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Published December 13th 2023

Introducing the Next Generation of Audience Analysis in Brandwatch

Social Panels is Brandwatch’s leading audience analysis feature in Consumer Research. It allows you to create large custom research panels of millions of online authors or niche stakeholder groups, break down your data by audience, or even create queries to research all conversations by a target audience group.

Social Panels were already unique in the social listening market for their scale and flexibility. But our latest updates are game-changing for users conducting market and audience research in Brandwatch. Now you can:

  • Build and analyze multi-source panels: Previously, Social Panels only worked with X (formerly Twitter) authors. Now, we’re bringing in more data sources, such as Reddit, other social networks, and online forums.
  • Complete the entire research workflow: Dive deeper into audiences you have discovered in your brand and topic research.
  • Create better quality and more complex panels: Create panels based on highly specific queries looking for identifiers in what people have talked about and filtering using other Brandwatch features.

What did we release?

  • Expanded social panel builder: Search for authors using longer search criteria for ‘mentions about’ in recent posts from the last 30 days. You’ll have up to 600 characters per search with full boolean support.
  • Reddit authors in panel builder: This new search field can now be used to search for Reddit authors as well as X authors.
  • Ready-to-use Reddit panels: Our experts at Brandwatch have built panels you can use straight away to find generational and interest-based audiences. Learn more about ready-to-use Reddit panels here.
  • Search by existing panel: Include or exclude lists of authors from any other Social Panel you have set up before. For example, quickly add a known group to a new research panel without having to recreate the search criteria or exclude a known list of spam accounts you want to always remove from panels you are creating.
  • Social panels from dashboards: This allows you to turn all the authors in a dashboard you are looking at into a panel. It will work with any filters you have applied in the dashboard, including all of Brandwatch’s AI-powered topic analysis and segmentation tools. Crucially, this also allows you to create panels with authors beyond X and Reddit, such as forums – or any source with author/username data available.

How does it work?

Let's use Tesla as an example to see how these new Social Panels features can be used to conduct even more advanced audience analysis.. Because Tesla is a brand that is talked about by many different audiences in many different contexts. 

Tesla is an automotive brand but also a tech brand. It’s a pioneering brand in the realm of sustainability, which also makes it a political brand. And it’s also a brand that is mentioned a lot by people in conversations that aren’t necessarily about the brand per se. 

This brand clearly exemplified the importance of having a better understanding of what highly specific audiences are saying about it. In a sea of general chatter, it becomes critical to cut through the noise to identify meaningful insights that can inform data-driven decisions.

And this is where Social Panels come in.

Defining your audiences

First, we need to build the panels of authors we want. Let’s go with:

  • Investors
  • Activists & Campaigners
  • Environmentalists
  • Automotive journalists
  • Tech journalists

These first five are relatively easy. We can build some good panels using a bio search as these people will often self-identify. Of course, we could expand from here, but for now, let’s say we’re satisfied with who we’ve found.

Now, how about some trickier panels?

  • Tesla owners
  • Tesla brand advocates 
  • Tesla brand detractors

To create these panels, we’re going to need a different approach. A bio search won’t cut it. We can start by creating a query to collect all mentions of Tesla across the web.

Once we have all this data, we can refine the search to tag all conversations where people specifically talk about being a Tesla owner or driver. We have all the boolean operators in Brandwatch at our disposal to create a tag looking for conversations like “I AND (drive OR bought OR own) NEAR (tesla OR “cyber truck” OR “model 3”).”

Now, if we filter our dashboard by this tag, we have a set of conversations by authors on many different platforms about being a Tesla owner. And with the click of a button, we can turn all the authors in this dashboard into a new Social Panel.

But advocates and detractors are going to be even harder. We could filter our data by sentiment but this is likely problematic. Many people might mention Tesla in a post that overall is negative or positive, but the sentiment is not aimed at the Tesla brand. Some might just be big fans of ‘Tesla CEO Elon Musk’. Some might be disappointed owners of Tesla stock when it’s taken a dip.

Fortunately, we have all of Brandwatch’s AI-powered analytics tools at our disposal to zero in on the right conversations to build the best, most relevant panels. In this case, we’ll use Custom Classifiers, our machine learning tool that trains a custom classification model by dragging and dropping mentions into different categories.

This lets us sort conversations into buckets for irrelevant or neutral posts, posts that are positive or negative but not in relation to Tesla, and finally, the ones we want: positive or negative posts about the brand itself.

Again, we can filter our dashboard by these two final categories to create our last two panels.

Breaking down data by panels 

Now, we can go back to our original brand query and break the conversations down by the panels we identified.

This allows us to build a far more nuanced ongoing understanding of how different audiences talk about our brand. We can set up a volume over time chart broken down by these panels to monitor when certain audiences discuss the brand.

Iris, Brandwatch’s AI assistant, is particularly useful here as it will detect and explain peaks for each of these social panels. For example, Iris has identified the big spike as brand advocates talking about Tesla and it’s driven by reposts of this post that Elon Musk shared in August.

Iris is even more helpful in identifying peaks like this where the human eye would miss it. For example, peak A detected here is within the investor conversation, which is a much smaller volume because it’s a smaller panel of people. We can see it better once we remove a few panels.

If we ask Iris to summarize this peak, we can see that it has identified a flurry of activity within this community around Tesla’s Q2 earnings report.

We can use this monitoring broken down by panel to identify moments of opportunity and risk for the brand and cut through the noise to zoom in on the trends within the audiences we care most about.

As well as monitoring over time, we can dig into and compare how each of these panels talk about the brand. For example, we can categorize conversations using keyword rules to break down by key topics we want to learn more about.

In Consumer Research, you can chart social panels against these categories or any other segmentation of data with complete flexibility to build reports that reveal insights and tell compelling data stories.

Here, for example, we can see that environmentalists are most likely to be talking about Tesla in the context of sustainability, investors talk most about price, and brand advocates and owners talk about the aesthetic and design of Tesla vehicles.

For any of these topics, we can drill down and compare how each audience is talking and better understand how messaging is pulling through to these key audiences and to learn how to better engage them around key topics.

Researching panels

We can also dive deeper into the panels we have built and understand everything they talk about, even when they are not talking about Tesla.

This allows us to develop detailed target personas or better understand our brand's advocates or detractors to build more personalized marketing and communications strategies to target them with.

Book a demo today to learn more about how Brandwatch Social Panels can help you build a deeper understanding of the audiences that matter to you.

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Falcon.io is now part of Brandwatch.
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Existing customer?Log in to access your existing Falcon products and data via the login menu on the top right of the page.New customer?You'll find the former Falcon products under 'Social Media Management' if you go to 'Our Suite' in the navigation.

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Brandwatch acquired Paladin in March 2022. It's now called Influence, which is part of Brandwatch's Social Media Management solution.Want to access your Paladin account?Use the login menu at the top right corner.