Service Providers
There are a number of data services providers supplying a range services to assist with the collection and use of data along the ad tech supply chain, including data management platforms, ad verification and attribution providers, and data brokers.
Some DSPs and SSPs may also provide some of the same functions as data services providers, which means that advertisers and publishers may not always require the services of separate data service providers. For example, Google Ads and Amobee have ad targeting capabilities.

Data management platforms

Data management platforms provide publishers, advertisers, DSPs and SSPs with tools to store, manage and analyse their own data sources and any data they obtain from other parties.
The key functions of data management platforms include:
  • combining data directly collected by the publisher (first-party data) with data obtained from others (third-party data), which may include information such as user purchase history, geographic data and sociodemographic data
  • analysing data to enable the targeting of ad campaigns to particular consumers or groups of consumers, and
  • using data, including from ad campaigns, to analyse ad performance and to manage ad campaigns.
The main data management platforms include the Google Analytics 360 Suite, Oracle, SalesForce, Lotame, Eyeota and Adobe.

How does it work?

A DMP can collect unstructured audience data from any source, including desktop, mobile web, mobile app, web analytic tools, CRM, point of sale, social, online video, offline and even TV.
This first-party data can be collected based on specific behaviors such as clicks, downloads, video uploads or video completions, interests like sports, football, parenting, museums and travel or demographic information. It can also include demographic data, socio-economic data, influencer and action data. As an example, a business can use a DMP to collect and organize data, then use that data to target a particular ad to moms who are 25-35.
Once the first-party data is collected, it is organized into a series of segments called a “hierarchy”, which can change based on each end user’s business models. A large publisher network may have their hierarchy divided up into different buckets based on each of the individual websites they own. An agency can have separate accounts for each of their advertiser clients. Marketers could manage different brands’ data separately, while also having an overall holistic view of the data at the top level.
1. Organization
A DMP will organize your first-party audience data into categories and taxonomies, which are specified by those using the platform — in this case, that would be you. You define how that data is organized, which means you need to understand — and define — what you need out of your data before deploying a DMP.
2. Segmenting and Audience Building
Once the data is organized into the platform into segments, you can use this information to build audiences for specific marketing campaigns. For example, a retailer may want to target one particular ad to females 18-34 while another may be focused on men who frequently buy shoes online. Regardless of who they are trying to reach, marketers, publishers and advertisers rely on audience segmenting to power their data-driven campaigns and reach the right consumers at the right time.
3. Insights and Audience Profile Reports
Soon after the data has been organized and classified, you can take chunks and analyze it to discern customer patterns, trends and intent.
Audience Profile Reports give an in-depth view of the characteristics and interests of each “audience” that has been built in the platform. This information can be used to inform your future creative and messaging.
4. Activation
The final step is to activate the data, by putting it to work! This activation step relies on the DMP having integrations and open APIs with other platforms, so that the audiences you build in the DMP can be seamlessly transported to DSPs, SSPs, and beyond. The most common DMP use case is running a targeted campaign to a specific audience via a DSP. Or, you can connect the DMP to your content management system (CMS) to adjust the content of your website for certain audience groups. The possibilities and use cases for data activation with a DMP are limitless.

Customer Data Platforms

DMPs have risen in prominence in recent years, as the lack of incentives for DSPs to integrate them pushed them to adopt a direct sales strategy. Today, we're witnessing a rebranding effort from DMPs to CDPs. They're increasingly becoming an entry point for advertisers, who are then told which DSPs to go and use.

Pricing

Many DMPs offer data in bulk, but most sales are done in the context of programmatic ads. Advertisers will use their DSP to choose audiences based on DMP integrations it offers, or upload their audiences directly. In most cases, DMPs need to be integrated both on the SSP and DSP side to work. DSP users choosing one or more DMP-sourced audiences for targeting rely on the SSP to send the same audience ID with the ad request.
Pricing is more often than not CPM-based. Both the DSP and the DMP will track impressions, and that's what the advertiser will be billed on.

Ad verification and attribution providers

Advertisers use ad verification and attribution providers to:
  • verify the delivery of ads in a brand-safe setting – that is, not adjacent to any publisher content that is unsafe, inappropriate, or incompatible with the advertiser's brand
  • verify that the ads delivered were delivered in a way that is viewable to the consumer
  • detect instances of ad fraud (e.g. when fraudulent consumer traffic is generated by bots), and
  • assess the performance of campaigns.
Some main ad verification and attribution providers include Adjust, Google Analytics 360 Suite, Moat (owned by Oracle), DoubleVerify, Comscore, and Integral Ad Science.

Data brokers

Data brokers (also known as data providers) supply data (or insights generated from the analysis of data) to market participants along the ad tech supply chain to supplement any first-party sources of data they may already have. Data providers mostly provide inferred data generated through their own processes, using volunteered, observed and inferred data. Data providers may collect data from a variety of sources, including from third-party cookies (now dying) and pixels on publisher sites, from public information such as online records, and from the records of public authorities or third-party companies such as banks or retailers. Data providers will then create databases of individuals (called audiences), which advertisers can then purchase and use for targeted advertising.
Some main data providers include the Google Analytics 360 Suite (which does not provide third-party data directly to other market participants but contains tools to enable advertisers and publishers to leverage the insights from Google's own data stores), Datalogix (owned by Oracle), LiveRamp (formerly Acxiom), Experian, Quantium, and Nielsen.
Data brokers may utilize various business models, but on the most basic level, data brokerage involves sourcing and aggregating data, and reselling the most valuable categories of users to third parties. For example, one of the biggest scandals to date involved a data broker that sold to advertisers contact data of rape victims, alcoholics, and erectile dysfunction sufferers. Such lists sold for $79 per 1000 contacts.
When audience segments are sold to Ad Tech companies, they are often sold on a CPM basis, or as a percentage of media.
Even though we often hear stories about data brokers selling sensitive data to advertisers, most data brokers, especially those who sell it to mainstream advertising companies, don’t sell such sensitive data, and focus on the more common categories like sports enthusiasts, music lovers, impulse buyers, etc.
Last modified 7mo ago