What is Audience Data & How to Use It

Audience data refers to descriptive information about consumer profiles which can be used for market segmentation and audience planning in an online environment. Audience data is generally used by companies to enrich consumer audiences and help optimize their marketing spend towards the right customers. In more detail, the data measures demographic, behavioral, and psychographic aspects of a chosen customer group and enables companies to create matching online audiences that can be targeted in both online and offline environments.

We compiled a list of over 400 vendors offering audince data to help you in your data hunt.

What is Audience Data?

As the level of “noise” in marketing increases, and reaching out to target audiences is becoming increasingly tough, more and more brands and businesses are looking upon audience data to derive key insights and to fuel their marketing engines.

So what exactly audience data is? Basically, audience data is information about your potential and existing customers. It comes in all forms and is often linked to a specific device ID. These ID’s can be tracked online via multiple methods to create consistent stories of the devices’ online behavior.

Most common form of such tracking involves cookie tracking. Cookies contain relevant information about the audiences – like the time at which they visited a certain website, what actions did they take, what products did they check out, what is their average time-spend on your website, what made them land to your website, and so on.

This crucial information based on your visitors’ varied online activities is then used to target advertisements and segment audiences.

There are various kinds of audience data, like:

  • Behavioral data: Reflects the behavior of audiences
  • Cross-device identity data: Helps you in identifying audiences who use your products and services from varied devices
  • Lead and address data: Crucial contact information that is needed to get the message delivered
  • Political and voter data: Often used by political parties and reflects the alignment of users towards certain political parties
  • TV consumption data: Illustrates what TV channels do users watch, what is the average duration they watch TV for, and so on.
  • Demographic data: Related to the demographics of audiences.

Who uses Audience Data and for what use cases?

Companies spent around $10 billion last year on third-party audience data for varied marketing and advertising purposes.
This is perhaps because of the number of cases that audience data is used for. Essentially the data can be used by anyone willing to understand their target audience better. Here are some examples of audience data usage in business:

  • providing pre-approved offers to consumers in the financial industry
  • targeting users who have made a purchase in a competitors’ store in the last 30 days (Retail and ecommerce stores)
  • In analysing audience in generalFor general audience analysis
  • Retargeting consumers both online and offline

What are typical Audience Data attributes?

Audience data can be effectively categorized on the basis of its attributes. While some data provides focus on behavioral data, others focus on demographic data. Here are some typical data attributes of audience data:

  • Behavioral and demographic attributes like gender, age, income, and education
  • Location attributes like state, city, and country
  • Interest-based attributed like shopping, surfing, and gaming

How is Audience Data collected?

More often than not, audience data is collected on the basis of the following technologies:

The common way to capture audience data from online sources like websites. Cookies are used to power online display advertising. However, their effectiveness is decreasing due to multiple challenges: government regulations, privacy advocates, and updated in the policies of browser companies.

Fingerprinting technology is seen as a replacement for cookies. Here, unique attributes related to a computer such as the browser version, screen resolution, IP address, font library, time zone and the like and collected to form a digital footprint.

Native database
This refers often to data collection from user accounts on popular platforms like Facebook, Google, Amazon, and so on.

Surveys and phone calls
Last but not least, these are the oldest tricks in the book. Opinions and values are easily shared over a quick phone call. However, this method is time consuming and not scalable.

How to assess the quality of Audience Data?

Every marketer understands the importance of audience data quality in advertising and marketing. For a business strategy to resonate with the target audiences, the data they hold onto should be perfectly accurate and reliable to be able to achieve the maximum ROI.

Thus, it makes sense to assess the quality of audience data before purchasing. Here is how you can do that:

The source of the data

Knowing the answer to the question Who Owns The Data is the first step in evaluating the quality of data. Generally, data ownership can be divided into three categories: 1st party, 2nd party, and 3rd party.
1st party means that you are the owner of the data. Data in such cases is extracted from CRM systems, your website visitors and so on. Ideally, 1st party data is the best quality data because it is your data, which means that it is reliable. Additionally, it doesn’t cost you anything.

Next is the 2nd party data. This data belongs to someone else with whom you are in direct touch. For instance, it might be your digital marketing agency who manages the marketing for you. Or it might be a marketing tool. Although this type of data is close to the first-party data in terms of quality, it all sums down to the level of transparency that you have with the second party.
The last category of audience data is 3rd party data which is obtained from an unknown party of origin. Since you are not sure of the exact whereabouts of this data, this data cannot be considered as high-quality without investigating.


The next factor which determines the quality of audience data is the technology through which it is obtained. Is it obtained through the browser cookies, or fingerprinting technology? Or does it come from a native database like that of Facebook Google, and the like?

It is important to mention that the data collected from native databases is the highest quality as it is the first-party data. On the other hand, audience data developed through cookies is the lowest quality data as almost 50-75% of cookies decay within 30 days, and do not hold true,


The way through which the audience data is collected also has an everlasting impact on its quality. Generally, data is gathered in three ways:


This data is explicitly disclosed by customers, users, and visitors. The data is generally in the form of profile information, survey answers, age, household income, religion, language and the like. Since the data is provided by the audiences themselves, this data is highest in quality.


This data is based on educated guesses about a certain attribute or characteristic of audiences. For instance, a publisher who runs a website for girls and women could collect and categorize data based on teens, working women, married women, and so on.
Apparently, this is not an accurate way to infer and conclude. This is what makes this data not as high in quality as the declared data.


Modeled data is similar to inferred data in which companies create look-alike or behave-alike data based on the conclusions derived from declared data and inferred data.
Naturally, the data obtained this way is not quality data either.

Other important factors through which you can determine the quality of audience data is its cost and its freshness. It is a no-brainer that aged data won’t hold any significance in current times.

How Audience Data is typically priced?

Most audience data APIs price their data based on the following metrics:

  • The composition of the audience data - For instance, first-party data will cost more.
  • The freshness of the data - Undoubtedly, old or stale data is available at a fraction of the cost of the fresh data.
  • Scales (The number of platforms and devices that the audience data is extracted from)

What are the common challenges when buying Audience Data?

When buying audience data, the number one concern that most marketers face is data accuracy. According to a study, only 20% of marketers who purchase audience data seem to be confident of its accuracy. Another 68% of them were somewhat confident. The other 12% were either slightly confident or not confident at all in the accuracy of the data that they purchase.

Undoubtedly, purchasing data from an audience data vendor and ensuring that it is what you are looking for, is reliable, and accurate is important. This is because audience data serves as a starting point for various campaigns and strategies, and if this goes wrong – it is likely that you won’t be able to achieve the goals.

What to ask Audience Data providers?

Before buying data from an audience data provider, here are a few questions that you must ask:

  • How do you collect data? What is your primary business model?
  • Is the audience data provided by you properly permissioned? Which rules and regulations do you stick to?
  • How is the data sourced?
  • Was the data modeled? What was your objective behind this?
  • How do you verify the quality of data?
  • How old is the data?

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