Benefits of early hypothesis validation in the design process
When it comes to new product development, assumptions are risky. However great the initial idea or concept, it is inevitably based on what you think you know about the target market and users. To ensure that the design, development, and engagement with the market are based in reality, it is necessary to convert assumptions into measurable hypotheses and test them. The resulting data either validates your direction or indicates a pivot to a more successful approach. Put simply, hypothesis validation safeguards against launching products that don’t meet market needs. Read on to understand why early hypothesis validation is necessary and, most importantly, beneficial for your product or service.
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What is a product hypothesis?
A product hypothesis is a statement about the product, users, or market. The statement takes an assumption that you have and frames it in a way that can be tested by experiment. If the experiment validates the hypothesis, you continue as planned; if it doesn’t, you pivot to take account of the new information.
Common hypotheses relate to users (their needs, expectations, or levels of knowledge or skill), the market demand, or the product’s features, usability, or security.
The details may vary, but most product hypotheses follow a similar format. An example of one such format used at Boldare is:
- We believe that…
- To verify that, we will…
- And measure…
- We are right if…
To better illustrate this, let’s consider a real-life example described in the YOUCAT daily app case study. Here is the hypothesis we formulated and tested during the development of the mobile application:
We believe that removing the onboarding process will increase user numbers within the app. To test this, we will eliminate the onboarding sequence, allowing users to proceed directly to the ‘Daily’ section after registration. We will measure the change by tracking the number of users, completion rate, and bounce rate. Our hypothesis will be considered validated if we observe a bounce rate higher than 32.5% and if the percentage of users accessing ‘other pages’ exceeds 56.4%.”
- We believe that: removing the onboarding process will increase user numbers within the app.
- To verify that, we will: Remove the entire process from the app so after registration, the user goes directly to the “Daily” section in the app.
- And measure: The number of users, the completion rate, and calculate the bounce rate.
- We are right if: The bounce rate is higher than 32.5% and the percentage of users on “other pages” is higher than 56.4%
As you can see, there is a clear statement of the assumption being tested, followed by the intended method of experiment, how the results will be measured, and what constitutes validation.
Common methods of validating hypotheses include A/B testing, usability testing, prototyping, or gathering user feedback via surveys or interviews.
Hypothesis validation is central to adopting a data-driven approach to product development and the market.
The benefits of early validation
Hypothesis validation can be done at any stage of the product development process. After all, new assumptions may emerge or be spotted at any time, and different stages of development may have different (and new) assumptions to be tested. However, in a data-driven approach, it’s clear that each assumption should be tested as early as possible if only to minimize the potential wasted effort if the assumption turns out to be unfounded. The following are the main benefits of validating hypotheses as early as possible.
Answer basic questions about your product
First of all, by developing and validating hypotheses, you are gathering data about the main concerns of your product, answering important questions such as:
- Is there a market for your product? – Does it solve the problem you thought it did? Does the problem exist? Maybe it’s a fit for a different market.
- Who is the ideal target user? – Validating hypotheses can help define your user personas.
- What features do users want/need? – Avoid developing features which won’t appeal to your market.
- How much are people willing to pay for the product? – Get an early indication of acceptable prices to feed into your financial forecasting.
Measurable data leads to actionable metrics
By definition, product hypotheses are measurable, resulting in clear data. Implementing a data-driven approach early on encourages the use of metrics to measure product development, and then later, product performance on the market.
Better risk management
In itself, hypothesis validation is a process of risk management – you are guarding against the risk of developing a good idea that no one wants. On a broader level, the hypotheses that establish your product is a viable proposition help guide the investment of time and money in that product. Knowledge and data reduce risk.
Faster development
This is possibly one of the two key benefits of early hypothesis validation for most businesses, but it can also seem a little counterintuitive. After all, how can product development be quicker when you’re spending all this time defining and validating hypotheses? The reality is, when a product is developed based on what you know instead of what you think you know, that product will reach a market-ready state more rapidly.
Reduced cost
Deciding on the right product for the right market means fewer development blind alleys and consequently less waste of time and resources. No surprise that this is the other key benefit for most businesses – the combination of faster and cheaper is the holy grail of product development (as long as the final product is of good quality and achieves product-market fit, of course!)
Boost ROI
A faster, more cost-effective development process means lower necessary investment which inevitably is reflected in the ROI. However, the experiment-based approach of hypothesis validation offers additional opportunities – by using A/B testing to gather user feedback on different product versions, you can ensure that your final product will have the maximum market impact, and bring the maximum possible return.
Boost user engagement
A more user and market-focused product will appeal more widely and achieve greater adoption rates. Furthermore, the process of experimentation to validate your hypotheses often involves engagement with target users and potential customers which will lay the foundations for user engagement with the final product on release.
The common thread through all of the above benefits is that using an early hypothesis validation approach helps avoid product development based on wishful thinking. When you arrive at the release date, you can be confident that your product does not rely solely on your gut feeling or intuition about what the market wants. The product you offer to users will be based on experimental data and meet proven needs.
Experiment, and experiment early
Validating your product assumptions by turning them into hypotheses that can be tested by experiment is a way to avoid unnecessary risks, save development costs, and create a product that will achieve product-market fit more quickly. While assumptions may emerge and be tested throughout the development process, clearly the earlier you adopt this kind of rigorous approach, the more value it will be to the business.
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