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Face the Facts: Data Decay is Killing Your Pipeline
Bad data costs companies HOW much every year? 
There’s really no room for debate. The world of sales and marketing today runs on data!
Think about it. Sales outreach, marketing campaigns, budgetary decisions, forecasts and more – all depend on data to be successful.
It’s so ingrained into business culture that we commonly call ourselves, “Data-Driven” (or as I like to say, “Data-Guided”).
Our worldwide data obsession makes sense too. With clean, accurate data, organizations can optimize nearly every area of the business. Campaigns convert at a higher rate, more revenue rolls in, and organizations can keep their doors open.
Unfortunately, we all live in a world where clean data doesn’t stay clean. There’s no escaping the reality that data, despite how important and expensive it can be, is a perishable resource.
In fact, data is decaying at a faster rate than ever.
This poses a big problem for businesses today. Left unchecked, data decay can and will cause serious financial challenges. Collectively, it’s upwards of a $1 trillion dollar problem.
Data affects the Fortune 10 down to freelance solopreneurs and everyone in between. This isn’t just for global enterprises..
We’re all in this together.
In this article, we’re going to bring you up to speed about:
- What exactly data degradation is
- How quickly data decays
- How fast databases grow
- Financial impacts and burdens data decay places on companies
- Suggestions & best practices for surviving and thriving in the perpetual war against data decay
(Quick sidenote – we use the terms data decay, data loss, and data degradation interchangeably for readability purposes)
1) What is Data Decay?
Data decay or “data degradation” refers to the rate at which accurate data becomes obsolete or inaccurate.
For sales and marketing, this applies to areas such as:
- Contact information and records
- Email address deliverability
- Accuracy of company data (geography, name, characteristics)
2) What Causes Data Degradation?
What’s accurate and up-to-date one moment could very well be useless in the next. According to ZoomInfo, each of these data-points change at a rate from 30-43% per year.
- Job changes
- Names changes
- Phone numbers change
- Titles and positions change
- Email addresses change
- Company names and locations change
In the time it takes you to read this article, over 100 people will have switched jobs or changed their title.
Takeaway: This is why databases decay at a rate of 30% or more every year.
3) How Fast Do Databases Grow?
Now, it’s important to understand that we’re dealing with a double-edged issue here.
While data quality decays by 30% or more every year, the quantity of records are rapidly increasing by 100-150% every year.
Think of it this way.
- Let’s say you have a database with 10,000 records.
- After one year, you’ll have upwards of 20,000 records
- Of those 20,000 records, at least 6,000 of them will be outdated, if not more.
Takeaway: As sales & marketing teams, we have to be consciously aware of the data that’s imported into the CRM. It’s not just a RevOps job to maintain cleanliness, it should be an all-hands-on-deck effort.
4) So What's the Financial Damage Look Like?
It’s not pretty.
As of last year, 40% of business objectives are failing because data is a limiting factor.
What are the Soft Costs of Bad Data?
The success of marketing & sales campaigns is bad data’s first victim.
Delivery rates go down because of bad emails.
In turn, productivity and conversions both suffer tremendously.
Real-world example:
- Say you use a Sales Engagement Platform to send 1,000 emails over the course of a month.
- Let’s assume you start with a delivery rate of 95% and a conversion rate of 2%
- This would mean that out of those 1,000 emails, 19 (2% of 950 sent) would convert into engaged conversions.
Now that’s not too bad!
Let’s compare the same intended result with bad data in the mix:
- 1,000 emails are sent with a 65% delivery rate with the 2% conversion rate..
- You are only going to set 13 meetings with the same effort (plus, you’ll know the effort invested into 300 emails was wasted)
- Now, to set 19 meetings, you’d have to send almost 1,500 emails
Ouch..
We warned you the truth would hurt.
There’s more bad news.
With decreased delivery rates (or increased bounce rates), your Sender Reputation will start taking a hit.
Sender Reputation
This is a topic that deserves its own post, but here’s the highlights.
Think of sender reputation like a credit score. It’s a calculation that reflects the quality of emails sent from a particular domain / email server.
In the same way that late payments affect credit, spam and undeliverable emails affect sender reputation.
And in the same way that bad credit makes it harder to borrow more in the future, a bad sender score makes it harder to deliver emails in the future.
It’s a brutal, viscous little cycle.
Takeaway: With bad data, sending more emails to achieve a the same input is not the answer. It’ll compound the problem and incur huge long term penalties. It’ll take time to recover the score, and in that time you’ll still have reduced abilities to deliver campaigns (which are crucial for business growth).
If you feel the need to deep dive into this topic, Twilio Sendgrid is a great place to start.
What are the Hard Costs of Bad Data?
We did mention that organizations lose billions of dollars every year from bad data. That’s just part of it.
They spend billions more trying to fix it.
Since that’s a bit difficult to conceptualize, let’s look at economic impact in a more relatable way. DiscoverOrg (Zoom) quantifies the total cost in their 1/10/100 rule.
- $1: the cost of verifying a record as it’s created in the CRM
- $10: the cost of correcting & completing the record later
- $100: the collective cost of doing nothing about it
So if you have hundreds or thousands of bad leads in your system, then it’s going to quickly snowball into an issue that costs hundreds of thousands of dollars.
Hence why 40% of business initiatives are failing due to bad data.
5) Best Practices for Sales Teams
While bad data quality has a snowball effect that derails strategy, decreases productivity, damages relationships, and lowers the bottom line, there are ways around it.
Be Wary of Purchasing Lead Lists
Purchased lists are like the greasy fast food of the data world. It’s cheap and quick, but it has harmful effects on you health.
More than likely, purchased lists have high bounce rates. Which, as we reviewed above, does you absolutely no favors.
Use an Email Verifier to Remove Bad Data From Campaigns & CRM
Think of emails verifiers as a filter for finding the good data amidst a world of decayed data. Just because a record seems accurate, it doesn’t mean it is. Email verifiers can help you determine the real truth.
You can learn more about email verification and sending in general by reading our Quick Guide to Bounce Codes and Email Deliverability.
Leverage B2B Databases that Update & Maintain Accuracy
There are dozens of providers for databases full of B2B contacts and companies. Inevitably, the data in each will be obsolete.
So, makes sure that your solution also verifies a record again BEFORE you send it to your CRM. If you don’t, remember you can be incurring hundreds or thousands in overhead later. This makes investing in a solution that doesn’t do this much less economically attractive.
Next Steps
You can learn more about navigating the challenges of data decay with the recommended reading below.
And in case you’re not aware, FoxBound DataScout is a Chrome extension that allows you to build lists of verified prospects & send only clean data to your CRM. All you need to get started is a business email and a LinkedIn account!
Zach Sergio
Co-Founder
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UPDATED ON
January 17th, 2020
Zach Sergio
Co-Founder
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