Test and validate the riskiest assumptions of a business idea using lean experiments and a minimum viable product.

What this dot point is asking

You need to show you treated your idea as a set of assumptions to be tested, ran real experiments, and used what you learned to keep, change or drop parts of the idea.

Why test before building

Most business ideas fail because nobody actually wants them, not because the product was badly built. Testing reduces this risk by gathering evidence early and cheaply. Instead of betting everything on a launch, you run small experiments that could prove you wrong before the costs are large.

Identifying and ranking assumptions

Every business model rests on assumptions: that a problem exists, that your segment will pay, that you can deliver at a profit, that you can reach customers. List them, then rank by two factors: how risky (how badly the venture fails if the assumption is wrong) and how uncertain (how little evidence you currently have). Test the riskiest, most uncertain assumptions first.

The build-measure-learn loop

The lean startup method runs a fast cycle:

1. Build the smallest thing that tests an assumption (an MVP, a landing page, a prototype).
2. Measure how real customers respond, using clear metrics.
3. Learn from the result, then decide whether to persevere (keep going) or pivot (change direction).

The aim is to spin this loop quickly and cheaply, learning more each time.

Cheap experiments you can run

• Customer interviews - test whether the problem is real and painful.
• Landing page or pre-sale - test whether people will sign up or pay before the product exists.
• Concierge MVP - deliver the service manually to a few customers to test the value before automating.
• A or B test - compare two versions to see which customers prefer.
• Smoke test - advertise the offer and measure click-through or interest.

Choosing the right metric and avoiding vanity numbers

A test is only as good as what it measures, so choose a metric that actually signals demand. Vanity metrics such as social-media likes, page views or "interest" feel encouraging but rarely predict whether anyone will pay. Actionable metrics tie directly to the assumption being tested: a conversion rate (the share of visitors who pre-order), a renewal rate (the share of trial customers who pay again), or a willingness-to-pay figure. Before running an experiment, state in advance what result would count as success and what would force a pivot; deciding the threshold beforehand stops you from rationalising weak results after the fact. This discipline, setting a clear hypothesis, metric and success criterion, is exactly the evidence SACE assessors look for in a testing record.

Using the results

Strong assessment work shows the test, the metric, the result and the decision. If results are weak, a pivot (changing the segment, the offer or the revenue model) is a sign of good entrepreneurship, not failure.

Linking forward

Your testing evidence validates the Business Model Canvas and value proposition, sharpens your financial assumptions, and gives your pitch credibility. Documenting your experiments and what you learned is core evidence for both the Business Growth Report and the external Business Plan.