STUDY OF THE MODERN "CUSTOMER DATA
PLATFORM"
A customer data platform is a type of packaged software which creates a
persistent, unified customer database that is accessible to other systems. Data
is pulled from multiple sources, cleaned and combined to create a single
customer profile. This structured data is then made available to other
marketing systems. According to Gartner, customer data platforms have evolved
from a variety of mature markets, "including multichannel
campaign management, tag management and data integration." The CDP market is
currently a $300 million industry and projected to reach $1 billion by 2019.
Capabilities In addition, some CDPs provide additional functions such as marketing
performance measurement analytics, predictive modeling, and content marketing
Commonalities across CDPs: marketer-managed;
unified, persistent, single database for customer behavioral, profile and other data,
from any internal or external source; consistent identifier that links all of a
customer's data;
accessible by external systems and structured to support marketers' needs for campaign
management, marketing analyses and business intelligence;
provide a 360-degree view of the customer; group customers into audience segments; and
allow
users the capability to predict the optimum next move with a customer. Data
Collection A main advantage of a CDP is its ability to collect data from a
variety of sources and convert that disparate data into a standardized form.
Some of the data types a standard CDP should work with include: Customer
events: Browsing activity, actions on a website or in an app, clicks on a
banner, etc.
Transactional data: Data
including purchases, returns, data from a POS terminal.
Customer attributes: Age, gender, birthday, date of first purchase, segmentation data,
customer predictions Campaign evaluation data: Impressions, clicks, reach,
engagement, etc. Customer-company history: data from interactions with customer
service, NPS scores, data from chatbots, etc. Marketing automation systems A
CDP is fundamentally different in design and function when compared with
marketing automation systems, though CDPs provide some of the functionality of
marketing systems and customer engagement platforms. CDP tools are designed to
talk to other systems. They retain details from other systems that the
engagement or automation tool does not. This is valuable for trend analysis,
predictive analytics, and recommendations that can leverage historical data.
Marketing campaigns using predictive recommendations are 116% more effective
than those that do not which leads to increased ROI of a CDP.
CDP
vs DMP
A Data Management Platform collects anonymous web and digital data. CDPs collect
data that is tied to an identifiable individual. Users of CDP can leverage the
intelligence to provide more personalized content and delivery. A data
warehouse or data lake collects data, usually from the same source and with the
same structure of information. While this information can be manually synthesized,
neither type of system delivers the identity resolution needed to build a
consolidated single customer view. Data warehouses are often updated at
scheduled intervals whereas CDPs ingest and make available data in real-time.
In practice, most CDPs use the same technologies as data lakes; the difference
is the CDP has built-in features to do additional processing to make the data
usable, while a data lake may not. Main differences between a customer data
platforms vs. data management platforms: It was meant to describe a marketing
software that could build a single customer view.
These databases were originally used to power some other type of software, such as a marketing automation suite, a personalization engine, or a campaign management tool.
The power of the database behind these systems eventually became desirable in its own right. They evolved to become full-fledged software. Simultaneously, some tag management and web analytics providers also transformed their platforms into similar solutions, creating CDPs with a different origin but the same use.
These platforms became successful, and by 2016 they had become the CDP industry. This
industry experienced quick growth, due to marketers recognizing the
shortcomings of alternatives like DMPs and data lakes, as well as the
capabilities a CDP could offer them.
References
Bibliography:
Wikipedia @baygross
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