A marketing campaign's success hinges on the ability to trust and analyse data. The question then becomes, 'how near or relevant is the data you have to your drive?'
To answer these questions, you'll need to know more about data classification. The most important thing for marketers is to have precise data for high-accuracy targeting. The significant distinction between 1st, 2nd, and 3rd party data is the quality-to-reach trade-off. The quality attribute refers to how close, rich, relevant, or connected the dataset is - your CRM data may be of the highest quality for operating or retargeting your current client base. Still, it may be severely constrained for reaching new audiences.
The distinction between 1st, 2nd, and 3rd party data will serve as a jumping-off point for a series of articles devoted to understanding the world of data and the many data kinds that can be used for campaign reasons.
First Party Data
The data you've collected about your clients or the audience you own and manage is referred to as first-party data. It can originate through your website or app, CRM, customer feedback, in-store beacons, purchases, contact centre, point-of-sale communication, or any other information given with users' agreement.
It is the most potent since it results from direct, trustworthy relationships and contact with a customer. You can also develop segments and profiles based on the unique consumer data you have on hand if you own first-party data. According to a report by Econsultancy and Signal, first-party data is more critical and relevant than second- or third-party data because of its specificity and quality.
Limitations of First Party Data
On the other hand, First-party data has several inherent limits, one of which being its reach. The scope and breadth of the first party are frequently limited. It provides a thorough picture of a given audience, including transaction history and behavioural data from websites and advertising. Even so, these data may not be large enough to make assumptions or reach new audiences. The extent of your operations is the only limit to the scope of first-party data. If you offer a health-related app, the data you have about your consumers will be limited to their fitness or healthy-living interests. Making adequate exact assumptions and developing a specialised and focused strategy will not be enough.
Second Party Data
In a word, second-party data is someone else's first-party data that you may buy directly from the source and use for your marketing (see AdExchanger article for more). With such information, a company may expand promotions beyond existing consumer bases and increase acquisition. A corporation could access second-party data by a formal arrangement between a first-party data owner and another party, such as a direct collaboration, data management platforms, or a 2nd-party data network.
Third Party Data
An example of receiving data from a third party could be a hotel reservation website that works with an airline. Both parties would benefit from mutual control of the other party's data sources over the quality of each other's first-party data, just as you have over your first-party data. Another thing is that while the scope of third-party data is more scalable, it is again limited to the extent of your source data partners. It's a way to overcome the scale limitations of source data, increase reach, increase campaign effectiveness, and personalise your journey with only relevant data.
Third-party data consists of many demographic or behavioural information that is generally aggregated from many different sources. Likely, the company that collects this data does not have a direct relationship with consumers. By collecting detailed user behaviour profiles, such as interests, browsing activity patterns, hobbies, or preferences, third-party data is compelling. And here comes the compromise between range and quality.
An inherent disadvantage of third-party data is quality: third-party data is statistical and aggregate data. Third-party data is often derived (implicit) data; it is based on the user's past behaviour and not on information explicitly provided by the user. It was not inferred from a direct relationship, making it more difficult to trace if it came from a reliable data source. Also, because giant data aggregators offer third-party data, it is not exclusively available to you and can be quickly sold to other parties, including your competitors.
What is the best approach?
Ideally, your strategy should start with defining your marketing objectives and targeting new customers or existing customers. We can overcome the disadvantages of different data types by combining 1st, 2nd, and 3rd party data to optimise accuracy and scalability. It is also critical that the data used for improved and efficient segmentation is secure, private, and comes from trusted data providers. Always choose partners who offer quality assurance and ensure that data protection regulations are not violated.