where avoidance reared its head, what patterns repeated, and which routines failed.

Team members log even the smallest adjustments, from changing the way a question is framed to tweaking the layout of a checklist.

Each experiment gets a quick review. Did it help? If not, we add it to our list of ‘what didn’t work’—just as important as the wins.

We value candid feedback. If someone spots a flaw in our approach, we document it, adjust, and move on. No ego, just data.

Progress is rarely smooth. Some days, nothing sticks. But over time, the record of failed tweaks is as valuable as the successes.

At the end of each week, we share the blunt summary: what moved the needle, what didn’t, and where we’re still guessing.

Iterative adjustments in practice

So what’s our process, exactly? It starts with noticing avoidance as it happens—no judgment, just observation. Then we ask: what’s the smallest adjustment we can make? We run the tweak, track the outcome, and move on. If nothing changes, we document that too. Some adjustments help a little, some not at all. The goal isn’t perfection. It’s to learn what nudges actually move people forward—even if the gains are minor. And yes, results may vary.

Process, not perfection

We’re not selling a miracle fix. Our process is deliberately unpolished: observe, adjust, review, repeat. Each experiment is shared in plain language, including the parts that flop. Why be so blunt? Because most people waste time chasing silver bullets. We’d rather show you the messy truth: small wins, frequent resets, and a running log of what’s worth skipping.

Why our experiment-first process matters

Grounded in observed behaviors only

We start with direct observation. No theorizing, no guesswork—just tracking where and when avoidance actually happens. This approach grounds our adjustments in data, not assumptions. It’s messy but honest, and it shows the real scope of the problem.

Transparent documentation of results

Every adjustment we try is documented and reviewed, whether it works or not. This process weeds out wishful thinking and keeps us honest about our progress. If something doesn’t move the needle, we flag it instead of pretending it’s a breakthrough.

Emphasis on learning from setbacks

We accept that setbacks are common. Our system is designed to surface what fails, not just what succeeds. That way, you know what to avoid before investing effort in the wrong tweaks. Results may vary, and that’s part of the process.

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Testing, failing, repeating

We don’t pretend to have a finished system. Instead, we test every tweak ourselves, documenting both the false starts and the rare improvements. Why bother? Because most financial avoidance isn’t cured by a single fix—it’s chipped away through small, iterative changes. Is this inefficient? Sometimes. But the alternative is endless theorizing with no impact. Our team logs each attempt, notes the outcome, and shares the results so others can see what’s worth trying. Question: What if a method fails? We say: good, now we know what not to repeat. That’s as useful as a win. Our process runs on humility, not certainty.

Our experiment-first system explained

We don’t chase perfection. Instead, we commit to an experiment-first approach—observe, tweak, review, repeat. Every insight comes from data, not dogma, and all findings are provisional. Our system changes as our understanding grows.

Direct observation over assumptions

Our team tracks where and when avoidance happens, using observation logs rather than memory or guesswork. This creates a foundation for targeted tweaks.

Tested, practical tweaks only

We brainstorm minor adjustments and test them in the real world. No theoretical fixes—just practical tweaks anyone could try.

Honest reporting of failed attempts

Setbacks and failed experiments are shared openly. We don’t hide mistakes; we document them to avoid repeating the same errors.

Real-time, ongoing process review

Every week, the team reviews both positive and negative outcomes, updating our methods in real time based on actual evidence.

Open experiment logs and findings

We make our experiment logs and findings available for anyone interested. Transparency is key, not secrecy.

Flexible, evolving recommendations

All recommendations are subject to change as we learn more. Nothing is set in stone—our process evolves with every experiment.