Audience profiling - example & learnings
If you work in marketing, sales, community management there is a good chance that you are working with lists: lists of clients, lists of prospects, lists of community members, lists of followers, list of key opinion leaders, list of influencers, list of competitors ...All these lists are audiences that you need to understand in order to:
segment audiences & identify personas
identify content that resonates with your audience
spot trends
identify influencers and potential content partners
structure campaigns
assign territories
The good news is that thanks to social intelligence and eCairn Audience Profiling service, it is now possible to do this quickly with a small budget.
Instead of a long description of what we mean by audience profiling, we are sharing below an audience profiling performed on the followers of the @slackapi account on Twitter.
This is done on a public audience.
Starting with these 14.6K followers, we automatically remove organizations, media, bots & accounts that are no longer active.
Then, we enrich the list of valid personal accounts with data points including LinkedIn, Facebook, Instagram, Github Profiles, bios, pictures, content, and "links shared" and we performed analytics and text mining on the resulting data.
Here is the outcome:
Personal Profiles
On this map, the circle on a city is green, yellow, blue, and white depending on the presence of top, high ann medium influencers in that city.
On this map, the circle on a city is green, yellow, blue, and white depending on the presence of top, high ann medium influencers in that city.
On this map, the circle on a city is green, yellow, blue, and white depending on the presence of top, high ann medium influencers in that city.
2. Professional Profiles
Looking at what companies these people work for we see, no big surprise, that a huge number of slack employees follow their company account.
We then find people working for some large US tech firms then, freelancers and entrepreneurs.
This is actually quite interesting for sales. Zooming on the Microsoft people, here are a few people following slackapi:
Screen-Shot-2020-08-12-at-4.16.07-PM.png
Screen-Shot-2020-08-12-at-4.16.07-PM.png
Since we provide the Linkedin URL (and github) for these people, it is easy to send an intro message/connection request, mentioning "since you're following our Twitter account" ...
Looking at what people put in their bio, we see that @slackapi followers are clearly software and tech people. The bios are 90% filled with tech keywords with only a few keywords like "husband", "dad" then "travel" and "music" showing up.
pro2.png
pro2.png
Interesting to see that "formerly/ previously" show up a lot. Maybe a sign that engineers keep connections with the companies they used to work for. That is something that could be leveraged in a referral program.
There are also many positive keywords too (love, enthusiast) and people writing for this audience should use a positive tone. Mining job titles, we find a lot of executive titles (CEO, CTO) and developers. However, titles span the full ranges of seniority.
pro1.png
pro1.png
3. Centers of Interest
Here are the top topics that these people use (removing politics and coronavirus), clearly these people talk a lot about Tech. "Share your idea and build amazing apps" is a tagline that would resonate with the audience.
ci1.png
ci1.png
The text cloud below is the same, but with a focus on Tech.
This audience uses hashtags a lot and #ai, #blockchain and #IoT are clear top trends.
ci2.png
ci2.png
These are the articles shared the most by this audience. A mix of tech and political articles.
Screen-Shot-2020-06-24-at-3.19.07-PM.png
Screen-Shot-2020-06-24-at-3.19.07-PM.png
In terms of domains, the audience is sharing mainly articles from medium, NYTimes and Github.
ci7.png
ci7.png
When we look at ho these people follow the most. Politicians, Tech gurus and VCs.
s3.png
s3.png
4. Network, Influencers & Personas
Looking at how the people within this list interact on Twitter, we calculate the influence of people and end up with this list of top influencers. The number is the influence and the radar logo is an indication of their reach.
s2-1024x917.png
s2-1024x917.png
When we plot the social graph i.e visualize it based on people following or engaging each other, we clearly identify a few clusters:
Screen-Shot-2020-08-12-at-4.31.56-PM.png
Screen-Shot-2020-08-12-at-4.31.56-PM.png
Some sub-groups may be interested to be managed as a specific audience:
API specialists, people who are interested in all APIs and how to combine APIs to build products
Community practices: More interested in the use case, business case, and the benefits of this API.
Large corporations: These groups can be used for ABM.
We also plot an Affinity Map based on the similarity of people's social graph i.e grouping people following similar people. Here is the Affinity Map for the SlackAPI followers:
Screen-Shot-2020-11-11-at-6.14.51-PM.png
Screen-Shot-2020-11-11-at-6.14.51-PM.png
When diving into one cluster, we clearly get a better understanding of the people in that group and can define personas. On the left is a text mining of the people's bios.
Screen-Shot-2020-11-11-at-6.17.25-PM.png
Screen-Shot-2020-11-11-at-6.17.25-PM.png
On the right a TF/IDF analysis of who these people follow most or less, compared with the people in other groups.
As a summary , this analysis can be performed on any list of people: members of your private community, leads, clients, employees and the insights are key to
better understand your audience,
develop content plan and source content that resonate with your audience,
identify influencers, micro influencers that will share your content, could partner with you on content or become speaker at your events
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