As a marketer you probably have heard about larger 3rd party data providers such as Oracle, Acxiom, Experian or Equifax in the past. However, if you take a closer look at the entire 3rd party data ecosystem, you will find over 100+ data providers offering and selling their data for targeting purposes.
This certainly is very exciting for anyone that is working at an agency or brand to execute more targeted campaigns. However in many instances you will find yourself overwhelmed with the abundance of segments and data methodologies as well as modeling algorithms that data providers apply onto their segments when offering them for sale.
The below overview goes into the most common data methodologies that 3rd party data providers use to generate their segments for advertisers or brands.
Personal or specific information that an individual is willing to share.
Depending on the information that is being asked, the data collector and the collection environment, declared data is one of the most precise collection methods out there. For instance, if a bank provider asks you to fill out a form to request a credit card limit increase, it is save to assume that your DOB, First and Last Name attributes are most likely correct. When compared to filling out a form on a suspicion website that promises a large giveaway.
Data and characteristics assigned to a person based on their activity and behaviors
Here too it is really important to understand who collected inferred data. In many instances, location data providers or website owners such as a publisher provide far more accurate inferred data attributes for targeting when compared to a data provider that scrapes public data sources and offers them up for sale.
Data based on a persons engagement, in many instances, this is done on owned web properties or physical spaces.
Understanding who the data provider is for observed data is also critical here. Purchasing a targeting segments directly from a website such as Forbes.com, Kayak.com or others, will give you far better and more accurate data attributes for targeting, when compared to purchasing data from an data aggregator that is not directly collecting observed data attributes.
Data based on a consumer's interests based on content consumption
Interest data, in the context of targeting and 3rd party data, is one of the data categories that can be very broad. E.g. Being an Outdoor Enthusiasts is specifically not telling a data buyer what it contains but is rather a grouping of multiple outdoor actives that are being combined into one.
Data based on a consumer's action that expresses a intent to purchase
Intent Data is perhaps the most valuable data source that data provider offer, as in many instances, intent data and signals are good proxy of someone completing a purchase.
In closing, the above 5 data collection methodologies will not address data quality or what data methodology is superior when compared to others. It all depends on the data collector, the data collection environment as well as the recency of the collection event. However, this will help you narrow down the data provider you might choose to work when it comes to targeting segments for your brand.
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