Customer Data Platform
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A customer data platform (CDP) is a collection of 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."


Capabilities

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 Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical p ...
; * 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. In addition, some CDPs provide additional functions such as marketing performance measurement analytics,
predictive modeling Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive mod ...
, and
content marketing Content marketing is a form of marketing focused on creating, publishing, and distributing content for a targeted audience online. It is often used by businesses in order to achieve the following goals: attract attention and generate leads, exp ...
.


Data collection

A main advantage of a CDP is its ability to collect data from a variety of sources (both online and offline, with a variety of formats and structures) 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 The point of sale (POS) or point of purchase (POP) is the time and place at which a retail transaction is completed. At the point of sale, the merchant calculates the amount owed by the customer, indicates that amount, may prepare an invoice f ...
. * 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
chatbot A chatbot or chatterbot is a software application used to conduct an on-line chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent. Designed to convincingly simulate the way a human would behav ...
s, social media posts, survey verbatims, focus group transcripts, call centre audio files etc.


Marketing automation systems

A CDP is fundamentally different in design and function when compared with
marketing automation Marketing automation refers to software platforms and technologies designed for marketing departments and organizations to more effectively market on multiple channels online (such as email, social media, websites, etc.) and automate repetitiv ...
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 Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In busine ...
, and recommendations that can leverage historical data.


CDP vs DMP

A data management platform (DMP) 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 DMP enables marketers to serve targeted ads programmatically and at scale using anonymized customer data in the form of third-party browser cookies. A
data warehouse In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integra ...
or
data lake A data lake is a system or repository of data stored in its natural/raw format, usually object blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc., and transform ...
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 A single customer view is an aggregated, consistent and holistic representation of the data held by an organisation about its customers that can be viewed in one place, such as a single page. The advantage to an organisation of attaining this unifi ...
. 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 (CDP) vs. data management platforms (DMP):


History of the CDP industry

Although similar tools existed in the past, the term Customer Data Platform was first used in 2010. It was meant to describe a marketing software that could build a single customer view (a collection of all of a customer's data and events into one file). These databases were originally used to power some other type of software, such as a
marketing automation Marketing automation refers to software platforms and technologies designed for marketing departments and organizations to more effectively market on multiple channels online (such as email, social media, websites, etc.) and automate repetitiv ...
suite, a personalization engine, or a campaign management tool. At this time, most customer databases were specially designed to support a vendor’s individual software application. Because of this, customer databases could not easily interconnect or interoperate with other layers of the technology stack. Data could not easily be moved from one place to another, so it could be leveraged to improve business performance. Because of these limitations, many vendors made the decision to begin adding more advanced integration tools (APIs) to their customer databases and converting them into what we now know as Customer Data Platforms (CDPs). 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 Web analytics is the measurement, collection, analysis, and reporting of web data to understand and optimize web usage. Web analytics is not just a process for measuring web traffic but can be used as a tool for business and market research and ...
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. The CDP Institute estimates industry revenue at $1.9 billion for 2022, up 19 percent from $1.6 billion in 2021.


References

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