Behavioural science and market segmentation

12 Apr

Understanding human behaviour has never been more important. Although the digital world has provided us with more and more data, the data rarely provides the full story. Only by understanding human behaviour can we truly know how to interpret the data, and more importantly, build a marketing strategy to suit our target market’s requirements.

As we’ve shown in our complete guide to marketing strategy, Segmentation, Targeting and Positioning (STP) is one of the foremost theories in marketing. However, in practice, the process is very difficult to complete accurately. This is because the foundations on which marketers base their decisions are often subject to little scrutiny and based on little factual evidence. For example, if you are running your own online store, you may segment an audience by age and subsequently target a young, style-hungry audience without having sufficient evidence to make that judgement.

In fact, these assumptions could be based on a falsehood that young people are likely to buy more clothes and therefore be more interested. This is because these assumptions are unlikely to consider the level of competition or brand loyalty within this market segment.

Taking another example for comparison, global businesses usually know how to segment and target their audiences. This is because they have sufficient data and resources to test any assumptions. So, in the same example, a global ecommerce business will be able to establish the level of competition and loyalty within each segment more precisely before making a targeting decision. This insight gives them greater resilience against a constant influx of new startups.

Behavioural science growing in popularity as data increases

This example shows exactly why behavioural science has become so essential to marketing strategy, and particularly when it comes to segmentation, targeting and positioning. For a CMO, the challenge will typically be to bring together insights from multiple data sources and agencies to build a complete customer picture (see CMO guide). Conversely, for a Head of Growth, the challenge will be to build up a customer picture with comparatively little initial data to go on.

It’s also important to emphasise that behavioural science is not necessarily the same as tracking data in one particular area or channel. It is all too common in today’s world for marketers to believe that they have an understanding of their customers when all they can assess is how they move around a website or respond to an advert. This is because this analysis is purely tactical. Although it is extremely valuable in determining how to improve a website’s design or an advertising campaign, it provides little insight into how the customer may operate in other channels. In other words, it provides an incomplete picture of a customer. This is precisely why behavioural science has grown in popularity. It can be used to link the activities from one channel to another.

Behavioural science builds a complete customer picture

Behavioural science is used to truly understand a customer’s beliefs and motivations. And with this in mind, it’s important to realise that this process involves an objective understanding of the customer. This is an essential consideration, as the process of behavioural science is not designed to make marketing 100% efficient. In reality, human behaviour is naturally unpredictable and not everyone in a target market is ever going to buy a particular product, nor should a marketer want them to. Instead, behavioural science is used to help a customer exercise their right to choice by clearly and succinctly being able to understand what they are looking for and why.

Of course, the way in which this process works is the subject of much debate. Behavioural Science is an art, as much as it is a science. The same can be said for many marketing theories widely in use. For example, we’ve previously explained why many marketing concepts such as the Marketing Mix were invented way before the technological revolution and are therefore out of date in some respects.

Defining audience mindset

When understanding whether to target a particular target segment, one of the ways in which you may consider doing this is by building a picture of how they live their daily lives and what drives them. This is without any consideration of what you are planning to sell them, and is an excellent way to test your assumptions of whether they are the right target group.

We’ve defined four elements that come together to explain this process. In a perfect situation, you will be able to test your thoughts about each of these by gathering and verifying data for each. But, even if you don’t have the data, the conceptual process will prove useful. This is because marketers spend most of their time considering how to get a group to ‘buy more’ without considering how important it is to them.

The four elements are:

Passions: What things drive them.
Worries: What their concerns are.
Availability: How much spare time they have.
Affluence: How much money they have.

Defining purchasing behaviour

With the audience’s mindset understood, it is possible to then understand how they view the purchase. These decisions can be evaluated using a set of seven elements, as explained in bullet points below:

Exposure: Whenever you make a purchasing decision, top of mind is whether you’ve heard of the company before.

Age: Whatever the purchase, you will always be interested in how old the business is.
Value: Whatever the nature of the purchase, you’ll need to make a value judgement, which is related to monetary value, but not the same.
Brand equity: Whenever you make a decision, you’ll make a subconscious and conscious decision about how you feel about the brand.
Impulsivity: There are many decisions that quickly move beyond the rational and are made without proper consideration.
Innovation: You’ll consider how different a purchase is from the competition and how much those differences are aligned with current and future needs.
Loyalty: You’ll make a judgement about how often and whether you’ll need to purchase the product or service again.

As with determining audience mindset, these seven elements can be judged with or without data. Clearly, with little data there can be inaccuracies, but the process can be extremely useful at testing STP assumptions regarding. At the other end of the spectrum, this process can be a useful way to bring together masses of data to build a clear customer picture. Typically, businesses can be awash with data lakes that are difficult to process effectively. By establishing the value that each data source brings using these metrics, it’s then possible to start building a clearer customer picture.

Behavioural science informs channel selection and the storytelling process

As we’ve seen, behavioural science is becoming increasingly prevalent to make sense of customer behaviour amidst growing data gathering techniques. We’ve then defined a process that can either be used theoretically to quickly test assumptions or as a way to build a complete customer picture by making sense of all the available data collections measures.

Moving beyond this, it is easy to understand that behavioural science can then inform both channel selection and the storytelling process. This is purely logical, but so often forgotten in the digital age.

The trouble is that many marketers move straight into activation. This means that they may follow a template of channels that are used by other businesses in their industries, or if they are a startup, focus on channels that other famous startups have used.

This is, of course, usually ill-advised. There is no smart thinking involved in this process. Instead, by using behavioural science, they can quickly test these assumptions and critique their channel selection. This doesn’t have to take a disproportionate amount of time, but instead be relative to the data and budgets that they have available.

To provide a clear illustration of this, we’ve analysed how 100 famous startups began. In doing so, we’ve shown clearly that the marketing strategies they adopted were situation-specific. In other words, they worked for their unique situation at the time. Any competitor, even doing the same thing, would be wise to build a strategy that suits their exact requirements and not copy one. Many successful startups in the same field used very different marketing strategies for this reason.