What is segment composition and how do you describe a target group?

Within the Neurofactor target group profile, segment composition is a concise description of who belongs to a segment, in which context and on the basis of which shared characteristics or associations. It also identifies relevant boundaries and uncertainties.

It provides the definition behind the group’s name. For an associative target group, the shared pattern of choice-relevant associations is central. Age, role or company size may additionally help define or describe the group, depending on the research design.

‘Segment composition’ is used here as a field name in the target group profile. We do not present it as a separate scientific theory or a historical term introduced by a single researcher.

Its background is market segmentation. Smith published an original article in 1956 addressing market segmentation and product differentiation as marketing strategies. This is a historical reference for segmentation, rather than the origin of our field name. Smith, 1956

For practical analysis, Dolnicar, Grün and Leisch distinguish profiling with segmentation variables from describing segments using additional information. Dolnicar et al., 2018, Chapter 8, Chapter 9

The writing structure below is Neurofactor’s own editorial application. The three-to-five-sentence requirement comes from the target group profile, not from these publications.

Make three types of information identifiable in your description:

This distinction is our practical writing rule. The same characteristic can play different roles in different studies. If you only want to investigate marketing leads, that role is a selection boundary. If you group people by associations and subsequently examine their roles, those roles provide additional profile information.

Make clear what you mean by ‘often’, ‘typical’ and ‘mainly’. A characteristic shared by many participants is not automatically required of every member. Do not turn an observed tendency into a strict exclusion rule.

Use the short description to answer five questions. Keep detailed measurement rules and source information available alongside the profile.

In B2B, describe both the person and the organisational context of the decision. A company with fifty employees does not itself have personal associations; people within it do. Distinguish users, advisers and budget holders when those roles matter to the choice.

Within Neurofactor, an associative target group is a defined group of people whose decisions are guided by similar associations within a specific choice context. Its segment composition therefore needs more than a list of words such as ‘security, growth and trust’.

Describe what those words mean in this situation, how you recognise the pattern and what is known about its relationship to the choice. ‘Security’ might refer to continuity of service or predictable costs. Without that detail, it remains unclear whether people actually share the same meaning.

John and colleagues described a method for combining individual brand association maps into a consensus map. John et al., 2006 This provides methodological background for association research; it does not independently validate Neurofactor’s target group definition.

For our application, document the step from pattern to group membership separately. A shared map does not automatically identify who meets the assignment rule. If the pattern has not yet been investigated, use ‘intended target group’ or ‘candidate segment’ and state the research question.

1. Identify the unit and context. Specify which people you are describing and which decision matters.
2. Separate selection from description. Mark which characteristics determine the boundaries and which provide additional information.
3. Gather supporting evidence. Record the source of each statement: research data, existing customer data, a brief or an explicit assumption. A brief is input, not a research finding.
4. Write three to five sentences. Start with the group and context, move to the connecting pattern and finish with boundaries or evidence status.
5. Check usability. Ask a colleague to explain who would and would not belong based on this description. If there is doubt, the underlying assignment rule should resolve it or allow ‘not yet known’.
6. Record the version and review. Retain the definition and sources so that later edits do not silently change the meaning of the entire profile.

These steps are Neurofactor’s practical instructions. They do not replace research design or analysis.

Fictional example — not a research finding or client case.

This candidate segment comprises marketing leads at B2B service companies with 20 to 100 employees. They are involved in selecting a new CRM system within the next twelve months. We are investigating whether a shared pattern around control and predictability, understood as visibility and error prevention, guides their preferences. Role and company size define the study population; assignment to the associative segment still requires an evidenced pattern rule. This description is a working hypothesis based on a fictional brief and contains no measured group characteristics.

These five sentences have distinct functions: selection, choice context, hypothesis, assignment and evidence status. The numbers and timing are chosen example boundaries. They say nothing about the distribution of a real market.

After research, replace the hypothesis with a finding only if the data support that change. If the pattern is insufficiently distinct, revise the grouping instead of making the wording sound more convincing.

Segment composition establishes the starting point. It determines which people and context the other fields concern. That does not mean every subsequent field can be logically or automatically inferred from the text.

An AI writer can help express known information consistently. A job description cannot, however, supply a measured BIS score, purchase frequency or emotional motive. Leave unknown fields open or formulate clearly labelled research hypotheses.

• Repeating the group name. ‘These are SME marketers’ adds little precision.
• Writing an idealised picture. ‘Ambitious, innovative and quality-focused’ does not establish membership without criteria.
• Presenting assumptions as findings. Keep the brief recognisable as a starting point.
• Equating the sample with the market. A proportion found among participants is not automatically a market share. State which group a number describes and how the data were collected.
• Erasing overlapping patterns. Allow mixed or uncertain cases in assignment when the data call for them.
• Forcing every detail into five sentences. Keep the supporting documentation beside the summary and provide a clear reference.

The description is useful when readers understand who you mean, in which situation, what connects the group and how certain the classification is. The underlying documentation should make its boundaries checkable.

Segment composition then becomes a consistent starting point for research and communication. The remaining profile fields build on it, with separate evidence for each additional insight.

Discuss the people you want to understand, the choice that matters and the data available for a useful target group profile.