Today’s podcast is a shorter version of an article I wrote for Martech.org, which I’ll link below.
Martech.org defines a CDP as follows.
“Customer data platforms (CDP) are marketer-managed systems designed to collect customer data from all sources, normalize it and build unique, unified profiles of each individual customer. The result is a persistent, unified customer database that shares data with other marketing technology systems.”
That’s a good definition, but it leaves a lot unsaid. There are different types of CDPs, and they can be used to implement very different marketing and operational strategies. This review of 10 CDP types will help you fine-tune your CDP strategy and evaluate prospective vendors.
Think of the question the way a connoisseur might approach a wine. You have to know what to look for – in aroma, flavor, structure and texture, finish, balance, color – to distinguish one wine from another.
10 Types of CDPs
My 10 types don’t cover every possible distinction, such as …
- composable vs. packaged,
- pure play vs. suite, or
- enterprise vs. small and medium businesses
But these 10 types can help you better understand the landscape.
Data Collection
Primarily focuses on aggregating data from multiple and varied sources. Such CDPs will have lots of proven integrations, and will focus on real-time data management. A data collection CDP will likely prefer deterministic over probabilistic matching. It’s ideal for businesses that need to create a reliable single customer record using data from websites, CRM, mobile apps, offline data sources, and third-party systems.
Data Cleansing
Focuses on cleaning, deduplicating, validating, and normalizing data to ensure accuracy and usability. It’s suitable for companies dealing with large volumes of data from diverse sources that need to ensure data quality, such as financial services and banking.
Analytical
Creates deep, actionable insights through analytics and data visualization, often incorporating machine learning for predictive analytics. This is good for organizations that need to derive complex insights and forecasts from their customer data.
Campaign
Manages and automates marketing campaigns and customer journeys across various channels through the use of internal marketing tools and/or through integrations with external tools. This can create a single system from which to orchestrate and coordinate marketing campaigns across multiple platforms and touch points based on a comprehensive view of the customer.
Segmentation
Segments customer data into meaningful groups – based on demographics, behavior, purchase history, and preferences. This can be used to categorize customers into well-defined segments to create more targeted engagements – for content, marketing, customer service, or product development.
Content
Aligns customer data insights with content management capabilities, focusing on creating a deeper content engagement with customers based on personalization and behavioral data. It delivers highly personalized content to individual customers based on their demographics, behaviors, preferences, and other data. The goal is to increase engagement with brand content and improve customer experience.
Retail
Integrates data from online and offline interactions to create a unified, real-time customer profile. This approach consolidates data across e-commerce platforms, brick-and-mortar stores, mobile apps, and social media to understand customer behaviors, increase sales, and create a better customer experience.
B2B
Handles the complex business structures and longer sales cycles for B2B efforts. It consolidates and manages data from various systems, such as CRM, email interactions, social media, and direct marketing campaigns to create a unified view of each business account and the stakeholders therein.
Customer Service
Leverages customer data to provide more efficient, personalized, and proactive customer service. It aggregates all customer interactions – from support calls, chatbot conversations, email exchanges, social media interactions, etc. – to enable customer support teams to offer personalized and accurate customer service.
Real-time
Integrates and acts upon new customer data in real time to power immediate marketing activations. It personalizes the customer experience, advertising, and marketing campaigns in real time on web, app, or customer service platforms.
Conclusion
The point of these “10 types” is not to pigeon-hole any given CDP, but to give the marketer a broad understanding of the different features and emphases CDPs might bring to the table. Reviewing these 10 types can also help the marketer think creatively about how a CDP can bring value to the business.
Links
There are 10 types of CDP. Here’s why that matters
If you’re curious about customer data platforms, please have a look at my e-book: What is a Customer Data Platform? And why should I care?
