A simple guide to data types for marketing: All you need to know
In today’s digital age, marketing needs to be data-driven to be effective. You should be familiar with the types of marketing data that you can use to improve your communication with customers. Our simple guide will give you the basic terms to get you started.
1) Data types by collecting source:
• First-party data
• Second-party data
• Third-party data
What is first-party data?
First-party data is information that your company collects directly from customers. Your company might have first-party data in its CRM.
Example: Every time you click on a product or add it to your shopping bag on Amazon’s website, the data containing your interactions is collected by the company. Amazon then uses this information to show you products that you might be interested in.
First-party data can act as a strong foundation for creating a consumer-centric marketing strategy. As the information comes directly from your customers, you can gather relevant and accurate information which can create highly personalized experiences at no cost.
That said, customer information has to be protected and used wisely, especially with the adoption of the General Data Protection Regulation (GDPR) in the EU and California Consumer Privacy Act (CCPA).
What is second-party data?
Second-party data is essentially first-party data that you didn’t collect yourself. Your company might work out an arrangement with a publisher or a non-competitive brand to access their customer data.
Example: Based on demographic overlap, an e-commerce site selling dress shoes for men might make a deal with another e-commerce site selling suits to send offers to its audience who are actually potential customers for the online shoe store.
Second-party data is commonly used for audience enhancement and extension. For instance, a company might partner with another one to find new customers based on demographic overlap.
What is third-party data?
Third-party data is information your company can buy from outside entities (data aggregators) that does not have direct relationships with the customers.
Commonly, third-party data is aggregated by data providers from various websites and platforms on on Data Management Platforms (DMPs) in order to create comprehensive audience profiles. These data sets, containing the categorization of users into particular segments, are then made accessible for companies to build effective advertising and retargeting strategies by leveraging the massive amounts of consumer information.
Example: A data aggregator has agreements and collects data from different sources on its DMP.
We will illustrate this below:
Let’s say one of these data sources is a website that publishes articles and videos on “fine dining”, allowing our aggregator to place cookies on visitors’ mobile devices, and name this segment “fine dining enthusiasts”.
Another data source is an online travel agency, selling airline tickets; allowing our aggregator to place cookies on devices of users who purchase airline tickets. The data aggregator puts a time constraint on these users and deletes them from its platform in 2 weeks. Name this segment “recent airline ticket purchasers”.
Our aggregator makes these sets of data it collects accessible for brands to be able to show ads through DSPs.
The first segment has an audience of 45,000 and the second has an audience of 88,000 and there are 5,000 users that are overlapping. “Fine dining enthusiasts that recently purchased airline tickets”. These users could be a very valuable segment for American Express.
So through a DSP, American Express can choose and target these users with ads on any publisher available on the platforms inventory.
American Express had no direct relationship with these users or the fine dining blog or the online travel agency but yet was able to target these users through intermediary providers, making this a 3rd party data source for them.
2) Data types by collecting method:
• Behavioral data
• Transactional data
• Declared data
What is behavioral data?
Behavioral data is information generated by the result of actions during the customer’s engagement with the business. Often times, behavioral data tracks the customer’s commercial behavior on the Internet such as the websites visited, apps downloaded, or search terms.
Example: Types of music you listen to on a streaming platform, items you checked out on an e-commerce site, articles you read
Behavioral data is valuable in that it can provide more than what static data –data that does not change after being recorded— can provide. Combined with behavioral analytics, your company can understand the “why” of customer behavior and generate day-to-day insights.
What is transactional data?
Transactional data is information generated as a result of transactions. It documents an exchange, agreement, or transfer between parties such as purchases, insurance claims, payments or deposits.
Example: Clothes you purchased on a retail site, deposits you made to your bank account, events you signed up for
What is declared data?
Declared data is a type of data that has been willingly and actively given by your customers. The ways to gather declared data include customer feedback, surveys, forms, and polls. A company might ask customers about their motivations, intentions, interests, or preferences.
The great thing about declared data is that it comes directly from consumers, rendering it to be the most accurate and relevant information you can utilize.
To learn more about why the collection of declared data in addition to behavioral or transactional can be a significant value-add for your business, read our post by clicking here.
Poltio provides a platform for first-party declared data collection through engaging interactive content. Below is an example of a test created on Poltio.
To learn more about how it works, visit Poltio.