Customer Data & Analytics Blog

Data Myopathy: How to Avoid Undercutting Yourself

David Slavich | 2 minute read

Form fills, sales created contacts and accounts, event lists, D&B, and Zoominfo. There are a lot of data sources out there and much like a periscope, those sources provide a myopic glimpse of a rapidly expanding data universe (data grows 2.5 quintillion bytes a day). Why myopic? In my last article where I discussed the cost of Data Decay, I wrote about the nature of data being akin to a snapshot in time but what if that snapshot was never complete, to begin with?

Topics: Data Quality

Breaking Bad Data - The Key to Data Accuracy

David Slavich | 2 minute read

When was the last time you updated your LinkedIn profile picture? At least for myself, it’s been a while and considering the “quarantine 15” phenomenon I have no plans to change my picture anytime soon. Ironically, I relied on the accuracy of LinkedIn profile photos for finding prospects at conferences when I was an SDR and due to data decay, I often found myself at the panting end of an apology after running down the wrong prospect. 

Topics: Data Quality

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

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

Nuances of Data Enrichment

Sandeep Koul | 3 minute read

We all agree about data decay in CRM, even with a conservative rate of 22% (based on average US company employee turnover rate) you might end up losing lot of marketing dollars not only as direct cost of managing dirty data but also as an opportunity cost of not reaching to potential customers.

Topics: Data Quality