Introduction
CDPs aren’t cut out for enterprise identity. And with the right identity solution, they don’t need to be.
Brands need a robust identity strategy. It’s the only way to know who their customers are and create relevant, personalized experiences that help them acquire, grow, and retain those relationships.
But a misconception we come across (on an almost daily basis) is that brands think they don’t need an enterprise identity solution because they’re using, or at least considering using, a customer data platform (CDP). We hear the same thing about a few other marketing technologies too, but it happens most often with CDPs, so let’s focus on those for now.
It’s not hard to see why so many brands think CDPs will meet their identity needs. At a basic level, CDPs are designed to unify customer data from disparate systems, which requires some form of key or identifier. So, many brands assume these platforms have enterprise identity baked in.
But identity is generally not a strength of CDPs.
This is not to be negative about CDPs – far from it. In fact, we believe every brand should invest in one to achieve unified, accessible first-party customer data. We actually partner with some of the biggest names in the CDP space (such as Salesforce, Sitecore, and Treasure Data) to help brands implement, optimize, and operate those platforms.
Most CDPs simply aren’t designed to support enterprise identity — they were never intended for that purpose. If your brand doesn’t integrate your CDP with identity at the enterprise level, there’s a risk it will become yet another data silo and will achieve mediocre performance at best.
To maximize the performance of your CDP, you need to extend its capabilities with an enterprise identity solution, including a brand identity graph.
Let’s examine why.
You get to know customers at the person level
CDPs typically approach identity using basic, deterministic matching of whichever identifiers they can directly observe in the brand’s first-party data, at a particular point in time. They might look for the same cookie, the same device ID, or the same email address, for instance. This easily leads to undermatching, where one individual has multiple profiles, or overmatching, where multiple people are grouped together under one persona.
Under and overmatching
Imagine, for example, that Sam signs up for a loyalty program in store using one email address and then, some weeks later, signs up for marketing emails from the same retailer using a different email address. A CDP is likely to create two different personas for Sam, leading to disjointed and frustrating brand experiences, such as ad bombardment.
Equally, when Sam’s partner Lindsay uses a laptop they share to also sign up for email marketing from that retailer, a CDP may well see the same device ID and assume it is the same person. The CDP will then link Lindsay’s record to Sam’s second persona, rather than creating a distinct identity that would enable experiences that are relevant and personalized to Lindsay.
When your CDP is integrated with an enterprise identity solution that uses more sophisticated matching and a brand identity graph, it has real-time access to far more touchpoints for potential matches beyond the information it can directly observe. It can see that one individual has multiple email addresses, or that a single device is used by multiple people. This means records can be linked far more effectively and accurately to enable person-level identity.
An identity graph also enables the CDP to recognize the relationships that exist between people, for instance within households, helping your brand deliver experiences that really make sense for each individual.
Identity terms defined
Deterministic matching: Assigning identity by establishing an exact match between two pieces of data such as a full name, email address, or mobile number.
Probabilistic matching: Assigning identity based on a wide variety of data signals and connections that infer who the individual is likely to be.
First-party identity graph: A private graph, unique to a brand, linking first-party data and third-party insights with customer identifiers to enable consistent cross-channel experiences.
Referential identity graph: A third-party reference graph providing non-intuitive connections that aren’t evident in a brand’s first-party data.
Enterprise identity: A single, connected identity solution across a brand’s entire enterprise, available to any department (e.g. marketing, operations) in order to enable a complete and consistent customer view and understanding.
You have more complete data on which to base decisions
As we mentioned earlier, CDPs generally only use a brand’s first-party customer data. This data is, of course, incredibly valuable for understanding the customer’s relationship with the brand, but it is often incomplete and only delivers a limited snapshot of that customer.
When you use an enterprise identity solution alongside your CDP, you can make the most of your valuable first-party data by supplementing and enriching it with additional information. You could, for example, use third-party referential graphs containing data about households, nicknames, or married and maiden names to ensure your data is complete and improve matching capabilities.
These third-party referential graphs are created by vendors who gather deterministic links from many different sources, or who observe visitors of popular websites, or users of popular mobile apps, to capture huge volumes of behavioral data.This enables them to probabilistically (and ethically) link interactions across channels and devices, where no connection would be evident in a brand’s own first-party data.
Filling the identity gaps
To understand the incremental lift a brand can achieve using an enterprise identity solution, we analyzed almost 14 million first-party data records from a well-known retail brand that had decided to use a CDP alone to support identity and marketing requirements but wasn’t satisfied with the results.
We found significant gaps in the data such as:
- Email address-only records, with name and address fields left blank
- First name left blank or initial only
- First name only with no last name populated
All these issues presented a significant hurdle to effective matching but could be largely overcome using an enterprise identity solution.
When we applied record completion to append addresses to records with blank fields, we were able to enhance 39% of incomplete records. This one small example illustrates how this retail brand is missing out on vital customer insights by relying on first-party data within a CDP and not using an identity solution with referential graphs to create more connections.
An enterprise identity solution can help improve the overall quality of your brand’s first-party data through cleansing, correction, and completion – standardizing and validating information so it can be better used to deliver personalized, relevant experiences.
You benefit from a broader, more holistic customer view
Every type of marketing technology has its individual strengths, and for CDPs one of those strengths is bringing together data at a particular moment in time to power a specific decision or interaction.
But when it comes to identity, this strength can also be considered a weakness. CDPs were never designed to replace longitudinal databases with contextual information that provides a more holistic understanding of the customer. Their simplistic approach to creating a single in-the-moment customer view means the output is often incomplete or inaccurate, so it can’t be used to drive performance over time.
Records in a CDP are restitched daily with no historical context, which can result in marketing that ignores lifestage considerations and lifestyle factors that may be vital to delivering exceptional customer experiences, and maximizing your brand’s return on marketing investment.
When a CDP is used in tandem with an enterprise identity solution, these issues can easily be overcome. Brand identity graphs have persistent person-level identifiers and take historical context into consideration when they are updated, resulting in enriched personas and increased customer intelligence accuracy, so you can gain a holistic understanding of your customers and engage with relevance.
You have visibility across the full customer journey
CDPs are able to collect customer data across your brand’s owned properties, such as your website, your mobile app, and your marketing emails. But this is a relatively narrow view, meaning you only have limited visibility into the customer journey.
By using an enterprise identity solution alongside your CDP you can expand your customer view with first-party tagging. This enables you to collect data across paid as well as owned media, allowing you to see and orchestrate the full consumer journey, from the initial awareness stage all the way through to purchase and loyalty.
Where is your brand with CDPs and identity?
A CDP is quickly becoming an essential part of every brand’s marketing toolkit, but adoption varies greatly between brands and sectors. Are you already using a CDP but not getting the results you hoped for? Or maybe you’re only just considering which CDP to choose and are exploring the identity capabilities it can offer?
Wherever you are on the CDP adoption journey, why not get in touch with Acxiom for an identity health assessment and find out how your current identity strategy holds up? We can show you the type of customer intelligence you are getting (or would get with any marketing technology you are considering) and explore how that could be enhanced with the right identity solution.
Talk to one of our identity experts to find out more.
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