Start with the decision you need to make
Audience segmentation groups similar units so a team can make more relevant decisions. Those units might be individual people, households, or business accounts. The choice sounds technical, but it determines what a segment means. A group of people who prefer a low-cost plan is not necessarily a group of households with low spending. A group of enthusiastic employees is not necessarily a group of accounts ready to buy.
Begin by writing down the decision the segmentation should support. Are you adapting messages to individual users, designing a service for shared homes, or deciding which organizations need a different sales approach? Then ask who experiences the need, who influences the choice, who pays, and who can act on your findings. Those roles may belong to different people. The best unit is usually the one that matches the action you intend to take, while still allowing you to collect reliable information about it.
Use people when individual differences drive the action
Person-level segmentation is useful when preferences, behaviors, or barriers vary meaningfully within a home or organization. A learning service, for example, might group users by goals and confidence because two members of the same household could use it in very different ways. A workplace tool might likewise have distinct segments of daily users, even if their employer makes the purchase.
Keep the questions and conclusions at the same level. If individuals answer a survey about their own habits, you can describe patterns among respondents. You cannot automatically describe their entire households or employers. Record whether a person is a user, buyer, decision-maker, or some combination, and consider how you will handle people who hold multiple roles. If your intended action is a direct message or a change to an individual experience, person-level segments may be the clearest choice.
Use households when needs and decisions are shared
A household can be the right unit when spending, resources, or product use are coordinated across members. Home internet service and shared grocery planning are examples where one person’s answer may not capture the full decision. Household segmentation can highlight circumstances such as the number of people sharing a service or whether needs change across members.
Define what counts as a household before collecting data. People who live together do not always share budgets or decisions, and one respondent may not know everyone else’s preferences. You can ask about observable household characteristics and decision processes, but avoid treating one person’s opinions as a consensus. If you survey more than one member, set a rule for linking their responses so the household is not counted multiple times without your knowledge. When an action targets the home but research captures only one resident’s view, label that limitation plainly.
Use accounts when organizations are the customers
For business-to-business research, an account is an organization or defined customer entity. Account-level segments may support decisions about onboarding, service models, or outreach. Useful inputs can include an account’s needs, buying process, and how its teams use a product. Size or industry can help describe an account, but those labels alone may not explain what support it needs.
Accounts contain people with different priorities. A purchaser may focus on procurement requirements while a frequent user focuses on daily workflow. Interviewing one contact can reveal that person’s perspective, not an organization-wide view. Decide whether branches, departments, subsidiaries, or a parent company count as separate accounts, and apply that rule consistently. Where possible, gather perspectives from more than one role and note disagreements rather than forcing them into a single account opinion.
Keep collection, analysis, and action aligned
Before building segments, make a short unit map: what you will group, who will provide information, and who will receive the resulting action. These need not be identical, but the connections should be explicit. For instance, interviews with several employees might inform an account-level profile, provided you have a defensible way to combine their accounts of the organization. A survey of individual shoppers might inform a household offer only if it includes enough information about shared purchasing to justify that step.
Check for duplicate units and uneven representation. A dataset with five respondents from one account and one from another should not silently treat all six answers as six independent accounts. The same issue arises when several household members respond. Document how responses are combined, which disagreements remain, and what information you chose not to collect. Use only data needed for the decision, especially when linking people to homes or employers.
Finally, test whether each segment can guide a distinct action. If the unit is a person, can you improve that person’s experience? If it is a household, can you address a shared need? If it is an account, can you adapt how you serve that organization? If the answer is unclear, revisit the unit before refining the segment labels.
