How to Read the Signals from Your Experiment
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You have already designed the Experiment with which you will validate your project. Great, but do you how to interpret the results, the signals you’ll receive? To do this, you must apply the scientific method: gracias a él, tomarás decisions based on evidence, not subjectivity. This way, you’ll quickly learn what works and what doesn’t to reduce uncertainty and create the best strategy for your idea.
Here’s a list of tips to read those signals:
1. Before measuring, establish success criteria It’s impossible to interpret data without first determining what you’re looking for. Therefore…
Define the key metric. Establish which metric is most important for validating your Hypothesis. For example, on a landing page, useful values include conversion rate, time spent on the site, or purchase intent.
Set a validation threshold. Determine what result would be considered a success. For example: “Interest will be validated if more than 10% of users click ‘Buy.’”
Formulate a clear Hypothesis. Every Experiment must respond to a well-founded Hypothesis. For example: “Our [PRODUCT/SERVICE/FEATURE] helps [CUSTOMER SEGMENT], who wants to [TASKS THEY PERFORM], reducing [PAIN OR FRICTION].” Add why you believe your Hypothesis holds true.
2. Interpret the (real) behavior of the customer Experiments seek to understand the behavior of your users.
Prioritize behavior over opinion. A purchase, a registration, a deposit, or a letter of intent are worth more than a hundred positive opinions or ‘likes.’ Design Experiments to measure what people DO (actual action) not what they SAY THEY WOULD DO (something that may or may not happen).
Evaluate the pain or Friction. If the Experiment fails, ask yourself the following: Is the problem you want to solve real? Is your approach correct? The Experiment must demonstrate that the pain is significant enough enough for someone to pay to solve it.
Confirm willingness to pay. Analyze whether customers or users are willing to pay enough for your product or service and whether the cost of acquisition is reasonable compared to the value the customer perceives.
3. Classify the signals to make decisions Once the data has been analyzed objectively, the result will be one of these three:
Hypothesis validated: move forward. The data confirms your Hypothesis: invest more resources and scale the test, since you have clear evidence that you’re solving an important problem.
Hypothesis invalidated: pivot. The data contradicts what you thought; the business model does not work as planned. Examine the signals carefully, as they will indicate what key component of your idea you need to change (customer segment, value proposition, channel) without changing the overall vision.
Inconclusive: test again. If the data is unclear or the sample size is small, adjust the Experiment to obtain clearer signals.
How to recognize the red flags These warning signals indicate that your Hypotheses are incorrect or that the Experiment has biases, which you must avoid at all costs.
Confirmation bias. If you only look for evidence that confirms what you believe, you’ll overlook signals that say otherwise. Solution: seek to refute your Hypotheses, not to prove them.
Biased data or wrong sample. It’s no use only asking for friends’ opinions or relatives. Solution: validate your idea with people who belong to the target segment of your customers or users.
Interest without conversion. If what you hear most is: “I love the idea, but I wouldn’t buy it,” it indicates that the pain exists, but it’s not as important as you thought. Solution: refocus your project or find another customer segment for whom that problem is significant.
Ignore reality. If you continue investing time and resources despite metrics showing a clear lack of interest… you’ve fallen in love with your idea. And that is not good. Solution: fall in love with the problem, not the solution. This way, you’ll move on to another project that will allow you to continue experimenting and launching.
How to recognize the green flags These signals indicate you’re on the right track. The market might accept your idea if:
“Money talks". Money talks: customers pay (there are orders or deposits) before the final product is ready.
Unsolicited positive feedback. Are potential customers talking about your idea with others? Are they proactively asking when your product or service will be launched? This is one of the best indicators you can find.
High engagement. Another good sign is that users return on their own to the tool you created for your Experiment (such as a landing page) and spend time using it.
Referrals. Let’s continue with the example of the landing page created for your Experiment. If several people share it without being asked, it means your idea may be interesting to many people (and best of all: it’s your potential customers who think so). Celebrate it!
Sources:
https://learn.microsoft.com/es-es/dynamics365/commerce/experimentation-identify https://cepymenews.es/experimentacion-lean-como-validar-ideas/ https://medium.com/@ayobamiadelugba/business-idea-testing-for-dummies-how-experimentation-saved-thousands-of-12712d456581 https://www.strategyzer.com/library/testing-business-ideas-book-summary
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