start.io Custom Audiences - Audience Data for North & South America, Europe, Oceania & Africa
OnAudience - Audience Data (1,200 ready-made segments)
Locationscloud - Prepackaged Audiences | Audience Data With WorldWide Coverage
Acxiom High Value Audiences (HVA) - Audience Data (Germany, UK & India Covered)
Gravy Analytics Custom Audience Creation USA & Canada -- intent audiences based on consumer visits to
Programmatic Advertising - Build Your Brand With FrescoData Audience Data ⎢10K+ Attributes
Custom Audiences: Audience Data for LATAM by Retargetly
Audiencerate Audience Data Platform with Global Coverage for Marketers
Multimedia Lists Consumer Audience Data USA (245 Million Individuals)
Zeotap People Identity Graph (High-Quality Audience Data)
The Ultimate Guide to Audience Data 2021
What is Audience Data?
With digital marketing becoming increasingly focussed on audience segmentation and streamlined messaging, more and more brands are looking to audience data to derive key insights on consumer behaviour and optimize the success of their marketing. As digital marketing gets more sophisticated, the amount of marketing ‘noise’ also increases. This means that, to engage with an ad successfully and secure conversions, customers expect a highly personalized experience. Audience data helps to ensure that the content that reaches them is relevant and effective.
So what exactly is audience data? 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 IDs can be tracked online via multiple methods to create consistent stories of the devices’ online behaviour.
The most common form of such tracking is cookie tracking. Cookies are small text files that save user-specific data in your browser. They contain relevant information about users – like the time at which they visited a certain website, what actions they take, what products they check out, what is their average time spent on your website, what made them land on your website, and so on.
This crucial information based on your visitors’ varied online activities is then used to create user-friendly experiences, to target advertisements and to segment audiences.
There are various kinds of audience data, like:
- Behavioral data: Reflects the behavior of audiences, such as the actions they take when visiting websites.
- Cross-device identity data: Helps you in identifying audiences who use your products and services from various devices.
- Lead and address data: Crucial contact information that is needed to get the message delivered to the right audience.
- 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: Provides data on the demographic of users, such as age, gender and income level. This is the most commonly purchased type of audience data.
- Social engagement data: data about what users view, like or share on social media.
Who uses Audience Data and for what use cases?
The use of audience data is growing rapidly; in 2020 advertisers spent 20% more on data than the year before..
Audience data can be used for a wide variety of advertising and marketing purposes, and it’s becoming an essential part of digital marketing.
Essentially, audience data helps marketers understand their target audience better. Here are some examples of audience data usage in business:
- To provide pre-approved offers to consumers in the financial industry
- For targeting users who have made a purchase in a competitors’ store in the last 30 days (both retail and ecommerce stores!)
- To retarget customers, such as providing ‘win back’ offers to customers who visited the brand’s website
- For general audience analysis, to better understand the existing audience and predict their behaviors
- Retargeting consumers both online and offline
- To personalise content for the target audience
- To display advertisements on sites which the target audience visits
- For identifying keywords for search engine marketing
- To find new potential audiences to increase a brand’s customer network
Why is Audience Data important?
Today’s consumers expect a highly individualised experience. Audience data can enhance the user’s experience, ensuring the content they consume is personally relevant to them.
“91% of consumers are more likely to shop with brands who recognize, remember, and provide relevant offers and recommendations.”
The use of audience data is crucial in enabling marketers to personally curate content to the individual and consequently improve their Return of Investment (ROI).
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, often inferred from online browsing activity
How is Audience Data collected?
More often than not, audience data is collected using the following technologies:
Cookies are the most common way to capture audience data from online sources like websites. Cookies are often used to ensure the user-friendly experience of websites, such as saving your shopping cart when online shopping, but they also power online display advertising. Cookies may now only be used with the explicit consent of the user. This is why sites will now ask you to consent to cookie tracking as you enter.
Fingerprinting technology is increasingly becoming a replacement for cookies. Here, unique attributes related to a computer such as the browser version, screen resolution, IP address, font library, and time zone are collected to form a digital fingerprint, a profile unique to the user but in aggregated format. It provides websites with more unique information than cookies, meaning the data can be of a higher-quality. Fingerprinting is also useful for identifying botnets and suspicious activity to avoid fraud.
Native database refers to data collection from user-generated content and input, such as through user accounts on popular platforms like Facebook, Google, Amazon, and so on. This is a kind of first party data and is of high quality since it comes directly from the user.
Surveys and phone calls
Last but not least, outbound market research. In terms of understanding your audience, cold calls and surveys are the oldest tricks in the book. Opinions and values are easily shared over a quick phone call or survey. In terms of accuracy, this type of data is extremely high quality since it is provided willingly by the user. However, this method is time consuming and not scalable, meaning the scope of the data collected is likely to be limited. This kind of data is thus much more practical for smaller businesses.
How does social media advertising use Audience Data?
Social media advertising is becoming ever more popular, with 83% of marketers using it in 2020, up from 60% the previous year.
Social media marketing is a good example of the clear usage of audience data in advertisement. Social media platforms are able to incorporate their own data collection into the advertising functions on their platforms. For example, Facebook and Instagram’s advertising service allow you to target specific audiences by selecting attributes such as age, gender, location and interests. Audience data is then used to distribute advertisements to a specific target audience.
How to ensure Audience Data is privacy-compliant?
It’s important to ensure that any data you collect or purchase is compliant with data protection laws.
One of the most prominent of these laws is the General Data Protection Regulation (GDPR) in the EU. This law was introduced in May 2018 and essentially means that the consumer’s consent is required for data collection. It also means that data subjects have the right to request a copy of the data collected or ask for it to be erased.
By complying with such regulations, companies can ensure they are transparent with consumers about how their data is used and build trust with them.
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 main categories: first party, second party, and third party data.
First party data is data collected directly from your audience from your own sources, such as from customers visiting your website or buying your product. This means that you are the owner of the data. Since it comes directly from your own sources you can be sure it is reliable and accurate data. It doesn’t cost you anything and it is easy to ensure your data complies with data protection laws. Cookies, for example, fall into this category.
Second party is data purchased directly from another company that collected it themselves. Essentially, a company can collect their own first party data and sell it directly to another company, providing them with insights on a wider audience. This is extremely useful to learn about your potential customers, rather than just existing ones. 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 to ensure its reliability.
Third party data is data purchased from an external source that was not the original collector of the data. Essentially, data aggregators purchase data from multiple sources, collect it into one data set and sell it to other companies. This kind of data is useful since it has a large scope, helping companies to expand their audience further. However, since you are not sure of the exact origins of this data, it cannot be considered as high-quality without investigating. Furthermore, this data may be less valuable if it is possible that there are many buyers of the same data, as it will provide less unique information.
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 higher quality as it is the first-party data, meaning accuracy is almost guaranteed. On the other hand, audience data developed through cookies is the lowest quality data as almost 50-75% of cookies decay within 30 days, making the data often unreliable or outdated.
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 based on their activity. It is data based on assumption rather than the direct disclosure of users; for example, it could be inferred from someone’s search history or social media follows what they are interested in, without them explicitly declaring this themselves.
There is a risk of inaccuracy with this data as it is based on informed guesses rather than confirmed data, which can mean it is not as high in quality as 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.
Its value will depend on the accuracy of the original audience data it was modelled from.
Other important factors through which you can determine the quality of audience data is its cost and its freshness. Depending on your use case, outdated data tends to be lower-quality. Generally speaking, audience data has to be current, because targeting a consumer at the right time with relevant information is crucial for a successful marketing campaign.
How to effectively use Audience Data in digital marketing
With various types of data, it is difficult to understand how best to use them in digital marketing. One strategy often used is audience enrichment, which involves using multiple types of data side by side.
Audience enrichment is using second or third party data to supplement your first party data. This results in a much more detailed picture on consumers than your own data can provide. For instance, your own first party data about a customer’s interests could be supplemented by third party data about the demographic they belong to, allowing you to market more specifically to their desires and needs. This type of marketing is called audience targeting.
What is audience targeting?
Audience targeting is a strategy used by marketers to focus on a specific group. This begins with audience segmentation, where the full audience of potential customers is divided into smaller, more specific groups based on their attributes. Marketing can then be concentrated on the customers most likely to buy your product or service, which is referred to as your target audience.
By directing marketing at a specific target audience, companies are able to communicate more directly with potential customers, providing more personal and focused content. Instead of reaching many people with a general message, audience targeting can optimise the success rate of marketing by concentrating on the people most likely to be interested in the product or service. This can also help companies to build customer loyalty as you are able to adapt content to suit your audience and resonate with their personal needs. Knowing your audience is a fundamental part of marketing.
Acquiring audience data is therefore extremely useful for audience targeting as it provides the information needed to define your target audience and predict their behaviours.
How can you buy Audience Data?
Audience data can be purchased in raw form or ready to use segments from various sources:
Data management platforms (DMP) are used by advertisers and publishers to onboard, segment, enrich, and distribute their first-party audience data for online targeting. This is where audiences can be segmented, and data can be organised in a meaningful way in a centralised location. Data management platforms are then usually linked to other software to buy or sell the data for advertising.
Demand Side Platforms (DSPs) are a popular way of buying audience data for advertising. DSPs often integrate with DMPs to allow marketers to purchase advertisement slots with audience data to target a specific audience. They use Real Time Bidding (RTB) algorithms which allow advertisers to bid on advertisement slots in real time. The advertiser specifies how much they are willing to spend and the target audience they want to reach, creating a bidding war which determines which advertisement is displayed to the consumer.
Audience Data Marketplaces (ADMs) collect audience and targeting data providers under one roof where the exchange of external datasets takes place. You can buy ready-made data segments here to target a specific audience. They are often integrated with DSP functions.
How is Audience Data typically priced?
First-party audience data can be collected from your own sources for free. However, this data is limited and to increase the scope of data at your disposal, you can also purchase second and third party data from external providers. Price will depend on the quality of the data. Most audience data APIs price their data based on the following metrics:
● The composition of the audience data - First-party data tends to cost more than third-party
● The freshness of the data - Real-time datasets and APIs typically cost more than historical databases
● Scale - The data’s geographical coverage, as well as the number of platforms and devices that the audience data is extracted from
● Depth of the data – the more aspects of a customer’s profile which are represented in a data set, the more detailed a picture of the consumer can be formed.
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, “6 in 10 marketers are concerned with the quality of data available from data providers and sellers” and only 1 in 5 are “very confident” in the accuracy of their purchased demographic data.
Undoubtedly, purchasing data from an audience data vendor and ensuring that it is what you are looking for, is reliable, and accurate is extremely 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 your goals. Inaccurate data leads to imprecise targeting, which will affect the success of any campaign.
What to ask Audience Data providers?
Before buying data from an audience data provider, here are a few questions that you should ask:
● How do you collect data?
● Is it first or third party data?
● Is the audience data provided on a consent-managed basis? Which rules and regulations do you stick to?
● How is the data sourced? Is it aggregated or single source data?
● Was the data modelled? What was your objective behind this?
● How do you verify the quality of data?
● How old is the data?
● How often is the data updated?
It’s also a good idea to ask for an audience data sample. This way, you can check that the dataset or API works with your business’ existing management systems.
How to evaluate the performance of Audience Data?
Using audience data in digital marketing is an ongoing process that requires constant review. This enables marketers to make in-flight adjustments to campaigns. It is important to consider the following criteria to measure the success of audience data usage:
· Did engagement in your content increase?
· Did your revenue increase?
· Which target groups responded most successfully to the content?
· Was the cost of the audience data worth the overall outcome?
By asking these questions throughout a campaign, marketers can adapt their audience data usage to achieve optimal results.
Who are the best Audience Data providers?
Finding the right Audience Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Audience Data providers that you might want to buy Audience Data from are Adstra, Mobilewalla, Oracle Data Cloud (ODC), Multimedia Lists, and start.io.
Where can I buy Audience Data?
Data providers and vendors listed on Datarade sell Audience Data products and samples. Popular Audience Data products and datasets available on our platform are start.io Custom Audiences - Audience Data for North & South America, Europe, Oceania & Africa by start.io, OnAudience - Audience Data (1,200 ready-made segments) by OnAudience, and Locationscloud - Prepackaged Audiences | Audience Data With WorldWide Coverage by Locationscloud.
How can I get Audience Data?
You can get Audience Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Audience Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Audience Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Audience Data?
Audience Data is similar to Demographic Data, Social Media Data, Marketing Data, Consumer Panel Data, and Psychographic Data. These data categories are commonly used for Audience Targeting and Audience Insights.