When selecting a customer data platform (CDP) the first thing to know is that not all platforms are the same. In fact, many of the vendors claiming to be CDPs are approaching the category with only a fraction of the necessary capabilities. Most CDPs are straddling multiple market categories (e.g., CDPs rooted in tag management, CDPs rooted in web personalization, etc.), and their bias toward these external categories inherently limits their CDP feature set. You can’t serve two masters.
What features should be included in every CDP? For enterprise omnichannel B2C marketers, six capabilities that must be present for a CDP to be fully effective. These marketers should thoroughly examine how exactly CDP vendors provide the following capabilities:
1. Data Quality and Identity Resolution
A CDP should offer comprehensive data cleansing, deduping, standardizing and enhancing of omnichannel customer data profiles. The profiles should be updated continuously and should be accessible for every type of customer campaign and engagement. Some CDPs do not offer any data quality features, and others have only very limited data quality capabilities. When choosing a CDP, marketers should insist on only the highest standards of data quality and identity resolution.
2. Complete Inclusiveness of Online and Offline Data
For omnichannel B2C brands, customer data spans several digital and physical channels. For example, in-store workshops, community events, call center experiences, in-store browsing or purchasing, as well as digital engagement across the website, email, mobile, and social channels—all contribute to a customer’s identity, and all of these experiences and more should be encompassed by a CDP. But some CDPs specialize in digital-only data, or they give lip service to physical channels but are limited to just some aspects of physical-driven data, such as POS transactions or call center logs. A true CDP should be able to integrate all, literally ALL, customer data sources into a clean system of record with a single customer profile that can be used for actionable marketing and engagement. See our case study on how athletic apparel retailer, lululemon, does this.
3. Machine Learning and Predictive Models
Integrating customer data is one thing, but making customer data actionable and intelligently enabling engagement is another. A CDP should be a configurable intelligence layer that marketers can apply across their engagement ecosystems. Some CDPs do not add any intelligence to their integrated customer data, or offer only crude segment calculations or rules to inform customer engagement. An enterprise CDP should include advanced machine learning to power genuine 1:1 relationships with greater lifetime value – as demonstrated by fashion retailer Lilly Pulitzer in their approach to marketing to millennials.
4. Robust Reporting
Marketers should be able to drill into customer data both at the single profile level and in aggregate across all customers and segments. An enterprise CDP needs to provide customer data reporting and analysis so marketers can understand customer patterns, behaviors, and how to most effectively create segments for campaigns. But many CDPs offer very limited or no reporting and analytics, making it difficult for data-driven marketers to understand how to most effectively reach and engage their audiences. Marketers should choose a CDP with comprehensive built-in reporting and customer analytics.