A Customer Data Platform is a software that uses data from multiple tools to create a single central customer database that contains data on all touchpoints and interactions with your products or service. You can then segment this database in a nearly endless number of ways to create more personalized marketing campaigns.
Customer data platforms create customer profiles by integrating data from a range of sources. These sources can be your CRM (Customer Relationship Management) and DMP (Data Management Platform), transactional systems, online fill-in forms, email and social media activity, website and eCommerce behavior data and more.
This makes CDPs essential for people-based marketing, as it helps organizations put the customer at the center of marketing efforts.
#The purpose of CDPs
With so much customer data floating through the digital space, how can you be sure which data is accurate? The solution – gather first-party data directly from your customers, visitors, social media followers, and subscribers. This is the best type of data you can collect to make intelligent marketing decisions because it comes straight from your audience.
CDP solutions primarily focus on collecting first-party data through pixels and other tracking tools. This way, you can rest assured that our CDP reflects the most accurate customer information you can get.
While collecting data, it’s essential to define data lineage and usage policies. This is why a CDP should be able to classify, protect, and control data that is being integrated. CDPs achieve this by profiling, segmentation, and cleansing operations on the incoming data in three steps:
Flagging restricted data using data labels: This allows organizations to stay compliant with data regulations and policies. The infrastructure automatically flags different types of data info labels:
- Restricted label – Personal and identifiable information such as name, physical address, web address, etc.
- Contract label – Data related to other contractual obligations that restrict its usage.
- Sensitive label – Data related to naturally sensitive information.
Configuring usage restrictions for the labeled data: When data is flagged and labeled, the software creates conditions for the use of that data. This allows operations to run smoothly, consistently, and in real-time conditions.
Simplifying data policy management: Since data governance rules and regulations change, each label is defined so it can be dynamically changed.
Enforcing data compliance: Once usage policies are defined on labeled data, each piece of data is treated the way it is defined in terms of data usage and data sharing during integration with third-party tools.
Validating and transforming the data and its consolidation
In automated systems such as CDPs, customer data is collected with minimal or no human supervision. This is why it’s necessary to ensure that the data that enters the system is correct and meets the wanted quality standards.
Even if entered correctly, unstructured data may cause additional costs for cleansing, transforming, and storage. There are many types of data validation, including
- Data type check – Confirms that the customer data entered has the correct data type. For example, if a field accepts only numerical data, any data containing other characters are rejected by the system.
- Code check – Ensures that a field is selected from a valid list of values or follows pre-set formatting rules. For example, verify a ZIP code by checking it against a list of valid codes.
- Range check – Verifies whether input data falls within a predefined range.
- Format check – If data must follow a predefined format, this procedure ensures data types such as dates are consistent across collected customer data.
- Consistency check – Checks if the data’s been entered in a logically consistent way. For example, the delivery date is entered after the shipping date.
- Uniqueness check – Makes sure that a unique item is entered only once in the database. Unique examples of data include IDs and email addresses.
CDPs also eliminate data silos by transforming fragmented collections of names, email addresses, and purchase history into valuable, actionable data that updates in real-time. This helps eliminate duplicate profiles that impact relevancy and analytics, enabling a CDP to create a 360-degree customer view.
Another function of a CDP is to consolidate customer data. Consolidation is the first type of data integration. It includes pulling data from a number of remote sources, unifying it, and storing it in a central database. Consolidation allows you to reduce the number of places where your data is stored. As a result, consolidated data is easily accessible for analysis.
CDP tools allow you to segment your audience down to smaller, more personalized groupings. Using a single CDP solution, you don’t have to rely on multiple tools, documents, and processes. Instead, you get the speed and flexibility to adjust your segmentation parameters to get the right sample and distribution.
For example, you can test different groups against each other, with the entire process being contained within one framework that draws directly in front of our customer data.
You can also test who will convert most quickly, who converts most reliably, etc. Such tests can significantly impact your revenue, loyalty, and lifetime value.
The fifth purpose of a CDP builds on the previous four. Once you have permission to collect your first-party user data, and it’s segmented into user profiles, you can take action on it.
Your CDP can highlight a number of features, like creating audience segments, that you can use to activate your user data across the rest of your marketing platforms and channels.
For example, it allows you to pull a list of e-commerce customers and create a new email campaign to reward them with a one-time 25% off coupon.
Or you can create audiences based on content preferences and send them to an ad network for advertisers to target for a more personalized ad experience.
#Overlaps with Digital Management Platforms (DMP)
CDPs operate with both anonymous and known individuals, as they store personally identifiable information (PII), such as names, postal addresses, email addresses, and phone numbers. Digital Management Platforms (DMPs) operate almost exclusively with anonymous entities, like cookies, devices, and IP addresses.
In other words, DMPs focus primarily on third-party data for business analytics, while CDPs make use of all data sources, including first-party data, to provide a singular customer view.
CDPs focus on all marketing aspects, while DMPs are designed to help advertisers and agencies optimize ad targeting.
So to sum up:
|Use Case:||Whole customer relationship management||Specific to advertising, better ad targeting, improves media buying|
|Data Types:||First-party data with little third-party data||Third-party data with little anonymized first-party data|
|Profile Identifier:||Personally identifiable information (PII) such as customer ID, name, email, address, etc.||Anonymous digital identifiers, cookie ID, the identifier for advertisers (IDFA), etc.|
|Data Retention:||Long retention periods to allow analytics over customer lifetime||Short retention periods needed for ad targeting|
#Benefits of using a CDP in your business.
Unified data in one place.
Omnichannel marketing is a great way to connect clients wherever they are. As the number of channels grows, it becomes increasingly difficult to maintain consistent customer data across all touchpoints. Omnichannel, however, works both ways – companies want to meet customers at every touchpoint, but then have difficulty in keeping those customer experiences consistent.
360-degree view of the customer.
In the age before CDPs, marketing teams had minimal overlap in platforms they spent most of their time. The only exception might have been a project management platform. Still, a 360-degree customer view used to be nothing but a dream.
Marketers could get a peek into ongoing campaigns and projects only at weekly stand-ups and brief meetings.
On the other hand, when businesses use a CDP, their marketing stack can become a marketing ecosystem with straightforward visibility and collaboration between separate marketing functions.
Marketing tools tend to silo team members from each other’s workflows. A CDP breaks those silos and creates a 360-degree customer view like no other marketing tool today.
Identifying new audience segments
A CDP helps marketing teams identify new audience segments in three stages:
Capturing intent attributes: Data is integrated from multiple sources including websites, POS, mobile apps, CRMs, eCommerce, purchase platforms, ad networks, lead capture forms and more.
These attributes are then specified by their characteristics, such as personal information, location, demographics, buying behavior, purchase patterns, etc.
CDP analytics: When the CDP collects data sources, the system performs various analysis types to respond to different queries. The CDP can create a particular audience of individual customers allowing for hyper-personalized and one-to-one marketing outreaches.
For example, a CDP will react in real-time by understanding the relevant intent signals on a website – such as when a particular audience segment views specific pages and engages with content.
Execution: Once the CDP identifies a customized profile, it can initiate several workflows, such as
- Real-time CRM update – Each time a new account qualifies, the audience is updated
- Campaign automation – The system feeds the data to several tools in the CRM stack to create real-time outbound messaging like personalized emails, discounts, texts, etc.
- Website/Mobile app personalization – The customer can have a personalized experience every time they visit the website or mobile app, which leads to a targeted connection.
Campaign optimization and knowledge gained from historical data
A CDP allows teams to automate the manual process of creating advertising audience clusters. Your team can use this data to drive promotions and campaigns across multiple touchpoints. CDPs enable highly targeted personalized advertising campaigns, as they can be integrated with Facebook pixels and Google Ads.
With CDP out of the equation, creating these campaigns for complex audiences would take a lot more time and effort. The CDP allows you to access clusters of customers and indicate what product they’re interested in.
Data governance and compliance
Customer Data Platforms bring data from multiple business systems together, enabling marketers to better identify, understand, and engage their customers. The problem is that his data may be subject to usage restrictions – either defined by your organization or legal regulations.
A CDP allows you to manage customer data and make sure it’s compliant with regulations, restrictions, and policies that apply to data use. On the other hand, it allows you to define sage policies, categorize your data based on those policies, and even check for policy violations when making certain marketing decisions.
#Evaluating CDPs - how to choose one that fits your needs
Integrations for the data sources
You need a CDP that will fit right into your tech stack and be able to pull the data from the remote sources that you currently use. Hygraph, for instance, allows you to pull data from any GraphQL or REST API.
Knowing your needs
You need to understand your use case in order to determine what type of platform you need. For example, do you need a CDP that does all the steps that CDPs usually do, or perhaps you just need a segment of its functionalities, such as pulling the data from other APIs and consolidating it into one platform?
The customer data your CDP ingots is subject to privacy constraints, so you need a system that can provide conclusive evidence of where the data came from originally, how it has been used since, what type of data is stored, and how it has been changed, and how it has been used for marketing. Some CDPs go one step further, offering a user interface (UI) that allows users to directly process and manipulate data held in the CDP.
A CDP really allows you to put the customer at the center of your marketing efforts. It allows you to combine raw, real-time customer data and deliver the immediacy, accuracy, and unity that every marketing team needs to streamline their operations and engage their customers.