Blog Post:Second-party data is so hot right now. Various publications have claimed 2016 as the year 2nd-party data goes mainstream, and as a DMP (data-management platform) practitioner, I have to agree with that assessment. But, as we will explore in this post, all 2nd-party data is not created equal.

Read: Is 2016 the year marketer's embrace data sharing?

As marketers look to reach new audiences that are similar to their best customers, they have to rely on external datasets to find those audiences. And, as they look outward, they have to make a choice between scale and access. Do I use data that is easily accessible but also available to my competition? Or, do I put in the effort to find exclusive datasets that provide inherent advantages?

That choice between scale and access is not binary. The 2nd-party data ecosystem is a continuum, with the characteristics of 3rd-party data at one end and 1st-party at the other:

Image - 2nd Party Continuum In -Text 1

Before we explore the rise, and subsequent stratification, of 2nd-party data, let's review why the trend is picking up steam now. 3rd-Party Data Is Everywhere Buying 3rd-party data is a proven way to reach new customers. It aggregates behavioral and intent signals in a way that no marketer could do on their own. But, there is also a lot of it. Every DMP or DSP (demand-side platform) worth its salt offers seamless access to 3rd-party data, and typically, dozens or hundreds of data sources. The concern is no longer access but choice. How do I decide which provider to work with? Making this decision more difficult is the fact that many 3rd-party providers pull their data from the same sources. Take “in-market” data, for example. The vast majority of this data comes from pixeling highly trafficked websites to collect behavioral signals. A person searching for “Bermuda” is in market for a cruise. A person reading an article about the Tesla 3 launch is in market for an electric car (and “green energy” and “healthy living” and “social causes,” and a number of other marketable data traits). If you're curious about where all of this in-market, or behavioral, data is coming from, download the Ghostery browser plug-in.

Download Ghostery

For many large publishers, you'll see between 30 – 50 tags on the site, with many of these beacons designed to collect data signals for advertising. Image - 2nd party Contimuum In-Text 2

44 trackers collecting the same data and offering it in different packages. It's the same data! Doesn't anybody notice this? I feel like I'm taking crazy pills (sticking with the whole Zoolander-theme)!

Assuming you can source the right 3rd-party dataset and use it to power your advertising, you are then confronted with the reality that your competition has the same access and may be bidding against you for the same inventory. The Rise of 2nd-Party Data The desire for more accuracy, transparency, and competitive differentiation fuels the 2nd-party data economy. The easiest way to think about 2nd-party data: it's somebody else's first-party data. An airline knows who its rewards customers are. They know their business travelers. For a credit-card company, this is very valuable information, and they would love to market their “travel rewards” cards to known business travelers. If the airline and the credit-card company are partners, sharing this information makes a ton of sense. This is 2nd-party data sharing — the original, pure form of 2nd-party data. Beyond this simple swap (Advertiser A and Advertiser B share data), there is a spectrum of use cases where two entities make their owned data available to one another: The new, key concept here is monetization, and it is typically driven by a publisher that is looking for a way to monetize its data assets. That distinction is critical — because we now see 2nd-party data packaged and sold like 3rd-party data. Selling 2nd-party data in this way will certainly make it more available but will also drive down the value as it becomes more and more commoditized (and less about relationships). A publisher may allow a data aggregator to pixel their site and collect data. An advertiser can then buy that data from the data seller. But, what if the advertiser already has a relationship with the publisher? Can they access that data directly without having to buy it through an intermediary? The 2nd-Party Data Continuum If we begin to break down the 2nd-party data section of the previous chart, we must compare availability and exclusivity and understand whether the intent of the data share is monetization or relationship-building: Image - 2nd Party Continuum In-Text 3 2nd-Party Data at Scale Marketplaces that enable the sale of 2nd-party data do so in a way that is modeled off of the 3rd-party data business: low friction, high discoverability, with the ability to transact online. Data sellers profit from an open marketplace but at the risk of devaluing their data as access, control, and scarcity are sacrificed for scale. Private Marketplace To preserve control and establish a tighter relationship with potential 2nd-party partners, some data marketplaces offer the ability for sellers to privately transact. In this workflow, the listing is typically unbranded (e.g., “in-market travel data from top domestic airline”), and the data provider has the ability to approve buyers before their identities are known. One to One (1:1) Relationships At the furthest end of the 2nd-party continuum is a 1:1 data exchange between two parties. This can be facilitated with technology, such as a DMP, but is typically based on a separate partnership agreement, and the data is not listed in any marketplace for sale. This is certainly not a scalable model, but the benefit is that the exchange is based on a trusted business relationship, and the data being acquired is more scarce and usually a better compliment to the marketer's own 1st-party data. I'm Evaluating Ad Tech — Why Does This Matter to Me? When looking at the ad-tech landscape — and specifically, the DMP industry — it's clear that the major providers are gravitating toward certain points on this data continuum. Some DMP vendors are focusing their solutions around the reach and access to 3rd-party data. Others look to link 2nd-party data across their clients to make partner data widely accessible. The Adobe Audience Manager platform is built on the philosophy that a client's 1st-party data is its most valuable asset, and sharing that data should be done with trust and discretion top of mind. 2nd- and 3rd-party data should be accessible to those who want it — made available by those who choose to share it — but monetization and distribution should take a backseat to governance and control. The selection of your technology vendor should be dictated by how well its approach aligns with your data-management needs and data-ownership philosophy.

Author: Date Created:April 15, 2016 Date Published: Headline:The 2nd-Party Data Continuum: “Data Sharing — It’s So Hot Right Now” Social Counts: Keywords: Publisher:Adobe Image:https://blogs.adobe.com/digitalmarketing/wp-content/uploads/2016/04/Image-2nd-Party-Continuum-e1460667484235.jpeg

Second-party data is so hot right now. Various publications have claimed 2016 as the year 2nd-party data goes mainstream, and as a DMP (data-management platform) practitioner, I have to agree with that assessment. But, as we will explore in this post, all 2nd-party data is not created equal.

Read: Is 2016 the year marketer’s embrace data sharing?

As marketers look to reach new audiences that are similar to their best customers, they have to rely on external datasets to find those audiences. And, as they look outward, they have to make a choice between scale and access. Do I use data that is easily accessible but also available to my competition? Or, do I put in the effort to find exclusive datasets that provide inherent advantages?

That choice between scale and access is not binary. The 2nd-party data ecosystem is a continuum, with the characteristics of 3rd-party data at one end and 1st-party at the other:

Image - 2nd Party Continuum In -Text 1

Before we explore the rise, and subsequent stratification, of 2nd-party data, let’s review why the trend is picking up steam now.

3rd-Party Data Is Everywhere

Buying 3rd-party data is a proven way to reach new customers. It aggregates behavioral and intent signals in a way that no marketer could do on their own. But, there is also a lot of it. Every DMP or DSP (demand-side platform) worth its salt offers seamless access to 3rd-party data, and typically, dozens or hundreds of data sources. The concern is no longer access but choice. How do I decide which provider to work with?

Making this decision more difficult is the fact that many 3rd-party providers pull their data from the same sources. Take “in-market” data, for example. The vast majority of this data comes from pixeling highly trafficked websites to collect behavioral signals. A person searching for “Bermuda” is in market for a cruise. A person reading an article about the Tesla 3 launch is in market for an electric car (and “green energy” and “healthy living” and “social causes,” and a number of other marketable data traits).

If you’re curious about where all of this in-market, or behavioral, data is coming from, download the Ghostery browser plug-in.

Download Ghostery

For many large publishers, you’ll see between 30 – 50 tags on the site, with many of these beacons designed to collect data signals for advertising.

Image - 2nd party Contimuum In-Text 2

44 trackers collecting the same data and offering it in different packages. It’s the same data! Doesn’t anybody notice this? I feel like I’m taking crazy pills (sticking with the whole Zoolander-theme)!

Assuming you can source the right 3rd-party dataset and use it to power your advertising, you are then confronted with the reality that your competition has the same access and may be bidding against you for the same inventory.

The Rise of 2nd-Party Data

The desire for more accuracy, transparency, and competitive differentiation fuels the 2nd-party data economy. The easiest way to think about 2nd-party data: it’s somebody else’s first-party data.

An airline knows who its rewards customers are. They know their business travelers. For a credit-card company, this is very valuable information, and they would love to market their “travel rewards” cards to known business travelers. If the airline and the credit-card company are partners, sharing this information makes a ton of sense. This is 2nd-party data sharing — the original, pure form of 2nd-party data.

Beyond this simple swap (Advertiser A and Advertiser B share data), there is a spectrum of use cases where two entities make their owned data available to one another:

  • Publisher 1 and Advertiser A share data
  • Publisher 1 shares its data with Advertiser A (i.e., Advertiser A spends a lot of money with Publisher 1 and negotiates data for an upfront buy)
  • Advertiser A sells its data to Advertiser B
  • Publisher 1 sells its data to Advertiser A

The new, key concept here is monetization, and it is typically driven by a publisher that is looking for a way to monetize its data assets. That distinction is critical — because we now see 2nd-party data packaged and sold like 3rd-party data.

Selling 2nd-party data in this way will certainly make it more available but will also drive down the value as it becomes more and more commoditized (and less about relationships).

A publisher may allow a data aggregator to pixel their site and collect data. An advertiser can then buy that data from the data seller. But, what if the advertiser already has a relationship with the publisher? Can they access that data directly without having to buy it through an intermediary?

The 2nd-Party Data Continuum

If we begin to break down the 2nd-party data section of the previous chart, we must compare availability and exclusivity and understand whether the intent of the data share is monetization or relationship-building:

Image - 2nd Party Continuum In-Text 3

2nd-Party Data at Scale

Marketplaces that enable the sale of 2nd-party data do so in a way that is modeled off of the 3rd-party data business: low friction, high discoverability, with the ability to transact online.

Data sellers profit from an open marketplace but at the risk of devaluing their data as access, control, and scarcity are sacrificed for scale.

Private Marketplace

To preserve control and establish a tighter relationship with potential 2nd-party partners, some data marketplaces offer the ability for sellers to privately transact. In this workflow, the listing is typically unbranded (e.g., “in-market travel data from top domestic airline”), and the data provider has the ability to approve buyers before their identities are known.

One to One (1:1) Relationships

At the furthest end of the 2nd-party continuum is a 1:1 data exchange between two parties. This can be facilitated with technology, such as a DMP, but is typically based on a separate partnership agreement, and the data is not listed in any marketplace for sale.

This is certainly not a scalable model, but the benefit is that the exchange is based on a trusted business relationship, and the data being acquired is more scarce and usually a better compliment to the marketer’s own 1st-party data.

I’m Evaluating Ad Tech — Why Does This Matter to Me?

When looking at the ad-tech landscape — and specifically, the DMP industry — it’s clear that the major providers are gravitating toward certain points on this data continuum. Some DMP vendors are focusing their solutions around the reach and access to 3rd-party data. Others look to link 2nd-party data across their clients to make partner data widely accessible.

The Adobe Audience Manager platform is built on the philosophy that a client’s 1st-party data is its most valuable asset, and sharing that data should be done with trust and discretion top of mind. 2nd- and 3rd-party data should be accessible to those who want it — made available by those who choose to share it — but monetization and distribution should take a backseat to governance and control.

The selection of your technology vendor should be dictated by how well its approach aligns with your data-management needs and data-ownership philosophy.