Most marketers today share two problems: fragmented systems and customers who want a unified experience. Customer data platforms (CDP) promise to close the gap between the two by gathering data from all sources, transforming it into unified customer profiles, and sharing those profiles with any system that wants them. Many CDPs go even further to create segments and recommend the best treatments for each individual.
It’s no wonder that CDPs have gained so much attention.
But once the initial excitement wears off, marketers quickly find that “unified customer profile” can mean many different things and that CDPs do in fact vary widely. Even more confusing, other systems, including customer relationship management (CRM) platforms, marketing automation tools, and data management platforms (DMP), create unified profiles of their own.
Marketers can either throw up their hands in frustration or buckle down to understand the details of what CDPs can really do. Just giving up would quickly lead back to the original problems of disjointed data and unhappy customers. So plunging ahead is the more promising choice.
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What Marketers Can Do With CDPs
Technicians might start with an exploration of CDP technology. But most marketers will be more interested in what a CDP can do than how it works. Specifically, they will want to know what’s possible with a CDP that isn’t possible without one.
Here are some examples of what CDPs can do:
Capture New Data
CDPs ingest all kinds of data without mapping each element to a predefined data model. This means marketers can add new sources more quickly.
Example: Identify brand advocates by reading data from a new social media service to uncover customer identifiers and sentiments expressed within posts.
Retain Full Detail
CDPs don’t throw away data when they load it, and they retain the full details for as long as marketers want. This lets marketers mine new information from old data by looking at items that weren’t considered important when they were captured. Analysts can therefore find unexpected patterns, and it also means marketing programs can use freshly discovered patterns without waiting to accumulate the underlying data.
Example: Assign customers to a retention campaign when their smart speaker data streams include unplanned events that analysts find are associated with high churn rates.
Personal Identifiers
CDPs work primarily with a company’s own data and are designed with the security and privacy features needed to manage personal identifiers. This lets them safely handle information that is often excluded from systems such as DMPs, which are designed primarily to work with anonymous data shared by others.
Example: Send personalized loan offers to customers based on a combination of account information and data they have provided directly.
Unified Identities
CDPs can associate multiple identifiers with each customer, stitching together a persistent identity that is retained over time. This may include data from multiple channels, such as email address, postal address, phone number, and account ID; relationships between customer identifiers and devices such as mobile phones; and relationships between different devices that belong to the same person.
Example: Build a complete product purchase history by connecting in-store purchases linked to a phone number with online purchases linked to an email address through a master identity record that includes both email and phone information. Add work and business email addresses to this master identity when the customer opens emails to both addresses on the same device.
Attribution
CDPs can apply their unified identities to find relationships between marketing efforts and sales in different channels.
Example: Measure the impact of social media ad campaigns by comparing email audience lists sent to social media publishers with emails captured during in-store and online purchases.
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Audience Selection
CDPs enable more accurate audience selection by providing a complete customer profile as the basis for selection.
Example: Run effective look-alike campaigns in web advertising by building a list of high-profit customers based on combined purchase and return histories across website, mobile app, and in-store channels.
Real-Time Response
CDPs can often process some information in real time, enabling quick reactions to customer behaviors or other events. This can drive new offers or adjust campaigns already under way.
Example: Improve web ad retargeting efficiency by immediately removing customers who have made a relevant purchase from audience lists in a DMP.
Automated Extracts
CDPs have special features to run data preparation processes and reformat data for specific purposes such as predictive modeling or business intelligence. This saves manual data preparation, documents the preparation steps, and ensures consistency.
Example: Provide marketers with an interactive dashboard to analyze campaign results by automatically creating new data tables every evening and feeding them into a business intelligence system.
Advanced Analytics
Many CDPs provide built-in recommendation engines or predictive models. This can substantially reduce the cost, effort, and time needed to generate results and make them available to other systems.
Example: Send the web personalization system a list of the top three products to recommend to each customer based on a machine learning model that is continually updated with offer results.
Customer Profiles
Some CDPs can expose an individual customer profile in real time for review by sales or customer service agents. Without a CDP, the agents would often need to check separately in multiple systems to look up different items separately.
Example: A telephone service agent can view current contract details, usage history, service status, past complaints, installed equipment and scheduled repair calls on a single screen.
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The CDP Advantage: Unified, Shareable Customer Profiles
Varied as they are, these examples all rely on a handful of key CDP capabilities: flexible data ingestion, vast storage capabilities, sophisticated data transformations, a focus on identified individuals, persistent identity management and easy external access.
Other customer data solutions lack one or more of those capabilities: CRM systems handle just limited amounts of rigidly structured data, marketing automation offers limited transformations and external access, DMPs work largely with anonymous profiles. These are not flaws in those systems, whose designs were optimized for other purposes. But they do mean those systems are not well suited to creating unified, sharable customer profiles. That’s what CDPs are designed for and that’s why so many marketers are now using them to solve that part of their customer data challenge.
