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1st, 2nd and 3rd Party Data – What It All Means?

Do you trust your data and how close or relevant the data you have on hand is to your campaign? Answering these questions requires further understanding of the classification of data. For marketers, the most crucial point is to have the exact data for precise targeting with high accuracy.


In general, the main difference between 1st, 2nd and 3rd party data is the trade-off between quality and reach. The quality characteristic refers to how close, rich, relevant or related the dataset is – your CRM data may be of finest quality for reaching or retargeting your current customer base, but extremely limited to reach new audiences.


The distinction between 1st, 2nd and 3rd party data will be a starting point in a series of articles we have dedicated to comprehending the realm of data and how understanding different types of data serves campaign purposes.


We will further explain the differences in more detail.


First-party data is the data you have collected about your customers or audience, you own and manage. It can come from your own website through cookies or via your app, CRM, customer feedback, in-store beacons, purchases, contact center, point-of-sale communication, or any other information given with the consent of users (see TubeMogul article for more). It is a result of direct, trusted relationship and communication with a consumer, which makes it the most powerful. Owning first-party data also gives you the freedom to create your own segments and profiles based on the unique consumer data you have on hand. According to a report by Econsultancy and Signal, first-party data is considered to be more valuable and relevant through its specificity and quality compared to second or third- party data.


However, first-party data has some inherent limitations and one of them is reach. 1st party is often restricted in scale and breadth. It gives you a detailed picture of a specific audience such as transaction history or behavioral data from sites and campaigns but these data may not have the scale required to make assumptions nor reach new audiences. The broadness of first party data is restricted only to the scope of your operations – if you provide a health-related app, the data you have on your customers will be restricted to the fitness or healthy lifestyle interests of your customers and will not be sufficient to make enough precise assumptions and create a precise and targeted campaign.


Second-party data in a nutshell is someone else’s first party data that can be utilized for your own marketing bought directly from the source (see AdExchanger article for more). It represents a way to overcome scale limitations of first-party data and expand the reach and increase the effectiveness of campaigns and personalize your campaign with only relevant data. It can be used to scale promotions beyond existing customer bases and drive acquisition. Access to it can be obtained through a specific agreement between a first party data owner and another entity such as direct partnership, data management platforms or a 2nd party data network. One example of obtaining a second-party data might be a hotel booking website collaborating with an airline to mutually benefit from each other’s data sources.


Usually such a relationship fosters collaboration and trust and is highly beneficial for both parties, but it is only possible when there is no competition or conflict of interest between the two parties involved. Also, although scalable you are again restricted only to the reach of your first-party data partners since you are not the owner of the data and hence not in direct control of how the data is collected, one disadvantage of second-party is related to the quality control of data obtained – you don’t have control over the quality of others’ first party data as you have over your own first-party data. Another thing is that although more scalable, second-party data reach is again limited to the reach of your first-party data partners.


Third-party data is generally aggregated from many different sources and consists of rich behavioral or demographic data. It is often collected by an entity that doesn’t have a direct relationship with consumers. (See the Digiday UK article for more). Third-party data is often an inferred (implicit) data, which means that it is based on past user behavior and not on information, provided explicitly by the user. By collecting detailed behavioral profiles of users such as interests, patterns of browsing activities, hobbies or preferences third-party data has an incredible reach.


And here comes the trade-off between reach and quality. One inherent disadvantage of third-party data is quality – 3rd party data is statistical and aggregated data, it has not been derived from a direct relationship, which makes it harder to trace back whether it comes from a reliable data source. Furthermore, since third-party data is offered by large data aggregators, it is not exclusively provided to you and can easily be sold to other parties as well, including your competitors.


What is the best approach?


To overcome the disadvantages of each different type of data, one recommendation is to have a combination of first-, second- and third-party data to optimize for both precision and scale. Ideally, your strategy should first start with defining your marketing goals and whether you would be reaching out new customers or engaging current ones. Also, it is important that data used to create improved and efficient targeting is secure and private and comes from trustworthy data providers. Always opt for partners that provide quality assurance and make sure that there is no breach in data regulations.

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About Giulia Grazzini

Giulia is the Senior Marketing Manager of Adsquare. Originally from Italy, she landed in Berlin after many years in the City that Never Sleeps and in beautiful Sydney.

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