With the rise of privacy laws (like GDPR, CCPA) and the current/upcoming deprecation of third-party cookies (by Safari, Chrome), publishers are realizing that their monetization futures cannot rely on programmatic ads and third-party data.
By making their first-party data targetable, publishers can own their revenue destinies and move away from a reliance on programmatic ad exchanges, which are providing lower eCPMs than they once did, due to the aforementioned industry changes.
However, to accomplish this goal of first-party data activation, publishers need a sell-side, first-party Data Management Platform (DMP).
Such first-party DMPs for publishers share the following characteristics:
This article looks into what a sell-side, first-party DMP is and how it’s similar to, but apart from, third-party DMPs, buy-side DMPs, and Customer Data Platforms (CDPs). We'll also dive into the top 5 first-party DMPs.
Table of Contents:
A first-party Data Management Platform for publishers is a database used for storing, segmenting, and targeting specific user segments when they are back on a publisher’s digital properties - including websites, apps, and digital-out-of-home devices.
Their purpose is for publishers to drive new revenue by:
This data would be stored in a first-party DMP tied to an anonymized ID - such as a hash of the user’s log-in name:
"""curl User 8743b5206: { "Age": 35, "Gender": "Female" "Interests": "Music,Running" "Lifetime Purchase Amount": 500 } """
The publisher, via the first-party DMP, would then create segments off of this data, compiled of all users who fit those filters.
They’d work with advertisers directly (or DSPs) to set up direct-sold ad campaigns whereby buyers could target those specific audiences when those users are back on the publisher's site/app.
For instance, let's imagine an e-retailer called Shoes Emporium. They work directly with advertisers to display native ads within their site.
One of their customers is Nike, who is given the below advertising options:
To Nike, site-wide targeting may be interesting but not effective at driving new sales. Meanwhile, even though it's 10x the price, targeting the third segment may drive better return on investment.
To make this data actionable, the first-party DMP has to be connected to the publisher’s ad server in real-time, in order to incorporate the user-level data into the ad decision engine.
A first-party DMP for publishers can indeed overlap with a CDP, and many CDPs do have first-party DMP capabilities.
A Customer Data Platform is more holistic, though. Similar to a first-party DMP, a CDP ingests user-level information and makes it actionable, but differences include:
In that world, most CDPs will have DMP arms, but DMPs will not be synonymous with CDPs.
You’re right that DMPs have predominantly been used by advertisers/DSPs to buy targeted inventory across thousands of publishers. A publisher could work with these DMPs to buy/target third-party segments like “High Household Income” and show those users tailored creatives.
Without any targeting, a brand may see $100 cost-per-first-purchase from their ad spend, but by targeting, say, “High Household Income” users, perhaps it drops to $50.
This is also referred to as a “buy-side DMP” - which is why we want to separate out “sell-side DMP” / “DMP for publishers” from that use case, as it’s important publishers understand that they can use DMPs too.
While the veracity of such data is often questioned, it’s nonetheless used by advertisers to augment their marketing efforts.
While technically a third-party-data DMP is the technology used to store and make this third-party data actionable (while the buyers/sellers of that data are called “data providers”), the two overlap to the point where most data providers also have DMP offerings and vice versa.
This data is collected via a combination of sources - usually through buying it from apps/websites directly or paying for their tracking pixel to be dropped by a third-party. For instance, an iOS weather app may be collecting information tied to the Apple IDFA and selling that to a data provider.
This data is often tied to IP Address, mobile IDs, or cookie IDs, and advertisers generally don’t have access to the raw data. Since advertisers have limited ability to audit the data, they can’t independently validate its accuracy.
As mentioned above, third-party-data DMPs are mainly used by advertisers/DSPs to drive down acquisition costs and reach the right audience. They aren’t really used by publishers for monetization.
These third-party DMPs will increasingly be made irrelevant with privacy laws and third-party cookie removals - as it’ll be hard to compile and sell this third-party data.
As a whole, first-party DMPs provide little value to publishers focused on OpenRTB programmatic revenue. This is because DSPs are just not equipped to buy custom, single-publisher-based segments at scale via OpenRTB. Such intricate buys involve a 1-to-1 relationship in order to understand pricing and what goes into the segment. This is historically why publishers have not gravitated toward DMPs.
Here, DSPs/advertisers would work directly with the publisher and their ad server/SSP to target specific audiences. Such campaigns are effectively direct-sold ad buys enabled through programmatic technology.
A first-party DMP can store any information tied to a user that the publisher wants. Technically a publisher could buy third-party data and attach it to the user’s row in the DMP, which could then be used for targeting.
A publisher, for instance, may have a DMP tied to a hashed username. Meanwhile, the data provider may send over data tied to IP Address. While the publisher could tie the username to IP and then the IP to the third-party data, you start to enter a grey territory in terms of accuracy and precision.
And assuming you’re transparent about where the data is coming from, offering segments based on third-party data may not be particularly interesting to advertisers due to accuracy concerns.
Unlike CDPs, which provide macro trends and insights, DMPs are used for ad targeting and are not analysis tools. The way you view DMP success, therefore, is not through complex queries or Tableau visualizations, but through ad campaign performances.
When viewing an ad report, for example, you can analyze how a site-wide ad campaign compared to the campaign targeting just the “High Spenders” behavioral segment.
Yup!
Let’s take Facebook, whose ad platform garnered an impressive $70B in 2019. The success of their ad business - besides the scale - is their ability to do micro user-level targeting, all derived from their unique first-party data.
This targeting is enabled via an in-house, first-party DMP that collects information tied to each user, such as what’s in their profile, what they’ve shared, what they’ve clicked on, and so on.
This data is then tied to their in-house ad server and made actionable by their self-serve ad product, where advertisers can set up campaigns targeting segments of their choosing.
LinkedIn, as well, has an ad platform that turns first-party data like company, job title, and interests into actionable targeting - which has turned it into the $2 billion revenue driver it is today.
Many disparate events have led to a perfect storm for publishers. Privacy laws, ad blockers, and the upcoming demise of third-party cookies on Chrome all can/will impact publishers’ programmatic revenues. Without the ability to augment their buys with third-party data or do retargeting, advertisers will see worse performance and lower their bids, leading to drops in revenue for publishers.
Due to this, publishers are increasingly looking for new, innovative ways to monetize. Some have turned to native ads that can draw higher rates; some have moved to optimized internal promotions; and others have found ways to monetize their first-party data through audience segments and direct-sold deals (many have done all three).
First-party data is effective because it’s:
1. Hard to acquire at scale - Consumers don’t share their data with everyone. If you can get their demographic or interest data from a sign-up form or browsing behavior, you’re well ahead of most publishers.
Of course, scale is key too. Your niche app may have demographic data on 5,000 users, but the work to set up a campaign won’t be worth it for advertisers.
2. Accurate - Your first-party data is based on real-world behaviors and/or user-given information. If a customer freely tells you their age, gender, and favorite pastimes, one can be pretty confident this data is accurate.
Third-party data, on the other hand, while perhaps directionally accurate, is far from trustworthy. If you’d like to test this yourself, you can use the Oracle/BlueKai DMP’s registry to see what segments they bucket you into (they are one of the largest data providers in the world).
According to Oracle, I am a 76-year-old man from Denver with a Graduate Degree and teenagers and a veteran in my household. For the record, none of these are true.
3. Precise - Third-party data relies on approximations based on cookies, IP Addresses, mobile identifiers, and various other anonymized IDs. As compared to first-party data tied to, say, a username, these methods are imprecise (except, perhaps, mobile IDs - but those may be deprecated soon).
If a large apartment shares an IP, for example, all five residents may get targeted when only one of them should have. This doesn’t make the IP Address inaccurate, per se, but it’s imprecise in that targeting it may lead to false positives. First-party data tied to a persistent ID like username or a browser cookie, on the other hand, ensures that advertisers are reaching the right person.
4. Unique - Your data will be unique to your product - giving it extra value. LinkedIn, for example, knows where users work, what their job titles are, where they got degrees, and so on. This data is what powers their successful native ad product, since it’s information that advertisers can target against almost nowhere else.
Take Dictionary.com; with over 100 million monthly pageviews according to SimilarWeb, they have both scale and unique first-party data (in the form of dictionary searches). Unfortunately for them, this data doesn’t translate into premium value: would a behavioral segment around “People Who Searched For Adverbs” be of interest to advertisers? Probably not.
First-party data also needs to be actionable to be valuable. If you’re able to track user behavior but then can’t tie it to your ad server, it’s useless for monetization.
The data will be information that the publisher has collected on the user (with consent where applicable), including:
The information will be tied to a persistent ID, such as a hashed email/username, mobile identifiers like the IDFA or Google AAID, or a cookie-stored randomized ID.
In order to make a DMP actionable, this ID has to be passed in the ad request at time of page/app load. The ad server would then cross-reference this ID with the DMP. If it sees that User123 is a member of the “Shoe Lovers” audience segment, then that user would be eligible to see an ad targeting “Shoe Lovers”.
The main purpose of a first-party, sell-side DMP is that it connects to your ad server so user-level information can be factored into the ad decision engine.
For this to occur, one of the following is needed:
Below touches upon the industry leaders in the first-party DMP space. The best option for you will depend on what ad server you use, engineering resources, and whether you want CDP functionality.
Kevel is the market leader in server-side ad serving, enabled through APIs. With Kevel, brands can launch custom, fully-bespoke ad servers in a fraction of the time and cost of trying to build it from scratch.
Kevel’s tools include a built-in first-party Data Management Platform called UserDB. Brands can send their data via APIs and have the ad platform they’ve built reference it at time of ad request.
Capterra: 4.5 stars | G2Crowd: 4.5 stars
Once referred to as Audience Center 360 but now rolled up into their Analytics 360 product, this Google offering allows publishers to use Google Analytics to build behavioral segments, which can then be targeted as line items in Google Ads Manager and sold against.
Capterra: 4.7 stars | G2Crowd: 4.5 stars
Blueconic is a major CDP that works with the likes of Hearst, T-Mobile, ING, and more. In addition to unification and marketing activation, they offer integration with Google Ads Manager and Xandr/OpenX for PMP deals.
Capterra: 4.4 stars | G2Crowd: 4.3 stars
With $170 million raised and over 500 employees, Tealium is a powerhouse in the CDP realm. Including in this offering is a robust DMP arm.
Capterra: 4.4 stars | G2Crowd: 4.4 stars
1PlusX is a pure-play first-party DMP. Their focus is on turning first-party data into actionable segments - for both marketers and publishers. Because of this, they have integrations with multiple ad servers, including Google Ads Manager, Smart Ad Server, and Adform.
If you're still unsure of what to do next, get in touch with us today. We wish you the best in your quest to activate your first-party data.
