Can you optimize your direct campaigns based only on first party data?

Data is making a lot of noise nowadays right from implementing GDPR to Apple disabling IDFA by default on it’s devices. Now Google is also planning to block third party cookies on Chrome browsers. This can affect publishers as a lot of Data Management Platform and retargeting ad agencies rely on 3rd party cookies/data to function properly. In this blog, we will discuss if there are any ways for the Publishers to optimize their inventory when third party cookies are gone.
But before that let us understand the difference between a First Party, Second Party and Third Party data.

First Party data is the information you collect from your own audience or customers through your own sources. It can be from online or offline sources such as website or app visits, CRM, social media, surveys or forms. First party data is considered as the most valuable, reliable and cost-effective too. Collecting this data is also considered as the secure way to collect as you comply with the privacy rules. Publishers can do many things with First Party data, be it increasing the user experience, personalized messages and audience targeting.

Second Party data is somebody else’s first party data either shared or sold. Second Party data is also of high quality because it is directly coming from the company that has collected it. Most of the companies share their first party data so that both the companies can benefit from it. For example, an airlines company can sell it’s customer’s data to a hotel chain so that the hotel chain can run targeted ads to those users and the airlines company will get paid for that data. There are many data exchanges such as Lotame which helps sellers to connect with potential buyers and vice versa.

Third Party data is data that you buy from outside sources that are not the original collectors of the data typically from large data aggregators or Data Management Platforms. The publishers or data owners are paid by data aggregators for their data. Third Party data is relatively easy to buy because of its volume and reach. Many Publishers often use third party data to gain more insights on their customers.

Some examples where other domains can set third party cookies include:

  1. Digital Ads: If you’re showing digital ads on your website, then the ad servers such as Google Ad Manager or Ad Network such as Facebook can set cookies on your browser and these cookies are considered as third party cookies.

  2. Social Media Plugins: Placing Social media plugins where you can like share a post on a website can also set third party cookies on the users’ browsers.

  3. Live Chat Popups: These also work similar to social plugins. They will leave cookies to enhance user experience such as remembering the user’s name etc.

Now if browsers start blocking third party cookies, then there will be limitations to the third party data. Advertising giants like Google, Facebook and Amazon cannot set their third party cookies and Data aggregators or DMPs have to rely only on first party data providers. This will reduce the overall volume of usable data and hence the number of targetable users. First party data will become even more valuable and DMPs or Data Aggregators may pay even higher prices for the same sets of data.
With blocking of third party cookies which sets limitations to third party data, first party data will become more important and DMPs and Data Aggregators’s solution may become less efficient. Publishers can use their first party data more efficiently to optimize their ad campaigns so that advertisers get more ROI.

For example, Tercept has optimized many campaigns based only on first party data from the Publishers and has been able to achieve 2X to 3X better CTR and viewability.
In the below image, Tercept has optimized one of our Publishers ad campaign for viewability and these are the segments created based only on Publisher’s First Party Data.
The overall viewability of the campaign is around 40% and through the segmentation, Tercept was able to give a segment with the viewability ~80% or 2X of the overall average.

Below is another example of Publisher’s inventory optimization based on Publisher’s first party data and optimized for CTR. To test this, we have created 2 similar line items in Google Ad Manager, one with Tercept Segments targeted and one without any Tercept Segments targeted.
We were able to achieve 1.75x better CTR than the base line item.

Publishers can use their demographic data, behavioral data, CRM data, Subscription data etc to make or create their own audience segments. There are a lot of variables that are available from this data such as frequency, last visited, user loyalty, gender, mobile make model, last clicked, last page visited etc.

Publishers can pick one or two variables from these, run a combination model and see if any particular combination gives better performance as compared to other combinations. But it needs continuous learning, trial and errors to arrive at an optimum solution. Publishers need to try these variables at a campaign level because variable behaviour can vary from campaign to campaign. There is no guarantee that a set of variables which worked for a campaign will work for another campaign. Usually this takes a lot of time and effort if Publishers try to achieve this manually.

So how can Tercept do this at scale? Because Tercept uses fully automated systems and algorithms to go through each and every variable from 30+ variables that are available from the data. Run various regression models to arrive at best sets of variables for each and every campaign which when applied gives exceptional results.

Vinay B Rao
Lead Analyst, Tercept

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