How to understand what motivates your audience

Knowing who your audience is gets you started. Knowing what motivates them is what gets your data story acted on.

Most data professionals default to demographics when thinking about their audience—job title, seniority, department. These are useful starting points, but they don't tell you why someone would engage with your insights or what would move them to act. Two people with the same job title can have completely different reasons for caring about the same data.

What you need to understand is psychographics: the interests, attitudes, goals, and concerns that shape how someone responds to information. And the most practical way to develop that understanding is through User Stories.

What User Stories are

User Stories are a tool borrowed from agile software development, where they're used to capture what an end user needs from a product. In data storytelling, they serve a different but related purpose: helping you understand what motivates a specific audience group, and how (where relevant) to frame your communication around that motivation.

A User Story for a data story audience follows a simple template:

As a [audience], I want [insert what YOU want them to want], so that [insert what motivates THEM to want it].

The structure might look like it's about the audience, but it's equally about you. You're working out how to connect what you need from them with what they care about.

Why motivation matters more than message

A common mistake in data communication is framing findings around your own motivation rather than your audience's.

Consider a data analyst who has completed a lifecycle analysis showing that a recently introduced product doesn't align with the company's environmental goals. The analyst needs different people in the organisation to understand the implications, but each audience has a different reason to care.

For a marketer, the concern is brand reputation. A User Story for this audience might read: As a marketer, I want to understand this product's lifecycle analysis, so that I can identify any reputation risk to our brand. That framing connects the analyst's finding to something the marketer is already motivated by. The subsequent data story leads with brand context, not environmental data.

For a product manager, the concern might be compliance or supplier relationships. Their User Story might read: As a product manager, I want to understand this product's lifecycle analysis, so that I can identify which supplier relationships need to be reviewed before this becomes a compliance issue. The same finding is framed differently and speaks to a different set of priorities.

A note of caution: framing your data story around what motivates an audience works well when their motivation aligns with the outcome you're trying to achieve. When there's a tension between individual motivations and collective outcomes, motivation framing alone isn't enough, and can sometimes work against you. But that's a deeper conversation for another post.

What User Stories aren't

User Stories are not a guarantee. Writing a User Story for an audience you don't know well requires making assumptions about their goals, their concerns, and what they value. And those assumptions might be wrong.

That's fine. The act of writing a User Story (of actively considering what motivates someone else) is itself valuable. It makes you think about why this person will care about what you want to share. Even an imperfect User Story can produce a more audience-aware communication than no User Story at all.

Treat your first communication as a learning opportunity. How your audience responds (what they question, what they ignore, what they ask for more of) will tell you more about them. Then, adjust from there.

Starting with empathy

User Stories are an act of active empathy. They ask you to temporarily set aside your own perspective on the data and inhabit your audience's instead. You move from communicating what you found (and what you found interesting) to communicating what your audience needs to understand.

Once you understand what motivates your audience, the next step is to understand how they prefer to receive information. This is where Empathy Spectrums come in.

The Data Storyteller's Handbook covers User Stories in full, including worked examples and templates. The online course and Rogue Penguin workshops develop the skill of writing them for real audiences.

Kat Greenbrook is a data storytelling consultant, author, and workshop facilitator based in Wellington, New Zealand. She is the founder of Rogue Penguin and the author of The Data Storyteller's Handbook.