Today’s B2B buyer journey is more complicated than ever. There are several reasons why this is a fact. First, B2B buyers are skewing much younger as millennials are getting promoted, managing large IT organizations, and many are entrepreneurs and launching companies. This didn’t just happen overnight either. In 2015, Google released some research stating that nearly half of all B2B researchers are millennials. According to the report, 18- to 34-year-olds accounted for almost half of all B2B purchase decisions.
Millennials are a driven generation, and for the last 5 to 7 years, they have been rising in the ranks in corporate America. They are digital natives and grew up using the Internet and social media to communicate with friends and family. That behavior does not change just because they are working for an enterprise company and making investments in IT and technology.
The second reason is more about cultural norms. As consumers of products and software, our attention spans have diminished, and we have difficulty focusing. The Internet is one of the main reasons, but that has given birth to wicked fast computers, apps that allow you to manage your entire life from your phone, and the need to always be in the know and connected.
In a nutshell, today’s buyer is all over the place. They are multitasking on several devices at once and at the same time chatting and texting with 15 different people.
Notice the B2B buyer journey below. This shows all the entry points where buyers might realize that they need to purchase software. The journey is not even close to being linear. It’s unpredictable, sporadic, and changes for various reasons–personal decisions, business need, etc.
One thing to note here is that buyers spend most of their time researching products and services on Google, reading industry white papers, blog posts, and e-books, and they are always seeking feedback and direction from industry peers, colleagues, and influencers.
This buyer journey might seem overwhelming and complicated, especially for the B2B marketers who want to reach them. That’s because it is.
It’s also an opportunity to use data and analytics to understand behavioral patterns and conversations that buyers have as they weave in and out of this crazy purchase journey. Every entry point and purchase factor below can inform a marketing program, advertising campaign, editorial approach, and digital content strategy. Additionally, third-party validation can reinforce purchase decision-making and accelerate the buying cycle. In this context, third-party validation could be in the form of B2B influencer marketing or even through a formal customer advocacy program.
There are a few key takeaways to better understand the buyer journey. First, it’s dynamic and changes daily. Second, audience’s expectations of technology also change as the speed of innovation increases. And lastly, just because one group within a specific audience behaves a certain way doesn’t mean that all the audience members follow suit. This makes it almost impossible to reach a target audience with branded content.
Just wait until Gen Z starts running the business.
Even though we’re talking about the B2B by your journey, audience analysis is just as crucial for consumer brands, especially when trying to analyze the shopper journey and, more specifically, Gen Z shopping habits.
What is Audience Analysis?
The textbook definition of audience analysis is a “process used to identify and understand the values, behaviors, interests, attitudes, and conversations of different groups of people.”
For me, audience analysis is about getting up close and personal with target consumer groups and getting a 360-degree view of their innermost being. I know, it sounds a bit weird in a Jennifer Anniston, romantic-movie-sort-of-way. But the more you know your audience, and I mean, really know your audience, you will have higher likelihood of delivering a memorable customer experience.
Why is Audience Analysis Important?
An audience analysis isn’t just important. It’s critical to the success of your business survival. I am being overly dramatic. But having an audience centered approach will ensure that your marketing and communication programs are successful.
But it has to be more than just a few bullet points on a PowerPoint slide or a screenshot from an eMarketer report. A buyer persona template that you downloaded from the Internet and filled out during lunch won’t cut it either.
An innovative and effective audience analysis will take you from “hoping” to “knowing” that you are building a plan informed by defendable data and will deliver business value and marketing ROI. Understanding an audience means that you know everything about them. Everything.
And here’s the best part.
After your present the results of your campaign at the company QBR and show your colleagues how you delivered well beyond performance expectations, you will become even more valuable than you are today. Plus, knowing more about any particular audience is good for long-term career growth and personal knowledge.
Why is it Important to Know Your Audience?
To know your audience, you should identify what they say at every customer touchpoint throughout the buyer journey. Of course, the trigger words and target keywords and phrases will be a priority when analyzing audiences. However, it’s also essential to know the context, sentiment, and emotional factors of those conversations.
It’s a little more advanced than identifying, clustering, and tagging positive, negative, or neutral sentiment. An analysis that focuses on the psychological and emotional factors of what your audience members are posting online will give you insights into how they feel, what they care about, and their attitudes and beliefs. More importantly, it can reveal “why” they think the way they do and “why” they care about specific products, services, cultural issues, and even politics.
Knowing your audience’s attitudes and behaviors goes beyond just marketing too. It’s a best practice to know your audience when communicating anything specific to product launches, company initiatives, and other public relations-related announcements.
How to Build an Audience
Audience analysis is art but mostly science. Together, human intuition and data-driven insights can identify target audiences, where to find them, and how best to engage them. There are several ways to build and analyze the audience based on your goals and objectives.
Although demographic information, age range, economic status, and other audience information may be hard to find for some audience members, this type of data isn’t that critical.
This type of audience building is based on social analytics. There is some demographic audience analysis that can be done. Still, the insights will show more about the audience expectations while gathering information during the buyer journey, the audience’s perspective on technology, software, and general business issues.
Specialized Audience: This type of social media audience analysis begins with a bio search and is effective for more technical audiences like engineers, developers, IT decision-makers, and the C-suite, mainly because they aren’t shy about telling the world what they do for a living.
For example, finding engineers or developers who are talking about #AIOps, #DevOps, or Robotics Process Automation (RPA) would require a combination of bio search and public social media conversations. Other specialized audiences like technology journalists, analysts, architects, real estate agents, physicians, nurses, and human resources professionals can be built effectively using this methodology. Here’s an audience analysis example of a developer audience.
Affinity-based Audience: This approach is suitable for finding a like-minded intended audience with similar interests, affinities, attitudes, and beliefs. A target audience analysis and segmentation use a combination of bio search, follower relationships, and social media conversations as a data source. So you can use this architecture to build niche audiences like millennial sneaker heads who live in New York, prefer drinking craft beer, and listen to 90’s R&B & Hip Hop or Los Angeles Lakers Fans who live outside of Los Angeles. This is how you would start brand audience analysis by simply analyzing a brand’s social community.
Micro-Audience: These are smaller audiences (<500), consist of influencers, and are built for the purpose of real-time content marketing or organic influencer engagement. The audience size is large enough to extract directional insights to inform content yet small enough to use to create highly-targeted creative assets.
An Overview of Other Types of Audience Analysis
So far, we have talked about using social analytics to build audiences. This is an area where I have done most of my work over the last 10+ years.
It should also be noted that when talking with clients or other industry pundits about audience analytics, it would be wise to talk about the sources of data and the approach first. Mainly because a lot of different people define audience analysis differently.
That said, let’s explore a few different other audiences you can analyze using various data sources.
Using Web Data for Audience Analysis
Using web analytics, you can analyze audiences coming to your website through various online channels. You can segment audiences based on-page search or other forms of advertising to see how they interact with multiple forms of content on your website. You can track conversion rates or pages per visit or top-performing content.
Google Analytics also provides interesting data related to web visitors. For example, they can give you the basic demographic analysis related to country, city, or area of interest based on their historical browsing behavior.
Google Search Console also gives you information related to the search queries that specific audiences are using in google and whether your website is actually showing up in the search results. I might refer to this as a website target audience.
Using Primary Research for Audience Analysis
Audience research using survey data is another way to understand certain Groups of people. This is also known as primary research, and it’s more complicated and expensive than most people think.
One of the most challenging aspects of primary research is determining what questions you want to be answered. For example, what information do you actually want to know about who they are or what they care about?
It’s also important to carefully instrument a survey so that it’s fast, easy to fill out, and makes sense to those filling out the questionnaire. Many research firms use incentives to motivate people to participate in the questionnaire.
Survey data can get very expensive with more sophisticated and specific audiences. For example, surveying the C-suite or executive audience would be very expensive compared to a millennial audience interested in music or sports.
It should also be noted that survey data will only give you the information that you ask about. That means you have to have a hypothesis about certain audience behaviors before starting.
Focus groups can also be considered a type of audience analysis. Depending on the format of the focus group, one can learn a lot about an audience. If it is a free-flow conversation and less structured, there might be an opportunity for an insight you had not thought of before the focus group. In other cases, where there is a more structured Q&A, you will either confirm or deny a particular hypothesis of an intended audience that you wanted to know about in the first place.
Analyzing Audiences for Paid Social Media
Another form of audience analysis is when building out paid media targets a segmentation on sites like Facebook, LinkedIn, and Twitter. This type of audience building is less about analyzing interests and characteristics but creating an audience to target using paid media and advertising.
For example, on LinkedIn, you can build an audience consisting of certain job types and functions, colleges attended, certain degrees in milestones achieved, skills, what companies they work for or have worked for in the past, job titles, and so much more.
For Twitter, you target based on interest, keywords or hashtags get specific individuals have used. You can also target audiences who went to your website previously.
Out of all the social channels, Facebook has the most robust audience-building capabilities for a few different reasons. For the most part, Facebook has been the social network that people used to talk about everything they cared about, including sports, politics, business, fashion, music, and everything else.
It’s the social network where we tell the world when we get married when we have children, when they graduate from college, and when they get married. Then, all of the data is used by Facebook so that advertisers can build custom target audiences and launch campaigns based on the audience attributes.
On a basic level, an audience can be attendees of an event, people using hashtags online, or a group of individuals who have used specific keywords.
The best-case scenario is to use a combination of these techniques to deep dive into audience interests and characteristics and even get more detailed audience demographic research.
Is an Audience Analysis and Segmentation the Same Thing?
So imagine doing an audience analysis using social analytics of a group of software developers. You might find some interesting things about the audience members that you were unaware of, so you leveraged a primary research study to dig deeper. From there, you can build a developer audience on one or more of the social channels and use the insights you gain from the audience study, and tailor messages to that audience through a creative campaign. And after the marketing campaign is complete, you can facilitate a series of focus groups to the audience members to measure impact or brand lift.
Many people ask me if an audience analysis and segmentation mean the same thing. It’s really not the right way to think about it. When you do an audience analysis, one of the typical outputs is a cluster of different sub audiences. These could be considered a form of audience segmentation.
Let me give you an example.
Below is an audience segmentation analysis of software engineers. The research started using a bio search of a few different job titles like developer, engineer, and programmer. Building an audience using bio search terms could take a long time, especially if you don’t really know the industry. To ensure that the data is clean and that all audience members are “software engineers,” the process will include filtering and excluding other keywords and phrases.
For example, there is a significant audience size of construction developers on social media, and they often add terms like commercial developer or real estate developer in their bio. To exclude these audience members from the data set, you would have to filter out commercial or real estate keywords.
Another way of ensuring that the audience is accurate is to add content searches combined with bio searches. For example, if your query search for bio just has programmer, developer, and engineer, you can add specific programming language keywords like Python, Java, or C++. In addition, you can add keywords like DevOps, software, and coding to be more precise.
An additional technique is to add a “follower” variable to the bio searches. This means that the audience must follow one or more social media profiles to be included in the data set. So, this could be profiles like @Java, @UCLAengineering, or @Docker.
Once the filtering and exclusion statements are added, the audience segmentation will be complete.
Below are just three of the nine total segments. However, when doing an audience analysis at a larger scale, it would be critical to analyze each subsegment separately.
Let’s explore these three segments and highlight some differences and similarities.
Based on our audience size, almost 9% of the audience are DevOps engineers. You’ll notice some basic demographic information in the description. In this case, we’re limiting the data to just include the geographic location at the country level.
More importantly, you will see the top influencers that influence this segment of our engineering audience. When you compare that to the other segments, there is minimal overlap.
When comparing the media data, you will see some similarities with affinities. All three audience segments have a high brand affinity for the tech publication MIT Technology Review. The Python engineers and IoS developers have a high affinity for ArsTechnica.
While these small details might seem insignificant, they can help provide marketers with the insights needed to tailor messages to an audience and target media outlets within marketing campaigns.
Many factors go into this type of data. At a very high level, when exploring affinity data, we’re looking at the percent of the audience that follows certain social media And the percent of the audience that uses specific keywords and phrases when describing what they do in their bio.
What isn’t illustrated in this example is conversational data. Like the audience persona Example above, we would want to explore the topics and trends that each subsegment is talking about as it relates to important issues to your business. It would be interesting to see the differences in essential subjects like artificial intelligence or enterprise security. I would bet that the conversations are incredibly different from each engineering segment.
The Intersection Between Social Intelligence & Audience Analysis
The more you know about your audience members and understand their attitudes and beliefs, the better you can intercept them with clear and concise messaging as they navigate the B2B sales funnel.
Back in the early days of social media, marketers used social media monitoring to listen to the Internet for specific keywords, topics, brand mentions, competitors, and industries. It gives marketers the ability to segment and analyze audience conversations by the news media, blogs, forums, and social media.
Social media platforms like Brandwatch, Pulsar, Synthesio, Talkwalker, and Netbase have come a long way, integrating audience analytics, natural language processing (NLP), AI, machine learning, and linguistic text analysis to decipher social media conversations.
Social intelligence is still common practice today. While there is value in this approach, a target audience analysis provides more in-depth research enabling marketers to make data-driven marketing decisions.
Marketers can be laser-focused when planning for marketing and communications programs that deliver ROI and business value by segmenting and clustering specific audiences into smaller groups.
Using Audience Analysis to Create Buyer Personas
As mentioned, the buyer’s journey is complex, and building an audience persona from intuition is a thing of the past. While it may seem convenient to download a template from Hubspot, customize it to your brand identify and fill in the blanks. Audience Personas that are not backed by data don’t work. They may look good on a slide, but they won’t get you the results you expect.
A target audience analysis and persona creation give marketers actionable insights they need to create data-driven content marketing programs that deliver real business value and make an impact.
The insights here are just scratching the surface. This audience analysis example is just one snapshot in time but there are some important aspects to talk through. We have already discussed top media affinities and purchase factors in the above examples. her name, age, occupation, location, and marital status are just examples but all of the other data is real.
I want to spend just a few moments talking about topical relevance. Every audience analysis should include some type of conversation data as an output. Conversation data will help narrow down what topics are most relevant to a specific audience. In this example, we are looking at an audience persona but it’s representative of a larger audience of CIOs.
The color-coded sunburst chart is broken down into four different topics––data science, insights, cloud, and CIO. They’re color-coded to show the volume of keyword mentions by the audience. So, in this example, data science accounts for most of the conversations followed by insights, cloud, and then CIO. The second and third layers are subtopics of the main topic. For example, when looking at data science one of the subtopics is deep learning, and then after deep learning, there is AI and analytics.
This is important because we are taking a large data set and clustering it into smaller, size data points to make sense of the data. There would be no way to come to the same conclusion of understanding topical relevance by scrolling through and reading thousands of social media mentions.
Imagine what you could learn if you tracked an audience over a period of time.
What types of Insights Are Available from An Audience Analysis
If done right, there are many data points and insights you can leverage, and all the known factors of an audience will be at your disposal. Here’s a summary of the types of
- Brand Affinities: What brands are the most connected to and reference more than others? You can also learn the audience expectations of the brands they follow on social media.
- Buyers Journey: What keywords (triggers) are they using to research and purchase products and services? You can also uncover the audience’s attitude as they navigate the digital ecosystem.
- Influence: Which audience group influences them, and what other audience members gain influence? What other cultures are a part of this audience?
- Media: What media publications do they read and share by topic of interest?
- Demographic Factors: Where does the audience live and work?
The beauty about building data-informed audience personas is that they will benefit everyone in the organization, from PR and social media to channel sales and direct marketing.
How Audience Analytics Can Inform Digital Marketing
Marketers must ensure that their supply of content marketing meets the audience’s demand by providing relevant stories and creative content.
Audience analytics is a blueprint. Like an architect who designs a house using 3D software, marketers can build data-informed programs using audience analysis. The result: creative storytelling and advertising that can break through the clutter and reach audiences with memorable, impactful, and game-changing programs. Here are a few examples of audiences I have analyzed in the past:
Targeting Audience in Real-time with Relevant Content
I call this real-time content marketing and analysis. The goal of real-time content marketing isn’t to be relevant to everyone. It’s to be highly relevant to your audience. For example, everyone remembers the Oreo Tweet in 2013 during Super Bowl XLVII. Since then, many brands have tried to “hijack” cultural moments to insert themselves into an existing narrative and reach a broad audience. Sometimes it works, but most times, it doesn’t.
This is where real-time audience listening comes in – rather than trying to align your brand with everyone, this approach leverages the audiences that are most important to amplify your success.
Once you build your audience, the content engine works like this:
Two paths can potentially be taken based on your goals and objectives. The first path requires no action other than reporting and making recommendations based on the audience insights. The second path requires immediate action to activate the real-time content engine.
Reporting & Recommendations and Audience Insights
- Monitor your audience’s conversations in real-time to see what’s top of mind and trending.
- Provide daily, weekly, or monthly reporting based on the audience data analysis.
- Recommend activation opportunities based on the insights.
- Provide content recommendations for employees and executives for employee advocacy programs and executive activation.
Real-time Content Engine
- Monitor your audience’s conversations in real-time to see what’s top of mind and trending.
- Provide daily, weekly, or monthly reporting based on brand audience analysis factors.
- Scrum with a team of analysts, creatives, community managers, content strategists, and paid social experts to brainstorm content and activation opportunities.
- Create shareable content, usually an animated video, gif, or digital asset. In some cases, a blog post could be produced.
- Post & amplify the content with strategic paid social.
Choosing the Right Audience Analysis Platform
There are several audience intelligence platforms in the market today. Below is a list of the top platforms I have tested or used over the years.
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