Building a complete understanding of your audience, often referred to as a 360-degree customer view, is increasingly challenging. As the number of devices and channels consumers use to interact with brands and consume content grows, so do the number of data points each individual creates.
Identity resolution is the process of connecting multiple identifiers across different devices and platforms, enabling each of these different data points to be associated with a single individual.
As we have alluded to, this process has become increasingly important as consumers move across channels and devices at an increasing rate throughout the data including; desktop, mobile, connected TV and audio devices. Here’s a common scenario:
The goal of identity resolution is to allow brands and media owners to recognise that this is the same person across all of these devices, instead of treating them as four different people. This provides marketers with a clear understanding of consumers at an individual level, and real-time knowledge of where they are on their customer journey.
A single, unified customer view is the Holy Grail for marketers at brands. By knowing who an individual is across multiple devices, and where they are in the customer journey, brands can deliver timely and personalised messaging which increases return on advertising spend and reduces media spend wastage.
Brands who can do this successfully are able to deliver superior customer experiences and improve brand loyalty. One of the key benefits of identity resolution for brands, is the ability to deliver effective people-based marketing.
People-based marketing is a data driven marketing strategy that enables advertisers to target individuals with personalised messaging based on their previous interactions with their content. It is proven to increase the performance of marketing campaigns, with 90% of advertisers saying they see an improvement from people-based marketing.
Identity resolution doesn’t just serve brands looking to target current, lapsed and new customers, it enables media owners to build more effective addressable audiences, and in turn make those audiences available for advertisers to plan and activate against.
For example, identity resolution allows a broadcaster to recognise the same individual using multiple devices to access their video on-demand service. Identity resolution in this case is often driven by authenticated data such as a login. This ensures the broadcaster has a complete understanding of their audiences viewing habits, therefore enabling them to offer advertisers people-based marketing capabilities.
Though there are many different uses for identity resolution, the ways in which it works behind the scenes remain the same. There are two methods in which businesses connect the dots and make sense of the millions of data points they have about their customers - deterministic and probabilistic.
Deterministic ID identity resolution is the most accurate way of matching identities. It is only possible where a unique identifier is present in each of the data sources. Two achieve one-to-one matching, these unique identifiers are often based on personal data (PII) such as email addresses, home addresses or phone numbers. It allows for advertisers to identify with 100% accuracy that two data points relate to the same individual.
Deterministic identity resolution is what powers the examples we mentioned above for a broadcaster. The unique ID here is the user’s email address, so when the user logs in on different devices, the service provider can tie two data points (two devices) to the same individual using the email address as a unique ID.
InfoSum’s identity infrastructure utilises deterministic identity resolution to connect the various parties in the advertising ecosystem, but is also capable of using probabilistic identity resolution where deterministic matching isn’t possible, or where scale is limited.
Where PII isn’t available for matching, probabilistic ID matching uses statistical analysis to make an informed decision on the likelihood that a combination of identifiers relate to the same customer. Identifiers in this instance are things such as an IP address.
As an example, a publisher could determine with relatively high accuracy that multiple devices on the same IP address are used by the same individual. Therefore behaviour exhibited on those devices can be tied to a single individual
While not as accurate as deterministic methods, one advantage of this method is scale as you are not reliant on PII data to identify individuals across devices.
As mentioned above, InfoSum supports both deterministic and probabilistic identity resolution techniques. Through our platform, clients are able to transparently select the type of match key (deterministic or probabilistic) that best suites their requirements.
In the past, third-party IDs have been used as a proxy for identity, third-party cookies being the most infamous type of these ID’s. These small files were dropped by adtech vendors on an individuals web browser when they visited certain websites. Once the cookie was placed, the ‘owner’ of the cookie can then track and target that individual across multiple sites. These cookies can then be ‘synced’ (traded) between the various ad platforms, enabling advertisers to target their audience on various publisher sites.
This approach has come under increased scrutiny, not only due to the lack of accuracy, but more significantly around consumer privacy and trust. For this reason, Apple and Mozilla began blocking third-party cookies by default in 2017, and Google has now confirmed they will follow suit in 2022 - leaving this method of identity resolution obsolete in the near future.
Universal IDs provide an alternative but come with significant risks of their own, specifically around the centralisation of data and management of consent. As Universal IDs are delivered in a first-party environment, many believe this to be a privacy-compliant way to gather identity information. The trouble is, this data still needs to be shared and centralised by a third-party to make sense of it. This creates similar security, privacy and commercial challenges as with third-party cookies.
With tightening privacy legislation and consumers becoming more savvy about how their data is used online, Universal IDs may well come under increasing scrutiny in the future.
For advertisers, the use case for identity resolution is through data onboarding. Data onboarding is a process that brings together both online data, such as website behaviour, social media activity, app activity, and offline data such as point-of-sale and CRM data. By resolving the identity gap between offline and online data, advertisers are able to both attain a more holistic view of the customers, and also use their offline knowledge to inform online marketing activity.
First-generation data onboarding solutions have required a brand to move their customers personal data into a third-party environment, where their data is flattened to the identity vendor's own ID. This raises significant trust and privacy challenges. Luckily, new technology makes data onboarding possible without having to share data - you can see the future of data onboarding in this blog post.
Where a single unique identifier can not be used to match identities between offline and online data sources, an identity graph is required.
An identity graph, or ID graph, brings together all the various identifiers associated with an individual, and ties them to a single unique identifier. Identity graphs are an important tool when resolving identities due to the sheer number of IDs that can be associated with one individual; including email address, home address, phone numbers, IP address, device IDs, usernames and loyalty cards, to name just a few.
Tying these identifiers together into a single view, along with related data points such as behavioural and demographic data, gives publishers or brands the foundation to deliver personalised messaging and superior experiences.
While brands can build their own sense of identity using their first-party data, to achieve the scale often desired by advertisers, often a third-party identity vendor is required.
However, using an identity vendor has traditionally meant sending your valuable data assets to a third-party to be synced and the resulting audience then ends up siloed in the identity vendor’s, interoperable, ID. The result is trust and security challenges with this method, not to mention the risk to commercial value in handing over your data over to another company.
Our federated, privacy-by-design identity infrastructure means you don’t have to share data to collaborate and you remain in control of your data at all times. Essentially, you own your own identity. By this we mean identity isn’t owned by one central source, rather it's distributed between any number of brands or media owners with whom you have a relationship with. It’s a new era for identity resolution, one that removes the need for trust and allows for greater scale as you’re not limited to one identity vendor.
Using InfoSum’s identity infrastructure, brands, media owners and data providers can resolve identity without having to share data or rely on a third-party ID. Our identity infrastructure provides a secure and privacy-safe way to connect multiple first and second-party data sources.
By removing the need for a third-party ID, we can deterministically match on PII data using existing online and offline identifiers in the original data (e.g. email address, phone number, device ID). Where a single identifier is not available, multiple non-unique identifiers can be combined such as date of birth and postal address to create a match.
The InfoSum identity infrastructure is completely agnostic and not limited to just overlaying one identity graph either - multiple graphs can be overlayed instead of a brand’s data being tied to just one. By removing the reliance on a single identifier, multiple channels can be addressed (OTT, digital, mobile) leading to a far greater understanding of their customers.
Identity resolution with InfoSum means you can gain actionable insights from multiple data sets and know your customers more deeply, without any of the privacy or security challenges of sharing your data.
Get started with privacy-safe identity resolution here.