It is no surprise that different groups of people respond to new innovations differently. Factors such as demographic characteristics, lifestyles, needs, goals, and behaviours all play a role in determining how quickly someone might adopt a new technology, product or service. However, the traditional focus on “who” the customers are — based on age, gender, or income — can be misleading, and most importantly, fail to provide the actionable insights needed to influence their decisions effectively. As an alternative, we propose applying a behavioural segmentation approach, a powerful research tool that focuses on individuals’ potential or “margin” for change based on the “what”: what they do, need, and value. 

Behavioural segmentation is the practice of dividing a market (e.g. citizens) into distinct groups based on their observed behaviours, particularly regarding how they interact  – or are expected to interact – with a product or service. These behaviours could include technology usage patterns, purchasing and working habits or responses to marketing messages. 

The adoption of innovative technologies – such as new mobility solutions, smart home devices, or digital health services – is often uneven across different groups of the population. Behavioural segmentation helps to identify these different groups and understand the unique barriers and motivators that influence their decision-making processes. This enables organisations to pinpoint which segments are likely to become early adopters, and potentially even advocates within their communities. 

For example, in a recent project with a UK local authority, we sought to identify the segments with the highest potential for becoming the first users of a novel “Mobility-as-a-Service” (MaaS) platform that allows users to plan, book & pay for a range of integrated travel modes, such as public transport, e-scooters, bikes, car sharing and more. Central to our approach was understanding each segment’s potential or “margin” for behavioural change and setting realistic target behaviours — whether that’s simply downloading the MaaS app, using it for occasional trips, or integrating it into daily travel routines.

What is each segment’s margin for change? 

Understanding a segment’s “margin for change” is particularly important when the behaviour change we aim to encourage involves forming new habits, as opposed to making a different choice just once. The Transtheoretical Model of Behaviour Change (TTM) developed by Prochaska and DiClemente in the late 1970s to understand health behaviours, can be a helpful guide in this process. 

Illustrated as a cyclical process, the model provides an explanation of the process that individuals go through when making changes in their behaviour. It considers behaviour change not as a single event, but rather as a several-stage process that unfolds over time. At each stage of the TTM, different intervention strategies will be more or less effective. The ultimate goal is to reach the maintenance stage, which represents sustained behaviour change.
The stages of the TTM (adapted to technology and service adoption) and opportunities for intervention can be roughly defined as: 

• Precontemplation: Users learn about the new product or service and begin to consider its potential benefits. Marketing and outreach efforts are crucial at this stage.
• Contemplation: Users seek more information, possibly by talking to others or researching the product. Providing detailed information about features and benefits is key.
• Preparation: Users are ready to take the first steps, such as downloading the app or creating an account. Ensuring a smooth, intuitive interface and clear setup instructions is essential here.
• Action: Users start using the product or service, such as completing their first trip using the MaaS app. Offering incentives like discounts, free trials, or loyalty rewards can encourage this step.
• Maintenance: Users continue to engage with the product or service regularly. Continuous improvement based on user feedback and expanding service offerings can help maintain engagement.
• Advocacy: Users promote the product through word-of-mouth, social media, or referral programs. Encouraging and rewarding this behaviour can create a ripple effect within their communities.

To determine the most realistically achievable target behaviour for each segment, it is good practice to assess the psychological, social, and structural factors that may influence their decision context. This can come from carrying out primary research, integrating existing datasets (e.g. satisfaction surveys of current services) and drawing on insights from the literature. The sum of these factors will allow us to place each segment onto the TTM to determine their “margin for change”, which will in turn inform whether and how to target them. This is illustrated in the Figure below.

Bringing the segments to life

An important thing to keep in mind while developing a segmentation is its intended use. Segmentation can be used to tailor communication campaigns, or even to guide the development of relevant service or product features. For example, if our aim is to get households to adopt smart home devices to monitor and reduce their energy usage then we might develop segments that reflect varying abilities and desires to do so. 

One segment might consist of the tech-enthusiasts who like the idea of having a ‘smart’ home, another segment of those who want to save energy and reduce their carbon footprint, and another of those who are most interested in saving money. We then might find that “tech-enthusiasts” have a higher margin for change, than “energy-savers” and we can set more ambitious target behaviour for this segment. Lastly, we can target these sectors with different marketing materials and through different channels as they are likely to respond better to messages personalised to their interests. 

In the digital space, it is quite easy to filter and target such behavioural segments. For example, on Facebook you can set very specific criteria for the audience you want to reach, such as by selecting their hobbies or group memberships. However, if we are limited to out-of-home advertising channels then no matter how detailed our segmentation model is, the factor most determinant of segment membership will most likely be physical location. 

In all these cases, the core principle remains the same: by understanding not just who our customers are, but how they behave, we can design more effective strategies to meet their needs and encourage the adoption of new products, services, or behaviours.

If you found this article interesting and would like to explore how behavioural segmentation can help your organisation, please don't hesitate to contact us!