Expert Insights

Using Audience Intelligence for Campaign Planning

Michael Brito, Zeno Group, on how & why to use multi-segment audience intelligence for planning campaigns that drive exponential engagement & growth.

Michael Brito
July 09 · 4 min read

Want to drive more campaign impact with laser-focused content? Digital strategist and keynote speaker Michael Brito explains how to build better audiences for your ads with multi-segment audience intelligence.

Transcript:

Ok, so you have a product that you want to sell to IT professionals. Maybe it’s a data or cloud platform, enterprise security software, ERP, Unified Communications … whatever.

And let’s assume you are planning for a full-scale integrated marketing campaign... media relations, social media, influencers, demand gen, search and display. You even have an employee activation plan. You’ve gone through rounds and rounds of edits to your messaging, creative. You have all your KPIs documented. The CMO is bought in. Your agencies are ready to go. Everyone is excited. And then you launch.

And then you scratch your head wondering why the campaign isn’t performing the way you expected. Maybe it’s the agency. Let’s blame them. The targeting is off. The ads are wrong. The website broke. But the question I have for you is … do you really know who your audience is? And if so, did you spend time segmenting that audience in order to be as laser-focused as possible?

The reality is that all IT professionals have one thing in common. They work in IT. But outside of that, there are hundreds of variables and characteristics that make them unique. Now Google is your friend but it's only going to give you limited information. Now I am pretty good at using Google (yes, I use boolean) and I found some good nuggets. This one from IDG.

And there’s some really good data here, which I will highlight here:

  • Innovation is one reason why IT decision-makers seek new platforms.  So those companies that are integrated AI and Machine Learning into their software are really driving demand among their audience.
  • IT looks to influencers to validate the purchase. I have said this many times. It can be used to inform the creation of an influencer marketing program so you can surround your audience with trusted, game-changing content.
  • They consume content. A lot of it
IT looks to influencers to validate the purchase. I have said this many times. It can be used to inform the creation of an influencer marketing program so you can surround your audience with trusted, game-changing content.

Ok, now moving down to the Slideshare presentation. Here is an interesting nugget based on what we just saw about content. We can see that download consumption varies by the topic or technology.

And this data is from Adobe.

I’m familiar with this study because I have referenced it before. The study examined IT decision-makers’ top concerns for 2020.

  • Data security was a top concern
  • AI Implementation
  • Creating a better customer experience using Machine Learning
  • Driving innovation

 

I also found this to be interesting - what factors influence purchase decisions:

  • Faster integration
  • AI-powered technology

 

Multi-segment Audience Intelligence

I want to introduce a new concept called multi-segment audience intelligence. And the process involves dissecting and clustering sub audiences – analyzing each of their sharing habits, conversational patterns, demographics, and psychographics in order to get actionable and defendable insights that you can use to make data-informed decisions.

Multi-segment audience intelligence involves dissecting and clustering sub audiences – analyzing each of their sharing habits, conversational patterns, demographics, and psychographics in order to get actionable and defendable insights that you can use to make data-informed decisions.

For the purposes of this blog post, I did a quick analysis of IT decision-makers.

And our cluster analysis shows each of these sub-audiences and how they are connected. Because I work with a lot of B2B and technology companies, I can tell you that each of these IT audiences is very different - not just in terms of job titles or functions, but also in their interests. Even within the C-suite and developers which would be a separate analysis, you’d find very different interests and characteristics.

Building an audience matrix

Moving on to what I call an audience matrix. The top row represents each of the audiences we just looked at.

In the columns, I added a few variables that I like to use:

  • Which brands do they follow and talk about.
  • What’s the context of that conversation?
  • What topics are they talking more or less about over time.
  • What’s top of mind for them right now, today.
  • What software language do they use to develop code (obviously this isn’t applicable to each audience)
  • What media publications are they reading when it comes to specific topics. In other words, when reading about business, are they reading the Wall Street Journal, NY Times, Business Insider, or all three. Maybe for security-related topics, they prefer ZDNet and Dark Reading. And then perhaps for content related to AI and data, it’s the Enterprisers Project.
  • And lastly, what hashtags do they use in social media.

Now I don't have time to do a full analysis and fill this matrix in, but if I were planning a campaign, I would go through this exercise and share it with my internal stakeholders. You’d be surprised at how different each one of these audiences is from one another.

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