Article

Data Decay: What, Why and How?

People and companies change every day. Companies make acquisitions, people change jobs, and intentions are dynamic. This means your data changes every day – but is your database up to date? Is the data you use to drive your business as accurate as the day you procured it? Data Decay is an issue that every company must face at some point. Email marketing databases, for example, naturally degrade by approximately 23% every year according to Hubspot.

Data decay has especially accelerated during and after the pandemic. This is agreed on by 79% of Customer Relationship Management (CRM) users according to The State of CRM Data Health in 2022 published by Validity. As the business environment restructures itself in the post-pandemic era, a new symptom is quickly spreading among companies: millions of workers are still quitting their jobs in 2022. The “Great Resignation” is affecting even the most solid data-driven strategies for B2B marketers.

High-quality data is the fuel that makes the sales funnel engines spin. According to the Global Data Management Report, which considered responses from 700 data-centric business leaders around the globe, 84% of B2B companies saw increasing demand for data-driven insights within their organizations during the COVID-19 pandemic. The effects derived from the “Great Reshuffle” or “Big Quit” have accelerated this decay to levels not fully understood.

While the degree of decay is not yet fully understood, our response to it can greatly mitigate the effects the decay will have on our organizations’ successful use of data to drive decisions. Here are 6 ways you can address data decay to ensure your data is accurate, up-to-date and, most of all, insightful:

What Is The Hidden Cost of Lead-Based GTM?

Latest Articles
Learn which job change sales signal predicts a real buying window, and how to work both accounts before competitors do.

Article

Which Job Change Signals Predict a Buying Window?

Your best-fit account went quiet six months ago. Then the VP of Revenue Operations you never reached moves to a new company. That single move is a job change sales signal, and it opens two doors at once. One at the old account, where a seat just emptied. One at the new account, where someone with budget wants to prove themselves fast.


Most reps see the notification and scroll past it. The ones who hit quota treat it as a timer starting.


The problem is that not every job change matters. A lateral move between two mid-level analyst roles rarely changes anything. A new CRO with a mandate to rebuild the tech stack changes everything. Knowing the difference is what separates a busy pipeline from a real one.

Bulk uploads drain credits and hand your list to a vendor. Enrich a CSV of leads row by row instead — verified emails, direct dials, and fit scores.

Article

How Do You Enrich a Spreadsheet of Leads Without Handing It to a Vendor?

You have a list. Maybe it came from a webinar, a conference badge scan, or an export someone pulled from your CRM two quarters ago. It has names, companies, and a few job titles that were accurate at some point.


What it does not have is phone numbers, verified emails, or any sense of which rows deserve your morning.


So you look for a way to enrich a csv of leads. The first path most reps find is a vendor upload. Drop the file, wait, get it back fuller. That works until you read the fine print, watch the credits drain, or realize your file is now sitting on someone else's server.


There is a second path. It is slower on paper and faster in practice, because it gives you a read on the account instead of a fuller row.

Per-credit models punish volume. Per-seat models punish turnover. Compare both on cost per usable contact, and see when a free tier beats either one.

Article

Email Finder Pricing Compared: Per-Credit vs Per-Seat

You open a prospect profile, click for the email, and watch a counter tick down. That single click has a price attached to it. Whether you feel that price depends entirely on how your vendor decided to bill you.

Email finder pricing splits into two camps. Per-credit models charge you for every reveal. Per-seat models charge you a flat fee per user and cap what you get inside that seat. Both sound reasonable on a pricing page. Both behave differently once you are running 80 touches a day and trying to build real pipeline.

This breakdown covers how each model works, where each one quietly costs you more than expected, and how to pick the one that fits how you prospect.