You are looking for your keys. You need them, but you cannot find them. You look into every corner, even the unusual ones and you ask for help. And then you find them in your pocket. You also have more customer information at your disposal than you would think.
Customer insights is an interpretation of trends in human behaviours which aims to increase the effectiveness of a product or service for the consumer. Yet, not all insights require market research techniques.
The typical structure of an insight executed right is when there is a person / segment, an action / context, a need and a friction / dilemma. You can meet the following in quite some resources:
Charlie (person) wants to eat less cake (action) because it makes him fat (need) but cakes make him safe (friction).
To meet this insight as a patisserie, you might develop a no sugar, no fat version of cakes in your selection. Executing gets easy after getting to know what you did not know before. But how do you get to know things about your customers?
To get to know anything, you need to search for and learn that thing. It is no different when it comes to your business or customers. Market research is the fundamental part of marketing, because you need to satisfy others’ needs and you simply cannot know what others want unless you investigate them. You can have a guess or a more professional hypothesis, but to be sure you spend your resources right and in the promise of profit, you must be unbiased.
To keep this unbiased position, companies often ask for the help of external market research companies. In practice, they use this option way too much. But what’s wrong with it?
To run a proper market research, it costs you quite some money and it takes more time, however, the research companies always develop new techniques to deliver more accurate and faster results in a more affordable way. Also, you might have business data that approach the problem quite well. If you want to know which product version is preferred by the customers, you might simply look at the sales figures.
The tricky part is to know which solution answers your question properly enough. The proper answer suggests that you know your preference in the car service dilemma, let it be quality, price or the time it takes to get it.
Understanding some basic options, you’ll have various options and you can be immediately conscious about your decision.
1. What kind of customer is relevant for your dilemma?
Target group customers are needed when it comes to your actual customers, basically when you need to understand something about the decision maker. You can ask men about lipsticks, but if women buy them, you will get relevant information from women. Actually knowing who buys your product can be tricky as well since, for example, white shirts for men are bought by women primarily. I guess, you still get the point.
Any customer can answer if your question is not specific or not closely related to the actual product. Validating which typography or button is more legible in your landing page is more about the general perception and comprehension.
2. What kind of data do you need?
Qualitative data is about non-numerical information to reveal concepts, connections or opinions. You need this when you don’t need to quantify the notion, you want to understand the reasons behind and the possible aspects. A nutrition company that sold shakes revealed that in the morning, people seeked for a healthy meal that was easy to consume in the car when they took their children to school and commuted to work. So they created a shake-on-the-go version with the adjusted packaging. It had nothing to do with the numbers, they understood an important aspect that had an impact on the demand they faced.
Quantitative data is numerical information to quantify exact amounts, averages and patterns. When the nutrition company got to know the need for takeaway shakes, they could calculate the commuting segment in the proximity of their stores in order to estimate the business potential and to validate if the effort was worth trying. At this point, pure maths showed them what to do.
3. What kind of execution can be used?
Own effort can be made when you can carry out the research on your own. In many cases, people can ask their colleagues or friends and families to get an external view on the subject. It is a rarely used way when company processes are in place and people are used to getting the information instead of working for it. However, making a desk research, creating a simple form or just talking about the topic with others might be all you need. Not to mention that you can retrieve a ton of information from your systems at a certain point of the product life cycle. It is within reach and it costs far less money. That’s why you should always check your possibilities here.
Purchasing from an external vendor is when you need a professional approach and the amount of work is beyond your capacity. It is the classic market research process a company can pay for. You get all the field work and analysis within a certain time frame for a decent amount of money. When you need to be punctual and the stakes are high, it is absolutely worth going for.
Based on the questions you have, you can have a certain set of combinations of the above categories, which leads you to various tools. Let’s take some typical situations along the product development journey.
In the idea phase, your primary goal is to validate the topic. You create the first draft of the concept and for that, you want to gather the existing information about the market and the customers, you look for some inspiration, you sketch the benefits of how you can relieve the pain or create gains, and you might evaluate the alternatives your customers might satisfy their needs with as of now.
So you can go for any kind of customer who has a relation to the topic, you need qualitative inputs to understand the nature of the need properly and you can make your own effort for it.
During the concept phase, you get into the details to finalise the initial potential you realised before. You have to be as specific as possible to target the right customer group(s). You need to define the business model you plan to operate in, calculate the exact business impact, define the product features and what the customer interactions are. And you’d better validate the entire approach.
For this, you need target group customers, both qualitative and quantitative data for the right setup and calculations which you can create with your own effort and external vendor help.
When you first have a prototype, you want to test the functions and the understandability of the product. You aim for feedback based on real, tangible experiences.
You can ask any kind of customer and you gather qualitative data, because the focus is on the operability and not measuring the performance. You need to define a minimum viable product that is good enough for meeting the basic needs. It allows you to collect the maximum amount of validated learning about customers with the least effort. In mature organisations, this phase is not used as often as it could be, but you can do it on your own.
Running a pilot or a friendly user test helps test the production as it is designed. It is pretty close to the prototype as it checks the operability and the understandability. The main difference is that it is not a test environment but a live environment that shows the comprehensive operation and not just a specific aspect. This is also good for supervising the features, which one is missing, which one is not essential.
You can ask the target group and any kind of customers depending on the aspect in question. Functions need to be validated by the target group, but e.g. the readability of the manual guide can be checked by anyone. You need qualitative feedback for the product assurance and you cannot make quantitative decisions due to the limited operation in terms of the customer base. Yet, you should run and monitor the process on your own.
Preparing the go-to-market (G2M), you use all the information you have from the previous phases. You exploit the acquired knowledge to set everything as perfectly as possible for the smooth launch. You take care of
You are developing all the details, so you use whatever is available, target group and any kind of customers, qualitative and quantitative data, and you execute these both on your own and with external help.
When you go live, you are after all the conceptualising and implementing part. You investigated and checked everything you could. Now you are in the mass production phase, you extend your audience and you open up the doors to a wider range of customers. If you succeed in previous phases, many bigger and smaller elements are already adjusted, so you will probably get less findings and issues. That’s what you aimed for before so that now you don’t have to deal with a ton of parallel problems. Still, mass demand is a bit different. Running everything smoothly at a larger scale can reveal other aspects that need to be taken care of. And more customers with more experiences can result in new issues as well.
So you are collecting the first reactions, you monitor the processes and the performance closely to quickly understand what works and what not. It is called babysitting. You also want to improve your efficiency for which you might play around with different adjustments. You might run A-B tests in which you try solution A and solution B for the same problem to see which results in better outcome.
You execute all of these within the target group, your actual customers. You collect both qualitative and quantitative data and you do so mainly based on your system data that are generated along the entire process. So it is really within your domain.
Finally, during the lifecycle management of the product there can be several new issues you have to deal with. As the circumstances change, you might need to adjust one thing or two. And based on the performance you might also want to modify the product features and the underlying processes. You can have measurements on satisfaction and recommendation. Everything is about adaptation.
Here, you are definitely focused on the target group, quantitative data gets dominant and you rely on what you can collect from your systems and employees, also when needed you can involve external help.
Of course, all the above describe a typical situation. Yet, you can have a specific constellation where you need external help due to the nature of the topic even in cases when others can do that on their own. Or you need more quantitative data even in the prototype phase, because of the more technical setup of your product. It is really up to you and your dilemma. All you need is to be conscious about what you want to achieve and how you can do that.
The more mature your product is, the more you rely on the target group and quantitative data. But you can do far more on your own and based on the data in your systems than you would think, so always check what you have in your pocket. You may easily find the keys you’re looking for.
