Applying behavioural science in marketing

Behavioural science’s popularity has surged in recent years, following a harvesting of digital data, combined with a need to make better use of it. In this in-depth guide, we bring you up-to-speed. We explain exactly what behavioural science is, how you may already be using it, and how you can make better use of it moving forward.

Behavioural science is the systematic study of human behaviour using evidence. This separates it from a general understanding of human behaviour that we all have. For example, it’s natural to know that people need to eat, sleep and drink, but it requires detailed research and analysis to know that people often eat more after sleeping less.

Taking this further, the study of human behaviour varies significantly depending on the nature of the challenge and the environment. For example, your chances of winning a Football match on penalties can be improved on the training ground, but the pressure of a real match environment will always increase the uncertainty of the outcome.

The majority of marketers are required to execute specific tasks, which limits their need to understand a company’s overall marketing strategy or the target audience. Instead, their skills are specialised to particular marketing channels and technologies e.g. social media, PR, or events. These are then measured by evaluating metrics such as clicks, comments, followers, views, or attendees.

However, with experience, the knowledge of how to market or ‘marketing’ becomes more valuable. With time, marketers begin to learn rules that increase success. These may be learnt from the data alone, but more often than not, they will be developed by the marketer’s own knowledge of how people behave.

For example, if you work at a shoe company, you may quickly learn about seasonal trends using common tools such as Google Trends. However, to gain an edge, you may decide to use your own intuition. You may therefore believe that customers buy more after a Bank Holiday, and run a test to see if you’re right. This is how the vast majority of campaigns are run. This is also a great example of using behavioural science or behavioural economics at an entry level.

We’ve shown previously that there isn’t a universal way to grow a company. Instead, growth hacks depend on an understanding of the target audience as well as several other factors such as level of competition, marketing budgets and business model.

This makes behavioural science particularly useful in growth hacking, with its application dependent on the company’s maturity. Startups have limited time and resources, which requires them to think on their feet and find clever ways to appeal to their target market. They also typically need to do this with little or no conclusive customer data to back up their decisions.

Conversely, scale-ups and brands can be limited by their allocation of resources. Selecting the wrong campaign can lead to millions of pounds being lost on activities that are ineffective or even negatively impact the customer. Behavioural science can therefore be pivotal in helping them to illustrate why some campaigns are more likely to be effective than others. When this is the case, market information from outside the business can be used to support these decisions.

Most marketers will develop their understanding of human behaviour throughout their careers. This happens naturally by reading books, articles and analysing data. However, behavioural science as a discipline requires specialist skills and a dedication to researching human behaviour beyond for marketing purposes.

Behavioural science is most relevant to marketers with a strategic aspect to their role. With experience comes seniority, and with seniority comes a responsibility to make better and more effective decisions. If you’re a marketer with a title such as CMO or Head of Marketing, you’re likely to be responsible for setting the direction of a wide variety of marketing activities. This naturally requires a significant understanding of the target audience, combined with analysis of how the existing marketing activities are performing.

Within the marketing arena, they are almost interchangeable, but there is also still a slight difference between them. Behavioural science focuses on human behaviour, irrespective of whether the outcomes can be monetised. Behavioural economics focuses on using human behaviour to improve marketing outcomes. For example, there are many aspects that of behavioural science that can be valuable to marketers such as colour theory, conditioning or cognitive dissonance that are difficult to easily validate with economic datasets. By contrast, there are many aspects of economics that behavioural science would not be able to explain.

Data science focuses more on the existing data from which to guide decision-making, whereas behavioural science focuses more on the behavioural context.

Typically, a data scientist will require skills to manage and manipulate complex data sets. With this in mind, when solving a challenge such as deciding when people are most likely to buy shoes, their first thought might be ‘what data sets do we have’ or ‘what model should I use to analyse the data’.

By contrast, a behavioural scientist will approach the challenge a little differently. Instead, they will focus more on the behavioural setting and context before considering the available data. In the case of buying shoes, they may consider the impact of the weather, or the rising cost of living or brand sentiment, or current societal trends.

Human behaviour has been studied for hundreds of years. In fact, science naturally requires evidence from which to test assumptions. The difference now is that the term data is usually synonymous with digital data and analysis.

Taking this into account, there are still many ways that behavioural data can be recorded digitally, especially for marketing purposes. Examples include, heart rate monitoring, eye tracking or footfall tracking.

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