The best cross-channel marketers have data in their DNA. They understand which levers to pull in order to optimize spending and maximize returns. But in all the mechanics, a marketer’s relationship with the customer can easily get lost. So how to avoid this? Let's explore how enterprise marketers are overcoming this challenge by:
- Understanding how marketers got into this mess in the first place.
- Evaluating the current “customer data platform” trend.
- Looking at successful strategies from an enterprise retailer.
How We Got Here
If you’re old enough to remember the pre-digital era, you probably also remember its simplicity. It was a time when interactions were in person – for example, someone working in a corner store could truly know each customer because they literally knew each customer. By knowing each customer, store clerks could easily ask the right questions, offer the right products, and provide the right experience for each individual.
But the digital age complicated this dynamic. More channels offer more opportunities for interaction, but they also offer more opportunities to fail at delivering a good customer experience. And faced with overwhelming amounts of data that all too often lives in silos, marketers until now have limited their efforts to a more manageable scope of marketing within those silos. But today’s sophisticated marketers are seeking, and finding, methods that bring them closer to applying the pre-digital idea of 1:1 marketing across a multi-channel marketing ecosystem.
Rise of the Customer Data Platform
The recent rise of the customer data platform illustrates how urgent this challenge is for marketers today. Customer data platforms (CDPs) are different from other data solutions in that CDPs are manageable by marketers (not IT), CDPs give a unified, persistent database for all first-party data and CDPs are fully accessible by external systems.
But not all CDPs are created equal. According to the Customer Data Platform Institute, only a CDP that also provides the following capabilities will meet the needs of an enterprise cross-channel brand:
- Data quality and identity management
- Online and offline data integration
- Analytics and machine learning
- Data actionability