User Identification
Identifying users is needed to power ad targeting, content personalization, measurement, conversion tracking, attribution, and frequency capping.
There are different ways to identify users depending on the environment, such as whether the user is using a web browser or a mobile app:
  • Web browsers use cookies, device fingerprints, and local storage to identify users.
  • Mobile apps use device IDs to identify users.

User profile matching

Identifying users via one method can be incredibly difficult and inaccurate. The problem is exacerbated when users use more than one device, which is often the case nowadays.
Currently, there is no method that allows Ad Tech vendors to identify users as they move from one device to another. The reason for this is because the traditional ways of identifying and tracking users with cookies in web browsers weren't designed for the multi-device world.
There are, however, two ways you can identify and track the same user as they move across different devices with reasonable accuracy: deterministic matching and probabilistic matching.

Deterministic matching

Deterministic matching involves creating a profile of users comprised of different pieces of data about them. The most common way to deterministically match users in online advertising and marketing is by using an email address as the common identifier, as this is unique to the user and is often available in different data sets.
Companies like Facebook, Google, Twitter, and LinkedIn are able to deterministically match users with ease and accuracy because they require users to create accounts and sign in using an email address to access their applications and sites on different devices.
The main advantage of deterministic matching is accuracy. It’s much more accurate than probabilistic matching; most deterministic matching rates are around 80-90%.
The main drawback, however, is that it lacks in scale, as most companies don’t collect this type of data and email addresses aren’t typically used for buying and selling online advertising. To address the issue of scale, publishers are requiring users to create an account or subscribe using their email address to access certain content.

Probabilistic matching

Probabilistic matching uses various pieces of data, algorithms, and statistical modeling to make a match.

Solutions to the identity problem

Due to the direct and severe impact privacy laws and privacy settings are having on identity in online advertising, and the inefficiencies of cookie syncing, various companies and groups have proposed numerous ID solutions.
The main goals of these ID solutions are to:
  • Identify users on web browsers as they move from website to website.
  • Reduce page-load latency caused by cookie syncing.
  • Compete with the walled gardens of Google and Facebook that have access to deterministic data and can offer advertisers better targeting, measurement, and attribution.
There are many companies that are providing solutions to the ID problem, but here are the main ones:
The Trade Desk offers Ad Tech and data companies free access to its Unified ID solution (TTID), which is hosted under the adsrvr.org domain.
The IAB Tech Lab & DigiTrust ID is a non-profit, neutral ID solution that is only accessible to registered members.
The Advertising ID Consortium is powered by the LiveRamp ID and hosted under the AppNexus domain, even though AppNexus withdrew from the consortium when it was acquired by AT&T in August 2018.
ID5 is a company that allows publishers, data companies, and Ad Tech vendors to outsource their cookie syncing processes with their partners and use ID5’s cookie-matching table.
These solutions are not designed to compete against one another. The goal behind forming multiple ID solutions is to solve the ID challenges collectively as an industry and to offer Ad Tech vendors, data platforms, and advertisers a choice when it comes to selecting an ID provider.
Another ID solution gaining traction includes Flashtalking’s Identity Management, which uses cookie-less tracking and collects data from different devices to create a deterministic ID that can be used for audience targeting across websites and apps, measurement, and attribution.

How Do These ID Solutions Work?

Most of the ID solutions work similarly to each other and act as an ID distribution and retrieval service. They manage the cookie-syncing and ID-matching processes on behalf of different Ad Tech platforms, so instead of DSPs and SSPs having to sync cookies between themselves, they could centralize the process via an ID solution.
Last modified 7mo ago