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Fivetran Webinar: What’s a Customer Data Platform?

Posted December 29, 2020
powered by fivetran

The New Edge for Customer Data Platforms Automated Data Integration


Recently, our CEO (Eric Westerkamp) was invited to present during a Fivetran webinar. During this presentation, he covered what a customer data platform does and does not do, what is unique about CaliberMind, and what people should consider before building their own customer data platform.


What is a Customer Data Platform?

A customer data platform (CDP) is defined as a customer database with consistent, unified information accessible by multiple platforms. A customer data platform should act as the single source of truth for your account and contact information and house any recorded interactions, linking them to the appropriate account and/or contact. 


The core objectives people try to achieve with a CDP fall into one of three categories:


  1. Data: “I want cleaner information so my reports are accurate. I want my leads matched to accounts. I don’t want any duplicates.”
  2. Orchestration: “I’d like my CDP to house some complex routing or notification rules. I want my prospects to be segmented according to multiple factors.”
  3. Analytics: “I want to see how many interactions are needed before a sale. I want to know which campaigns work best. I want to understand what actions people take before purchasing.”


A CDP should integrate with any systems that house key information or applications you would like to use to visualize the data. A CDP should also be able to pipe data back into any source system once it’s manipulated.


Because CRMs, MAPs, and other business systems have API call and processing limits, it’s not a good idea to collect all of your data in a CRM or MAP and then try to run processes to clean the data. If you were to add a record for every website interaction that takes place over three months, you would inevitably see many system errors or warnings.


A CDP is a processing powerhouse, able to manipulate giant sets of data. This makes a CDP the ideal place to house extensive digital interaction data and run algorithms needed to match leads to accounts, normalize data, and deduplicate.


B2B vs. B2C: Different Worldviews

We’ve seen that B2C companies are further along in terms of adopting customer data platforms. The data is a little less complicated, making the results a little easier to understand. The applications B2B and B2C companies use are also very different.



B2B companies typically deal with a buyer committee at a single account. Multiple people are actively researching product options, have different requirements, and want to consume different content. A single website may offer content catered to the CFO, IT, and marketing representatives to cover their typical buyer committee members’ needs.



Consumer sales can involve many steps, particularly with luxury item purchases. A consumer may bounce around different websites doing research and then interact with several ads before deciding on a product. It’s rarer that they bounce around different funnel stages.



However, there are plenty of lower-cost items that are relatively linear. A consumer enters “socks” into an eCommerce store’s search and may either buy the brand they searched for or select a different brand with a similar design from one of the sponsored ads at the top of the page. One or two clicks and the purchase is complete.



The purpose of a B2C CDP is to understand which advertising tactics and content are producing the most sales. An example of B2B use cases include:


  • “My customers interact with dozens of campaigns before a sale. I need to understand how much each of these campaigns progressed the deal.”
  • “An average sale has 52 logged interactions. One-third to half are logged by marketing, and we need to show how much each department is contributing.”
  • “We want to spend less time trying to merge data in Excel files.”
  • “I need to track marketing attribution against expansion and renewal sales.”


How Is CaliberMind Different?

CaliberMind was created to help marketers grow pipeline faster through actionable insights. We focus on integrating sales and marketing tools and then unifying the data. Then we translate this information into actionable insights using algorithms powered by machine learning.


In short:



We take data from your systems of record, website, and elsewhere and translate it into campaign attribution, engagement scoring, campaign effectiveness, return on investment, and more. We segment data and run workflows to assign team members or notify people of key events. We also pipe information back out to allow customers to keep their systems of record clean and visualize their data, although we also provide a customizable report builder.


It’s a lot! But that’s what a customer data platform is all about. Data, orchestration, and analytics. We’re different because we do this for B2B companies, looking at the data through both the account and individual contact lenses.


Things to Think About Before Building Your Own

There are a lot of steps involved in building your customer data platform. There will also be a lot of people involved. When it comes to shared systems, unilateral decisions can lead to significant problems.


You must get cross-functional sign-off on your data definitions and systems of record. You’ll also need to consult with people about what kind of data clean-up/manipulation is allowed. Of course, you’ll also need to ensure you have access to the resources necessary to build complex data models, integrate applications, and manipulate data in source systems.


As a B2B organization, you’ll need to plan for:


  • Integrating a minimum of eight systems with your data hub
  • Implementing a solution to enable detailed tracking on your website
  • Working with IT to determine which data warehouses or data lake providers are allowed
  • Ensuring your team either has the resources equipped to manage integrations and your data warehouse/data lake or that IT can dedicate resources
  • Assign a project manager to obtain sign off on data definitions, workflow rules (deduplication, data matching, normalization, etc.), data models (attribution, engagement scoring, segmentation, spend analysis, etc.), and processes for updating associated reports (writing “clean” information back to systems of record”)
  • Pencil in time to calculate the amount of time it will take to add the necessary tables each time marketing or sales adds an application
  • Determine which tool you will visualize the data in and whether or not you have access to resources that can manage reports and dashboards


Your project team should include revenue operations (or sales operations and marketing operations), as well as IT and BI. From project kickoff, you’re probably looking at nine to twelve months to go live.


Or you could go with a customer data platform provider and shave a minimum of six months off your implementation time frame.


For more information on building your CDP, check out our guide.