Audience profiling is like building a persona but let me clarify. Many marketers go through a persona brainstorming exercise using qualitative insights and hope. There isn’t any rigor or data analysis used in the process. You can actually find and download persona templates online, add in your customer information and call it a day.
This is not the way that I like to build audience personas.
Don’t get me wrong. Building a target audience profile does require a level of qualitative analysis and context. But it must be driven by audience profiling data and analysis.
Audience profiling and segmentation is the process of using social media data to build a target audience profile based on conversational behaviors, and media insights. Seems like a lot of buzzwords but let share an audience profile example below.
I started with landscape analysis of blockchain and cybersecurity. Based on several parameters of measuring influence, I built an audience group that consisted of 600 or so journalists, analysts, writers, authors and columnist.
What is an audience profile in social media?
Below is an audience profile of Daniel Newman, a Principal Analyst of Futurum Research. The purpose of profiling audiences is to understand their interests, motivations, characteristics and conversational patterns.
What information is included in an audience profile?
Daniel’s target audience profile example only scratches the surface of the type of data that can be included. Of course, basic demographics and psychographics are always included in analysis like this. Profiling audiences’ media consumption is also a common data point included. This simply means, that we can identify which media outlets that certain audiences have an affinity for based on historical sharing patterns.
Daniels audience profile also shows a level of conversation analysis over a period of time. You can see that over the course of one year his interest in blockchain has increased two fold. Conversational data shows what topics, trends, and stories are top of mine for either individuals like Daniel or groups of larger audiences.
Tracking podcasts, influencers, and events affinities are also a common data points.
Audience profiling for one individual does provide actionable insights for research and building an influencer marketing program. But there is a benefit from analyzing larger audiences as well. You can see from the below data what industries the 600+ influencers are talking and writing about. But keep this in mind–this changes all the time and is dependent on several market and business variables.
Target audience profiling will also look at both the branded and unbranded conversation. The branded conversation explores what an audience is saying about specific companies in the industry. The unbranded conversation are topics that are “top of mind” for the audience related to security.
Below you’ll see that 95% of their conversational volume is unbranded and represents an opportunity for brands to own the conversation. You’ll also notice which security companies are mentioned the most by the influencer group. This is helpful for share voice analysis.
When building an audience profile, its critical to explore the unbranded conversation in more detail.
The below data shows which security-related topics that the audience is talking about the most, purely from a volume standpoint. The value in reviewing this data is that you can use the trending topics to inform social content, bylines, blog posts, executive thought leadership and so on.
A drill-down of the blockchain media conversation illustrates how important this topic has become over the last 12 months, specifically among target audience profile. You’ll notice when Bitcoin started trading at over $11,000 dollars, the conversation skyrocketed.
This may seem like a lot of information. But building audience profiles like this one takes the guesswork out of marketing. It ensures that hope is no longer the strategy and that audience analysis is the infrastructure.
Here’s an example of AI analysis I did last year which uncovered the AI audience’s top media affinities.
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