Understanding different user needs

You can't have a user-centric approach without knowing who your users are

You may want to target a specific audience because you know they drive demand for your work, or you may want to appeal to a wider range of people because the data has many different applications for social good.

Once you identify who your audience is, you can start to see common characteristics and patterns in the ways they interact with your data. Once you have an idea about the characteristics of your audience, you can start thinking about their data needs and goals, and then you can tailor content directly to their needs, provide specific types of service and support they’re seeking, and enable your product or service to resolve some of the challenges they’re experiencing. This is part of fostering strong, long-term relationships with your audience/customers/data users and also helps build a sense of loyalty over time and advocacy for better utilisation of data.

One effective method is to use analytics tools to track how people are interacting with your website or social media accounts. This can give you a sense of who your audience is (sector, profession, role, location), what they're interested in (standard metrics, benchmarking, bespoke analysis, insights, examples, guidance), and what kind of content they respond to (downloadable, interactive, technical, infographics).

Audience definition

TOOLS: Audience definition and segmentation

Audience segmentation typically enables people to match messages, products and services based on the specific needs and preferences of the audience. In the case of data user audiences, we might want to segment them by skill set or seniority, as well as the aspects above.

Even if you have a good grasp of your data users, audiences do evolve and it is worth reviewing periodically to ensure you continue to meet new data needs.

Let’s address one of these aspects in more detail...

A. Professional aspects: skill level, seniority, sector

Example audiences segmented by seniority/influence and by skill level:

Different approaches to different audiences

Data skill: For audiences with substantial data skills in terms of analytical proficiency, you may want to publish data with more detailed descriptions using applicable technical language, as well as options to take the raw data and analyse it in bespoke ways. They may want to know about any outliers in the data or any limitations and quality concerns. Experienced analysts will have a good understanding of how to utilise the data and may want to manipulate and present it in novel ways. For those with limited data skills, it may be more user-friendly to publish data stories with clear concise descriptions of the data (what the data says and its potential implications). See section below.
Seniority or influence: More senior audiences are likely to want a good understanding of the data and its potential implications in the most summarised and concise way possible, in order to use it to drive decision making.
Audience knowledge of topic: Audiences with intimate knowledge of specific topics may want more deep dive information alongside the data or are likely to require more detailed descriptions and analysis.
Audience attitude: Attitude and motivation may also shape how your audiences perceive and use the data you publish. This includes things like being motivated by seeking funding, improving performance, responding to statutory requirements, and also being safety conscious (from cyber safety to protection of organisational reputation).

Segmentation tools

For more detailed audience segmentation, there are many digital tools available, ranging in cost and sometimes sector specific.

If you have a social media presence and people following you on Facebook, LinkedIn, and Instagram platforms, then this can be a rich source information about your audience. Many of these platforms have built-in analytics tools though you may at some point want to invest in a tool designed for social media analytics.

These tools give you in-depth insights about your audience preferences (by the likes or interactions with your posts) and could generate potential new data users with similar social media profiles and data interests.