Marketers are often expected to justify ideas with evidence.
You might know that a part of your website isn’t working as well as it should. Or you may have been asked to explore a new feature or module, but need to determine whether it’s worth the cost. In many cases, the challenge isn’t finding data, it’s explaining what that data means, and why it matters, to people who aren’t digital specialists.
This is where data storytelling becomes essential.
Data storytelling helps marketing managers explain complex information in a way that’s clear, relevant, and actionable, supporting better decision-making across councils, government organisations, not-for-profits, and beyond.
What is data storytelling?
Data storytelling is the practice of using data, context, and narrative together to explain a situation and support a recommendation.
Rather than sharing dashboards, spreadsheets, or charts on their own, data storytelling focuses on answering a few key questions:
- What is happening?
- Why is it happening?
- Why does it matter?
- What should we do next?
For marketing managers, particularly in the public sector, this approach helps turn performance data and user insights into information that decision-makers can understand and use with confidence.
Why data storytelling matters
Marketing teams regularly work with complex data sets, user behaviour insights, and competing priorities. However, internal stakeholders may only see a snapshot, or may be relying on assumptions rather than evidence.
Effective data storytelling helps to:
- Justify investment and budget decisions
- Explain digital performance clearly and simply
- Reduce subjective decision-making
- Align stakeholders around a shared understanding
- Make recommendations easier to support and approve
By focusing on the story behind the data, you move the conversation from “what do we think?” to “what do we know?”
Step 1: Understand and explain the current state
Before proposing a solution, it’s important to clearly understand how things are currently performing.
Setting the scene provides context and helps stakeholders see why change may be needed.
What to look for
At this stage, aim to understand:
- How the website or feature is performing now
- What your goals or benchmarks are
- Where users are experiencing difficulty
- Where opportunities for improvement exist
Common data sources
You don’t need large or complex data sets to tell a useful story. A small number of well-chosen sources is often more effective.
Usability testing
Usability testing helps you understand how real users interact with your website. It can reveal points of confusion, unmet needs, and inefficiencies that aren’t always visible in analytics alone.
Heatmaps
Heatmaps show how users interact with a page, including where they click, scroll, or pause. They are particularly useful for identifying:
- Content that is being overlooked
- Links or buttons that users expect to be interactive
- Mobile usability issues
- Areas of high or low engagement
Google Analytics (or GA4)
Analytics data provides a broader view of user behaviour. Useful reports include:
- High-traffic pages
- Pages with high exit or drop-off rates
- User flows between key pages
- Engagement trends over time
Together, these insights help paint a clear picture of the current experience.
Step 2: Test the proposed solution
Once you understand the problem, the next step is to test whether a proposed solution is likely to work.
For example, if a new website module has been suggested, testing allows you to validate the idea before committing time and budget.
What to test
At this stage, focus on understanding:
- Whether the solution meets user needs
- How users interact with it
- What could be improved before implementation
Useful testing methods
Usability testing
Testing a prototype or mock-up shows how users interact with a proposed solution and whether it is intuitive and effective.
Tree testing
Tree testing helps assess whether users can find information easily within a proposed structure. It’s particularly helpful when reviewing navigation or content grouping.
Focus groups
Focus groups provide qualitative feedback on language, expectations, and perceptions. This can be especially valuable for public-sector organisations where clarity and trust are critical.
Testing strengthens your recommendation by showing it is evidence-based and user-informed.
Step 3: Tell the data story
Collecting data is only part of the process. How you present it is just as important. Good data storytelling focuses on clarity, relevance, and outcomes.
Key principles of effective data storytelling
Know your audience
Consider who you’re presenting to and what they care about, whether that’s cost, risk, community impact, or service efficiency.
Lead with the insight
Start with the key takeaway, then support it with data. Avoid expecting stakeholders to interpret charts on their own.
Keep it simple
Focus on the most important findings. Avoid overwhelming your audience with too much detail.
Be clear about recommendations
Clearly explain what you are recommending, why it’s needed, and what the next steps are.
This is the “so what”. The point where data supports action.
Here’s an example of teaming data with the “so what”:
Data: Traffic is up 18% this month
So what: This uplift is driven by the new campaign going live and it should help increase enquiries over the next few weeks.
Turning data into decisions
Good data storytelling relies on real user insight. When you understand your audience, it becomes easier to explain what’s happening, why it matters, and what to do next. If you’re considering user research and would like support, get in touch with our team. We embed user research into every digital project to help you build a clear, evidence-based case for your next digital project.