Marketing 0

Step 3: Build an Integrated Data Ecosystem
Most data-driven marketing initiatives begin as ad-hoc, agile
projects. In the long run, however, data-driven marketing must be a
routine operation. To make sure the data collection effort gets
maintained and continuously updated, companies must build a data
ecosystem that integrates all the external and internal data.
The biggest challenge for data integration is to find a common
denominator across all data sources. The most ideal is to integrate
the data at the individual customer level, allowing for the segments-
of-one marketing. Good recordkeeping practices ensure that every
captured dataset about the customer is always tied to unique
customer IDs.
While it is straightforward for internal data sources, using customer
IDs for external data is a challenging, albeit doable, exercise. For
instance, social data can be integrated with the customer ID and
purchase data if the customer logs into e-commerce websites using
their social media accounts, such as Google or Facebook. Another
example of data integration is using a customer loyalty app to
connect to smart beacon sensors. Whenever a customer carrying his
mobile phone is near a sensor, for instance, in a retail aisle, the
sensor records the movement. It is useful to track the customer
journey in physical locations.
However, sometimes it is not possible to tie everything to an
individual customer ID, primarily due to privacy concerns. A
compromise solution is to use a specific demographic segmentation
variable as the common denominator. For example, the “18-to-34-
year-old male customer” segment name can be the unique ID to
consolidate every information item from every data source about the