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Key Questions to Ask When Evaluating an Enterprise CDP

November 18, 2019

The Customer Data Platform Institute created the RealCDP designation to clear up marketplace confusion about the true purpose and capabilities of a CDP. While over 100 vendors offer what they consider CDPs, the institute bestows the RealCDP label on just 44 of them, RedPoint Global included.

According to the institute, there are five qualifications for a CDP to earn the RealCDP distinction:

  • Ingests data from all sources
  • Retains full detail of all ingested data
  • Stores the ingested data as long as the user wants
  • Converts the data into unified customer profiles
  • Makes the profiles available to all external systems/li>

That’s a lot to unpack for companies that are evaluating CDPs as the single source of truth for customer data and as the foundation of a future-proof martech stack. To further clear up confusion, we will address five questions every company should ask during the evaluation phase.

Dynamic, Rules-Based Application of Customer Data

The five RealCDP qualifications do not explicitly state that a CDP must perform all of those functions dynamically, but that is perhaps the most important consideration for any company evaluating enterprise-grade CDPs. A solution can ingest, retain, store, and convert data and make it available to external systems, but done statically it will not keep pace with a dynamic customer journey.

A rules-based solution that offers an in-the-moment, real-time, flexible decision at the moment of interaction makes all the difference between a real-time, dynamic journey and a list-driven journey that will, by definition, always be at least one step behind the customer. Attaching static information to a persistently updated golden record devalues the ultimate purpose of a CDP, which is to guide a customer journey with segment-of-one personalization in the context and cadence of a unique, omnichannel journey.

Data Enrichment for Deeper, Richer Insights

An enterprise-grade CDP should offer a broad set of data enrichment capabilities. Data enrichment is the merging of third-party data from an external authoritative source with existing first-party customer data.

Data ingestion is a core requirement of a CDP, but data enrichment is needed to make raw data useful. It adds additional layers of detail to first-party data, generating insights that help marketers deliver a more hyper-personalized customer experience.

Data enrichment is a key element of integrated identity resolution. And while it is not expressly covered by RealCDP, it is nevertheless an important topic and an important distinction between an enterprise-grade CDP and an also-ran. Brands poised to deliver omnichannel personalization recognize that well-functioning data enrichment is a key CDP capability.

Advanced Identity Resolution for an Anonymous-to-Known Journey

Identity resolution is another question to ask when evaluating a CDP, because creating relevant, personalized interactions requires not just enriched records but accurate and timely understanding of the customer journey across all touchpoints. Marketers should expect the CDP to dynamically map partial sets of details from identified and anonymous records to resolve a customer identity across an unknown-to-known customer journey.

Identity resolution is foundational for building an accurate customer profile. It should automatically identify customers across databases and engagement systems. Companies evaluating CDPs must be wary of solutions claiming to offer advanced identity resolution, but providing little more than matching and stitching together known identities. Advanced identity resolution requires understanding, tracking, and relating the complete range of identity elements – offline and online, anonymous and identified, shared and individual – to build identities in the context of households, organizations, and changing preferences and goals.

Identity Resolution Done Right: Building a Golden Record

To provide the performance, agility and control marketers need for engagement at the cadence of the customer, a CDP must natively include all the tools required to convert raw data into a golden record. This includes handling normalization, validation, and transformation of raw data – names, addresses, numbers, business details – from both structured and unstructured sources, along with all kinds of “housekeeping” items, like handling nicknames, abbreviations, incomplete or missing fields, and data entry errors.

The RedPoint Customer Data Platform standardizes the data and uses probabilistic and deterministic matching – with more than 375 built-in functions – to decipher individuals, households, cookies, IP addresses, and IoT smart devices, among others, and handles both digital and offline identities.

This process turns raw data into an identity graph that marketers use to create a personalized customer experience in any channel. Relying on data scientists to convert data into a unified customer profile is an unnecessary, time-consuming step when trying to keep pace with a customer in an omnichannel journey.

Not Just Another Solution for the Martech Stack

An evaluation should begin with an understanding that a CDP is not just another martech solution, but is an enterprise tool. As such, a major consideration is whether a CDP offers pre-built connectivity to all enterprise sources of customer data, or whether its performance relies on limited martech and channel connections.>

An open garden architecture that supports connection to all enterprise systems is different than “open garden light” which limits connections to the martech stack. While the latter may integrate limited e-commerce and CRM data, or offer the “escape hatch” of file imports, it still requires the IT department to do the heavy lifting to bring all relevant back-office data into the CDP. A real open-garden CDP should provide high-quality, high-performance native connections to data sources above and beyond the martech world – first-party, second-party, and third-party data, batch and streaming, big data, databases, message queues – to ensure that keeping pace with an omnichannel customer journey does not require an IT project to make a new connection happen.

And for Good Measure …

There are two additional questions to ask when evaluating a CDP that are related more to underlying performance rather than off-the-shelf capabilities. First, it is important to confirm the CDP you are evaluating meets an IT department’s security, compliance, privacy and governance requirements. In a modern, customer-centric world where data is king for creating a personalized customer experience, the data that goes into a CDP is high-value, high-risk data centered on the relationship between a brand and the customer. It is vital that this data is handled appropriately (in transit and at rest) as a high-value asset.

Second, a CDP must offer performance that matches the cadence of the customer. Like the dynamic application of rules at the moment of each interaction with a customer, this requirement underpins the requirement for real-time throughout the data lifecycle, real-time at the data level, at the analytics level, and at the orchestration level. In fact, in describing the five qualities needed to be a RealCDP, the CDP Institute takes pain to say that there are topics not covered under the RealCDP umbrella – and real-time data processing is first and foremost on the list.

If your CDP checklist includes all five core capabilities of a RealCDP, kicking the tires of real-time ensures you’ll walk away with a solution that’s ready for the high-speed twists and turns of a dynamic, omnichannel customer journey.