When someone tells us their social learning experience-- whether that's a community of practice, cohort, social learning network, or something else-- has fallen flat, the first thing we ask is: did you do an audience analysis?
The second: what did you aim to uncover in your audience analysis?
Often, the audience analysis / learner analysis stops at: age, job description, performance goal, and level of expertise.
The problem is that information is too surface level. If that's all you're getting, you don't really understand how to connect with these people as people.
Knowing your audience deeply gives you the tools to:
write compelling copy
craft experiences that demonstrate immediate value
schedule structured learning in practical ways
optimize tech stacks and user interfaces for improved adoption
connect people in conversation
meaningfully incentivize and promote continuous learning
Over the course of the next three articles, we're going to walk you through more effective audience analysis and help you leverage what you learn.
Audience Analysis Step 1: Gather Data
Identify Your Audience
The first thing you need to do is ask yourself: who is this learning experience for?
There may be more than one audience. You'll want to get to know them all.
Now, that doesn't mean if you have 200 job codes going through the program you need to do all of the things we're going to walk through for each of the 200 different job roles. In this case, you'll need to figure out the common ground.
For example, you may have a big class of new hires from all different parts of the organization. You might break the audiences down by company function: technical staff, sales and marketing, HR, etc. Alternatively, you could split it by experience level: career transition, new to the workforce, early career, experienced employee.
Audience analysis isn't just asking some questions about how someone does their job and moving on. In fact, it isn't even just interviewing users (we'll talk more about effective ways to do that in Part 2).
It's about uncovering your audience's needs, desires, and disconnectors. To get people consistently participating in social learning, you have to make the "What's in it for me?" very clear, and you also need to make it easy to access. We use data gathering as an opportunity to learn more about:
how they experience the work environment / tasks
pain points / challenges to overcome
sources of inspiration
apathy triggers (the things that make people roll their eyes and disconnect)
To do this, we advocate for a UX research style approach to audience analysis. We start by populating empathy maps. We like Paul Boag's model.
Empathy maps are simply tools to categorize data from these sources. They aren't the end product.
We use data and our empathy map notes to craft audience profiles, which help us contextualize the learner population in meaningful ways. These are fictionalized profiles that humanize the data-- not a representation of any one individual.
Our data gathering involves all or some of the following:
User / user representative interviews - not to be confused with SME interviews
System reports (e.g., incident data, customer feedback, performance review data, HR complaints, learning content access data)
Assessments (e.g., on the job activities, LMS data, questions asked during interviews, survey responses with a correct answer.)
Research (e.g., association data, workforce reports, blogs from individuals similar to our audience)
It typically takes us 2 - 4 weeks to complete these activities, which culminate in our findings and recommendations plus a strategy-- the game plan, if you will.
This may seem like a lot, but I assure you it saves a ton of work down the line, and it lets us craft an experience designed to truly engage learners in meaningful ways. We don't just want to ask people to get online but to invite and entice them to continually participate in the experience.
In our next post, we'll talk more about how make the most of your audience interviews and focus groups.