Full Guide to Audience Analysis: Types, Use Cases and More
Audience analysis helps marketers uncover key segments, enable personalization and boost ROI through smarter targeting, messaging and media buying.
- Overview
- Types of Audience Analysis
- What Is Behavioral Audience Analysis?
- What Is Demographic Audience Analysis?
- Use Cases for Audience Analysis
- How to Collect Data for Audience Analysis
- Resources
Overview
Savvy marketers know that understanding the audience is the foundation of a successful marketing campaign. Audience analysis delivers data-driven customer insights that reveal what motivates consumers to make a purchase or stay loyal to a brand. With audience analysis, marketers can craft highly targeted messaging that drives action, identify the most-effective channels and platforms, discover opportunities to increase average order value and more. Let’s explore how demographics influence audience targeting, and highlight the best data sources for conducting effective audience analysis.
Types of Audience Analysis
Holistic audience analysis involves researching various behaviors or characteristics of a group. While demographic information is an essential aspect of audience analysis, it only scratches the surface of what is needed to implement a modern, data-driven targeting strategy. Audience analysis also includes psychographic, behavioral, situational and contextual analysis. Before we dive deeper into demographic audience analysis, let’s take a look at each of these aspects for a broader context.
- Demographic analysis focuses on statistical data about a population, such as age, geographic location, education level and so on.
- Psychographic analysis looks at the internal landscape of a group, including values, beliefs, attitudes and interests.
- Behavioral analysis examines an audience’s behavior related to the buyers’ journeys, such as what social media platforms they engage with, what type of content they consume, where they look for product recommendations and so on.
- Situational analysis takes into account the fact that variable factors influence an audience. For example, the season heavily influences the purchasing behavior of an audience.
- Contextual analysis looks at the specific context in which audiences encounter messaging, such as time of day, device used, content type or platform, enabling marketers to deliver messages when and where they’re most effective.
What Is Behavioral Audience Analysis?
Behavioral data in audience analysis for marketing delves into the actions and interactions of individuals with a brand, its website, apps, content and even physical locations. Unlike demographic or psychographic data that describe who an audience is and what they think, behavioral data reveals what they do. It offers a dynamic and insightful view of how individuals interact with a brand across various touchpoints, moving beyond static demographic and psychographic profiles to reveal actual engagement. This rich information paints a detailed picture of the customer journey and preferences.
Here are key components of behavioral data analysis in marketing:
Website and app interactions: This encompasses a wide array of digital actions:
Page views: Tracking which pages users visit provides insights into their interests and the information they seek.
Time on page: Longer durations suggest higher engagement and interest in the content.
Click patterns: Analyzing clicks reveals navigation paths, feature usage and calls to action that resonate.
Search queries: Understanding what users search for on a website or within an app highlights their specific needs and intent.
Content consumption: Tracking views of videos, downloads of resources and reading of articles indicates content preferences.
Form submissions: Completion of contact forms, sign-ups or feedback forms signifies engagement and potential lead generation.
Transactional behavior: This focuses on purchase-related actions:
Purchase history: Past purchases are strong indicators of future buying behavior and product preferences.
Items added to cart: This signals interest, even if the purchase isn't completed immediately.
Cart abandonment: Analyzing abandoned carts can reveal friction points in the purchasing process.
Order value and frequency: These metrics help identify high-value customers and purchasing habits.
Engagement with marketing communications: This tracks how audiences interact with marketing efforts:
Email opens and clicks: These metrics measure the effectiveness of email campaigns and the relevance of the content.
Social media interactions: Likes, shares, comments and follows indicate brand affinity and content resonance.
Advertising interactions: Clicks on ads and conversions from ad campaigns demonstrate their effectiveness in reaching the target audience.
Offline behavior (increasingly integrated): Bridging the digital and physical worlds:
In-store purchases: Tracking purchases made in physical locations provides a holistic view of customer behavior.
Foot traffic: Analyzing store visits can offer insights into local interest and engagement.
QR code scans and app usage in-store: These actions connect online and offline interactions.
By analyzing these behavioral data components, marketers can develop granular audience segments based on actual engagement, understand customer journeys, personalize marketing messages, optimize user experiences, and ultimately drive more effective and customer-centric marketing strategies.
What Is Demographic Audience Analysis?
Demographic audience analysis defines and examines an audience by its demographics such as age, geography, gender, education, income and other statistical data. Understanding these characteristics offers insights into an audience’s expectations, the context in which they’re making purchasing decisions and the cultural influences that should be accounted for. Additionally, it is one of the most accessible types of audience analysis because this information is readily available.
Components of Demographic Data for Audience Analysis
To see how demographic analysis influences the effectiveness of marketing initiatives, consider these common demographic data components of audience analysis.
Age: The age range of a market segment can offer clues into stage-of-life events that the audience may be experiencing, such as raising a family or preparing for retirement. Age also can indicate particular preferences and perceptions. Knowing the age range of your audience can also tell you which channels, platforms, websites and publications to focus on.
Geographic location: A variety of information, from cultural influences to weather events, can be gleaned from knowing the geographic location of your audience. Retailers especially benefit from geographic data.
Socioeconomic status: Understanding socioeconomic status will tell you what price point to target and what product types are likely to perform well for a given audience.
Gender identity: The gender identity of an audience also can provide important clues into its needs and desires. Beyond the obvious, gender may have subtle influences on demand for various product types.
Industry/occupation: For B2B companies, knowing the industries and occupations an audience operates within will improve the ability to target pain points and choose the appropriate terminology and examples.
While these are just a few of the many components of audience demographics, this list reveals the impact of having this information at your fingertips when crafting a marketing campaign.
Use Cases for Audience Analysis
Marketers across industries use audience analysis to improve performance, drive personalization and maximize the impact of their campaigns. Here are a few examples.
Media companies optimize ad performance
Media companies and publishers use audience analysis to measure content and advertising effectiveness. With insights into audience preferences, they can guide advertisers on creative and placement strategies — improving campaign outcomes and boosting advertiser retention.
Retailers refine retargeting and personalization
By combining demographic and purchasing behavior, retailers can identify high-intent segments and improve retargeting efforts. This enables more relevant product recommendations and timely offers, increasing conversion rates and average order value.
Marketers reduce ad spend through smarter targeting
Audience analysis helps marketers understand their audience’s needs, motivations and preferred channels. With these insights, they can focus spend on high-performing segments and platforms, reducing waste and increasing campaign efficiency.
Better insights increase customer engagement
With a clear picture of their audience — including demographic, psychographic, behavioral and situational factors — brands can craft content and experiences that connect on a personal level, delivered at the right time in the customer journey.
How to Collect Data for Audience Analysis
Audience data can come from a variety of sources, and most organizations already have a wealth of data waiting to be tapped for valuable audience insights. Here are five key sources you shouldn’t overlook.
Online brand mentions: Look at who’s talking about your company or products on forums, reviews sites and social media, and see what they’re saying.
Your social media accounts: Gather information about the people engaging with your brand on Facebook, LinkedIn, Instagram and other social media pages.
Your SaaS tools: Marketing platforms, CRM systems, customer service platforms and chat tools all hold valuable audience insight data.
Your website: Your website is an excellent source of audience insights. Track behavioral patterns and content consumption patterns, and identify paths to purchase.
Third-party data: You’re not limited to using only data that you own to glean audience insights. Open and commercial data sets, such as those in Snowflake Marketplace, are available.
