Customer Data & Analytics Blog

6 Reasons Why Data-Driven Marketers Need a CDP

Chuck Leddy | 3 minute read

This post answers six questions B2B marketers often ask us about how an automated CDP can make their lives easier and their marketing efforts better.

Topics: Marketing Technology CDP Data Operations

Why you should care about RevOps

Pat O'Brien | 3 minute read

 

RevOps is a hot topic. With an “81% increase in RevOps titles on LinkedIn alone, RevOps is not just a buzzword but something companies are actively investing in and will continue to grow. But where organizationally does it fit? Is it just an extension of sales ops or marketing ops? Can those organizations morph into this role? This blog will explore what RevOps is, why companies should care, and explore whether the true definition of RevOps can be implemented successful.

Topics: Revenue Operations

The Shocking Cost of Data Decay - How Bad Data Causes Loss

Sandeep Koul | 3 minute read

One universal fact about data is that, like many perishable things in the world, it goes bad over time (unfortunately pretty quickly). 

Topics: Data Quality

How AI, ML and CDPs can impact sales operations

Chuck Leddy | 3 minute read

 

An earlier Zylotech blog post described the multiple benefits customer data platforms offer technology companies, benefits that go way beyond “just” the marketing function. With the close ties today between sales and marketing on everything from ABM to intent, this post will explore why so many companies are now choosing CDPs in the noisy tech-laden sales and marketing landscape, what CDPs offer them, and how they’re implementing CDPs for three important, sales and marketing-related purposes: Account Based Marketing (ABM), ID resolution, and even privacy compliance mandates like GDPR (your security team will be happy).

Topics: machine learning

Every marketer’s dream: Clean, segmented data—How can you get there?

Abhi Yadav | 2 minute read

Great data is the basis for great marketing

Data scientists are intimately familiar with the processes data must go through before it can be used for machine learning models and analytics. Marketers, on the other hand, are usually not. The journey that customer data takes before it’s actually useful is outside of many marketers’ purview and deemed unimportant to some.

Topics: Data Quality