Customer Discovery – How to discover exactly what your customers need

Customer Discovery ProcessTo build really great products and services for your customers, it’s vital to get into the nitty-gritty of what they really need.  Not what they say or think they need, but what will actually solve their problems and enhance their lives.

Customer Discovery is the concept of getting customers involved in the development of new products and services right from the beginning – something that can massively alter the way businesses perceive their customers and raise the chances of long-term success.

Whilst Customer Discovery processes will vary from organisation to organisation, they should include the following steps:

Step one – Start with market segmentation

Identifying your target market segment gives you a focal point to begin the discovery process and avoids information overload.  Often markets will break down into layers of sub-segments and drilling down to a very specific sub-segment or niche further helps to focus resources.

A good starting point in established organisations will be the corporate strategy documents that should detail the target segments.  In addition to this, discussions with key stakeholders from around the business should merit further insights into the preferred segments.

Once you have identified your target segment, it is useful to create customer personas which will help make the connection with customers more tangible and also make it easier for your team to emphasise with the end user.

Step two – Collect and compile customer data

The next step is to establish what data you currently collect and hold on your target segment.

This could be internally gathered data gained from analytics packages and customer services feedback or it could be secondary data purchased from external sources, such as market research agencies.

By mapping out your existing data sources, you can assess their usefulness and credibility, enabling you to identify gaps in your knowledge base that need to be filled with new research; ideally by directly observing and talking to your target audience through focus groups, one-to-one customer conversations and visiting your customers in their homes or places of work.

Step three – Analyse the data

Analysis of the data should reveal patterns and trends that will lead you to identify potential customer problems.  Further analysis and research should then help you gauge which problems or opportunities are going to have greatest impact amongst your target audience.

Customer problem statements are a good way to illustrate the issue, enabling greater empathy and providing a tangible challenge for your team to take on.

You’ll need to be selective with the number of statements you produce, so it is important to prioritise those that will have the most impact.

Remember that everything from here on in becomes part of an iterative process and the initial set of statements will evolve, grow and re-prioritise as you discover more information.

Step four – Formulate a hypothesis

Scientists use hypotheses to formulate ideas about why things are the way they are, so that they can develop experiments to see if their understanding is correct.  It is an iterative learning process and one that is making a big impact in the business world.

In the context of customer discovery, the aim is to formulate ideas that will solve customer problems and identify ways to test the predicted outcomes.

Each hypothesis can be summarised in a similar statement to the following:

We believe the customer has a need to do X, and that we can satisfy this need by offering them Y. We will test this by doing Z and are expecting the following outcomes…

In addition to the statement, there will be supporting documentation for each hypothesis and for big experiments some sort of budget / risk sign-off.

As with the problem statements, you’ll need to prioritise what becomes a hypothesis and be aware that each one will evolve as new information and learning is gained.

Step five – Experiment and validate

The number of experiments you can run at any one time will be limited by factors such as their size and your own resource limits, so again it is important to prioritise the hypotheses that you will be testing.

Taking the highest-priority hypothesis from your list, you will need to design an experiment that will test whether doing Z will result in the outcomes that you predicted.

Experiments will vary significantly in terms of size and methodology – ranging from simple A/B tests through to focus group reviews of mock-ups and right the way through to fully-fledged prototypes that are launched to a limited audience.

Once you have run the experiment, you will need to analyse the data to validate the customer need and depending on the results you and your team see, decide whether to refine, alter, expand or simply reject the hypothesis completely.

Remember positive and negative results are all useful

Try not to be despondent if your experiments do not provide the results you were expecting, as negative results still provide very useful feedback and help you decide on a slightly different methodology or confirm that the expected customer problem is not really a concern (providing you have conducted the test in a robust way).

With consistent testing, you’ll soon begin to see more positive results appear and find yourself on the path towards better customer experiences.