How to Choose a B2B Customer Data Platform: Better Data Integration Means Better Decisions

January 31, 2022

Complete buyer profiles at the account, buying center and contact level are critical. This starts with leveraging your ongoing 1st party data with a variety of 3rd party data to create profiles (or a full buyer data graph) — combining what you know about the customer with what the world knows about the customer — for better lead to account matching, classification/scoring, context and insights. And buying signals come from all kinds of systems with data that can be in many different formats. 

Integrating & unifying numerous types of variably-sourced data on your own is extremely tedious, time-consuming, and error-prone. Luckily for marketing and sales operations professionals, implementing a Customer Data Platform (CDP) turns that cumbersome process into the first of many automated steps in your buyer’s journey.

Of course all CDPs are not the same. So, you need a way to determine which best fits your needs. Check out the latest from Forrester, who recently published The Forrester New Wave™: B2B Standalone CDPs, Q4, 2021.

In Forrester’s evaluation of 14 leading B2B CDP companies, they consider several areas of capability to determine and compare the platform’s individual data integration and unification qualifications. Forrester takes into account integration capabilities (deduping, cleansing, normalization, lead-to-account matching, etc), integration processes (workflow visualization, data ingestion, frequency, customization, etc), and supported data sources/types (1st and 3rd party integration, CRM, marketing automation, structured/unstructured, data sources/providers, firmographics, technographics, intent, etc). While Data Integration & Unification is just one of 10 variables Forrester uses to rank B2B CDPs, let’s look at how a comprehensive process for that should work. 

First of all, platforms should be able to cluster, unify, link, and dedupe company & person identities originating from any data source. Using primarily proprietary AI-based classifiers, they can unify a record while maintaining data integrity and custom business rules including validation and normalization. Modern platforms also offer real-time, on-demand, and scheduled sync of unified profiles for data management objectives. Finally, profiles can be synced to any activation channel.

An important question to ask is – whether the platform is data agnostic and ingests both structured and unstructured 1st and 3rd party data in the backend as well as through a self-service UI. It’s also important to discern if integrations are supported via native apps, REST API, and SFTP. And sometimes unification is very unique, check to see if the unification logic is customizable via the UI or customer service requests.

Basic capabilities to look for include the typical first-party sources including CRM, ERP, web analytics, MAP, product usage, and CSX data. There are dozens of high-quality third-party sources that provide firmographics, demographics, technographic, and intent data. Can the platform support custom sources? Also understand what is possible with respect to scheduling for ongoing data health.  Does the platform offer both real-time, scheduled and on-demand ingestion, unification and segmentation workflows for data management? Then evaluate whether the segments and profiles are persisted and can be synced to any channel for activation.

Lead to account matching is sometimes an overlooked capability in CDPs. Depending upon the volume, the complexity of routing and the response time required in your GTM system, small errors can mean a lot of distraction or lost deals by your reps. After working with lots of large B2B accounts, we’ve found that not all profiles require the same number of sources for complete profiles used in matching, routing and scoring. For account profiles, we’ve found that 80% of records have between three and eight data sources. And for people or contacts, nearly 95% of records have 8-10 data sources. So, it’s important to consider the ability to normalize all of that data into a coherent profile. Platforms that support multi source matching do just this.

One of the most unique capabilities of a Customer Data Platform is the ability to take data and integrate it into a Buyer Data Graph. This creates a customer-specific B2B Graph with multi-source validation — tens of millions of companies, hundreds of millions of Buying Centers, hundreds of millions of people from dozens of curated third-party data sources and a broad array of first party data. This is one of the most unique capabilities that differentiates a great B2B CDPs from an average one.

To learn more about the benefits of implementing a CDP, and to see how companies compare to other B2B CDPs in all 10 evaluated categories, download The Forrester New Wave™: B2B Standalone CDPs, Q4, 2021.