Target audience analysis – how to do an analysis that steers content, channels and messaging

What is a target audience analysis?

A target audience analysis is a structured mapping of who you want to reach: who they are, what they need, how they make decisions and where to find them. The purpose is to base decisions about content, channels, messaging and product on data instead of assumptions. A finished analysis answers three questions: who should we talk to, what do they care about, and how do we reach them?

The term is often confused with related concepts. If you want to untangle the difference between target group, customer group and personas, we have a separate guide for exactly that. Here we stick to the analysis process itself: how you actually do it.

Why you need a target audience analysis

Without a clear picture of who you are addressing, every decision costs more. You write content nobody searches for, advertise in channels where your audience is not present, and craft messages that miss the mark. An analysis gives you the opposite: a shared basis for content, channel choice, messaging and sometimes product decisions too.

It is also the starting point for the work that follows. Accurate keyword research depends on knowing how the audience phrases its problems, and search intent cannot be interpreted without knowing who is searching. The same goes for positioning – you cannot choose how to stand out until you know who you are standing out from. Our guide to SEO strategy covers how the analysis fits with the rest of the channel work.

The effect is measurable. According to McKinsey, companies that reach the right person with the right message earn measurably more – typically 10–15 per cent higher revenue, with a company-specific range of 5–25 per cent depending on industry and execution. Knowing who you are talking to is therefore not a soft issue, but one that shows up on the bottom line.

Target audience analysis step by step

Most target audience analyses follow the same logic as the STP model from marketing: segmentation, targeting and positioning. Below is the process in five concrete steps.

1. Gather data. Start with what you already have: customer data, conversations with the sales team, support tickets and web analytics. Add external statistics and research where your own data runs out. The goal is to understand needs and motivations, not just who the customer is on paper.
2. Segment. Divide the market into groups with similar needs and behaviour. A small number of clear segments is always better than many vague ones. More on the bases for segmentation below.
3. Choose target segments (targeting). Not all segments are worth prioritising. Weigh them by size, purchasing power, how well they match your offering and how easy they are to reach. Actively ruling out segments is part of the work.
4. Position the message. For each chosen segment: what is the most important thing you need to say to become relevant? Positioning is about the place you want to occupy in the minds of that particular group, relative to the alternatives.
5. Document. Pull the insights together so that the whole team can use them. A common format is to turn the segments into personas – that makes them easier to write and design for. We explain how to build them in our guide to creating personas. Personas are one possible outcome of the analysis, though, not the analysis itself.

Segment your target audience: demographics, psychographics and behaviour

Segmentation is the core of the analysis. You can divide an audience on several bases, and the best analyses combine them rather than stopping at one.

• Demographics – age, gender, income, education, family situation. For B2B: industry, company size, role and decision-making authority. Easy to measure, but rarely tells you why someone buys.
• Psychographics – values, attitudes, interests and lifestyle. These explain the motivations behind decisions and sharpen your messaging.
• Behaviour – how someone actually acts: purchase frequency, loyalty, how they use the product and where they are in the buying journey.
• Geography and situation – where the customer is and in what context the need arises. Sometimes the location or the occasion matters more than who the person is.

A complementary way of thinking is jobs-to-be-done: the customer "hires" a solution to get a job done. This lens is useful for shifting the focus from demographics to the real need – but it does not replace the other bases; it sharpens them.

Where do you find data about your target audience in Sweden?

An analysis is only as good as the data behind it. Distinguish between first-party data – your own customers, CRM and web analytics – and secondary data from reports and statistics. First-party data is always worth the most, because it describes your customers specifically. Secondary data fills the gaps and provides context.

• Your own sources – CRM, GA4 audience insights, search data in Google Search Console, support tickets and conversations with sales. This is where you find the patterns unique to your business.
• The Swedish Internet Foundation (Internetstiftelsen) – its report The Swedes and the Internet 2025 (Svenskarna och internet) is a solid Swedish primary source on digital behaviour. Almost all Swedes, around 97 per cent, use the internet, and roughly four in ten use AI tools such as ChatGPT.
• Statistics Sweden (SCB) – demographics, income and household statistics at the level of the Swedish population.
• Meta and LinkedIn audience insights – aggregated data on interests, roles and reach, particularly useful for estimating how large and reachable segments are.

Target audience analysis in the AI era

AI changes the analysis in two ways. The first is as a research tool: with deep research tools and language models you can compile segments, summarise reports and test hypotheses faster than before. One important warning, though: AI-generated "synthetic personas" are based on probabilities, not on your customers. They can be a starting point for hypotheses, but they never replace real customer data. Never let them become the only basis.

The second is the link to AEO. A modern target audience analysis should map what your audience asks AI assistants such as ChatGPT, Gemini and Perplexity about your product category. Those questions are a new data source – they reveal how the buyer thinks – and they decide which content is cited and mentioned in AI Overviews and other AI answers. The stakes are concrete: if the answers about your product are missing, an AI tends to answer "no" rather than "don't know", and then you lose the deal before it has even begun. Our guide to organic marketing covers how this AEO shift affects the whole organic channel.

Target audience analysis – template and example

A good template forces you to make the decisions that make the analysis useful. Whatever format you use, your template should cover the following for each segment:

• Segment name and short description – who the group is in one sentence.
• Size and value – approximate volume and how much the segment is worth.
• Needs and motivations – what they are trying to achieve and what stops them.
• Channels – where they are and how you reach them.
• Message – the most important thing you need to say to become relevant.
• Data sources – what the conclusions rest on, so that the analysis can be updated.

AUDIENCE ANALYSIS — draft

=== SEGMENT 1 ===
SEGMENT NAME & DESCRIPTION
—

SIZE & VALUE
—

NEEDS & DRIVERS
—

CHANNELS
—

MESSAGE
—

DATA SOURCES
—

Template: SEOS Design — seosdesign.se

A short example makes this concrete. Imagine a B2B company selling a bookkeeping tool. One segment could be "early-stage solo founders": small companies, often a single person, who do their own bookkeeping and have no finance background. Their motivation is to stop spending evenings on receipts and to avoid mistakes with the Swedish Tax Agency (Skatteverket). You find them in Google searches for concrete problems and in LinkedIn groups. The message becomes "bookkeeping with no prior knowledge – done in minutes", based on the company's own support tickets plus Statistics Sweden data on new businesses. A clear segment, and a clear way in.

When do you need a formal target audience analysis – and when is gut feeling enough?

Not everyone needs a full-scale analysis. A sole trader with five customers knows their market well, and spending hours documenting audiences would be wasted effort. In that case it is often enough to write down who you sell to and why, and adjust as you go.

The need grows with complexity. As soon as you have several segments, a team that has to pull in the same direction, or money spent on advertising and content, a documented analysis quickly pays off. The rule of thumb: the more people who make decisions based on the picture of the customer, the more valuable it is to write that picture down and share it.

Common mistakes in target audience analyses

The same traps come up analysis after analysis. Avoid these:

• "Everyone" as the audience. If you want to reach everyone, you reach no one. A broad audience waters down your messages.
• Demographics without motivations. "Women aged 30–45" says nothing about why someone buys. The basic data has to be supplemented with needs and motives.
• One-off documents. An analysis that is written once and never updated quickly goes out of date. The market moves – let the analysis move with it.
• Unsourced statistics. Figures that circulate without a clear source are easily passed off as fact. Always link to the primary source, and trust your own data rather than figures you cannot trace.

Want help producing an analysis that actually guides your content, channels and messaging? Get in touch and we will happily talk it through in an initial call.