A common mistake is to confuse a good prototype result with strong affinity for the problem, or customer demand for the solution.
Validating the problemIt might sound obvious, but before we do anything else, we need to ensure that the problem we are trying to solve is indeed one worth solving. There needs to be a significant number of customers who have a genuine pain point, or a process in an organization that is so inefficient that it needs an overhaul.
No matter how confident you are in your solution, it’s critical not to get carried away with your ideas before getting to grips with the real issues facing customers. It’s astounding how many products fail because they solve a 'problem’ that no one really cares about.
Mapping out the customer experience and the processes involved are important steps for deeper learning. These two methods are worth exploring:
- A great way to create a shared understanding of customer interactions and pinpoint problems along the way is Experience Mapping - a visualisation showing the outside-in view of the complete customer journey. In essence, it’s a map that exposes key insights and allows you to build a more seamless customer experience.
- Value Stream Mapping plots the inside-out view of everything that happens in the organization to deliver value to customers. It’s particularly useful for identifying and eliminating waste and bottlenecks, allowing for a more efficient process and giving customers more value.
Evaluating potential solutionsOnce you’ve got a good grasp of the problem and have thought up ideas for the best solution, it’s time to test those ideas to ensure you’re on track to a desirable outcome. The approach you take to evaluate your solution will depend on the time and resources available, your budget and whether you are building a new product or optimising an existing solution. Here’s a summary of some approaches to consider:
A concept prototype is a throw-away sketch or mock-up for rapidly exploring concepts with customers. It’s low cost and often gets more honest feedback because the sketches are low effort.
A high-fidelity prototype is a detailed and interactive mock-up of the product experience and helps validate the interaction design, content, look and feel. Based on the feedback received it’s easy to iterate and build upon.
The concierge model is a personalised service provided to a small cohort of early customers to learn what works before building an automated solution. The constraint with this approach is that it’s difficult to scale and there is a risk of building for a niche, because the cohort might not represent the broader market.
- Although high-cost, a working prototype tested on a sample of real customers can be a great way to learn what really works, especially when building new products.
- When it’s an existing product or service, quantitative analytics and split/multivariate testing create feedback loops that help agile product delivery teams decide what to do next.
Testing market demand for a solutionThe solution we build must be technically feasible, commercially viable and perfectly timed for market demand. Before spending money to build what we think people want, we aim to measure what solutions they actually want or need. Measuring demand helps determine where to invest or whether to invest at all. It’s the reverse of build it, and they will come. Demand validation says, when they come, build it.
One way to test this, is by running a marketing campaign before building anything. Try setting up a search marketing ad to direct target customers to a simple landing page about the product. This facade ad campaign allows you to experiment with different variants to see what resonates. Pairing this with a waitlist registration or pre-order can tell you a lot about who’s out there, and how interested they are in your solution.
To get an accurate feel for organic market demand, before investing in a complete solution, try a Wizard of Oz Prototype. This gives the appearance and experience of a complete and working service, yet all of the back-of-house processes are done manually, mimicking a real-time automated solution.