What is the purpose of a CDP?
Our customers are becoming more and more demanding and expect the same approach and treatment regardless of the channel, be it phone, web or social media. The purpose of the CDP is to bring all customer information together in one place to create a consistent customer picture and to solve the problems caused by data silos. Data silos are created as we start to have many different systems containing different information about our customers, each providing its own, often limited, picture of our customers. Different information in different systems can lead to customers suffering through disjointed customer experience and complicated customer journey when they interact with a company.
So a CDP, or customer data platform, is a system for managing information about real customers of a company with the aim of creating a centralized place where all data about its customers is stored to get a complete and unified customer picture. A CDP therefore collects data from the company's various systems and databases that contain customer data such as CRM, ERP, websites, webshops, apps or transaction systems. This is then used to analyze and get to know their different customer groups with the aim of creating relevant and coherent experiences, services, communications, offers and campaigns.
CDP and Data Management
Customer data can range from anonymous ad exposures and known purchases to product usage and customer service contacts. There are three main types of customer data:
Demographic data: Socio-economic information such as age, nationality, income, education, interests and employment.
Behavioral data: Created through a customer's digital interactions with a company. This type of data tracks which websites are visited, which apps are downloaded and which games are played, as well as the number, duration and intensity of interactions.
Transactional data: Documents an exchange, agreement or transfer that takes place between organizations and/or individuals. Usually has commercial or legal significance and can include transactions such as purchases, returns, payments, registrations, reservations and subscriptions.
Device data: Does the customer use one or more devices, if so, which ones? Which devices are preferred for different activities or times.
Most commonly, a CDP is used to manage first-party data and stores personally identifiable information such as name, email, postal address and contact number, much like a CRM. The difference with a CRM is that a CDP is built to handle more different types of first-party data collected from customers. This can be information about how they interacted with the company in different 'channels' such as the website, services or apps. It can also be generated from newsletter subscriptions (Marketing automation systems) or purchase transaction systems made through the company's website (CMS, ERP) or Point of Sale (POS) systems in stores.
A customer profile can be enriched with information from other sources to create a more coherent customer picture. Examples of such data are financial data from credit institutions, purchased data (i.e. second-party data) as well as third-party data obtained from a collection of different, sometimes unknown, sources can in many cases also be managed in a CDP. Usually you want to separate first, second and third party data because of the large differences in quality.
CDP and data security
There are arguments related to data security for using a CDP, where a CDP can (at least in theory) serve as the only strongly encrypted database in a company where personal information is stored about customers. Other systems that are integrated with the CDP then only store the reference ID in their database. This makes it easier for a company to keep track of and secure the management of its personal data. With careful authorization management, access control and activity logging, there is traceability for who or who has access to and uses the data. A CDP can thus simplify the control and management of personal data, consents and regulatory compliance, such as GDPR compliance.
Segmentation and analysis
A CDP collects a lot of data that is valuable to analyze as the data is based on a specific individual and so-called customer identifier, such as an email address or a social security number.
In a CDP, the idea is to be able to analyze different behaviors such as of all those who bought product Y, what peripheral products or services did they buy? can we find a pattern? Another example is to analyze the likelihood of a web visitor converting into a customer or learn to understand content affinity (i.e. relatedness between different content) based on the customer's interest in visiting articles and searching for specific products. The knowledge can be used to create better customer experiences with smart product or content recommendations, smarter website navigation and clearer information.
CDP and Marketing Automation
Using technologies such as Marketing Automation, AI and predictive analytics, it is possible to not only identify which sales or communication channel a particular individual prefers, but also to personalize the customer experience and communication with the individual customer. An example is sending the next order confirmation via SMS instead of email for those individuals who prefer it. Or perhaps have a profile and behavior that is consistent with others who prefer the SMS channel for order confirmations.
Another example could be to use the data to individually control when the newsletter is sent. For example, to 8 pm on Sundays for the particular individual who most often opens and reads the newsletter at that time. And 10 am on Tuesdays for another. In addition, each newsletter can contain information, inspiration and offers customized for that specific individual, so no two newsletters sent need to be the same. The reason companies and marketers want to do this is to be as relevant as possible. In other words, only communicate what the customer is actually interested in, i.e. on the customer's terms.
A CDP can integrate online and offline data and uses customer analytics and machine learning to provide a Marketing Automation system with insights and thus the ability to create individualized communication in a variety of channels such as email, SMS, in app, on page, social media, ad networks or personalized print.
8 good reasons to use a CDP:
It can:
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act as a central hub for customer data.
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break down data silos to deliver a unified customer view.
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deliver an encrypted storage of personal data with a focus on security.
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integrate with different systems such as Marketing Automation systems. Also advertising systems such as Facebook and Google to enable customized personalized communication and advertising.
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capture data anywhere in the customer cycle from a variety of systems.
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identify customer traits and behaviours that can be used for personalized communications and individual customer experiences.
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store contextual, demographic as well as historical data.
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As well as being used for customer analytics and source for predictive models and analytics.
Some examples of CDP systems:
CDP is still relatively new and is predicted to be "the next big thing". This is clearly evident from the number of solutions on the market, as more and more Customer Data Platform systems are being launched and major resources are being invested in developing the technology. In principle, the major players have all recently launched or announced that they will soon launch CDP solutions. Here is a list of some different examples of CDPs.
