We live in a data-centric world. Everything from marketing campaigns to sales calls derives from existing data. And the best way to ensure your business decisions are impactful is by having the highest-quality data at your disposal.
But how do companies manage to have the highest-quality data possible to make informed decisions? Through a process called data hygiene.
What is Data Hygiene?
Data hygiene — aka data cleanup, cleaning, or scrubbing — is the process of removing obsolete information, known as dirty data, from your CRM. Old email addresses, duplicate contacts, incomplete records (like a contact with no phone number or email), and corrupted entries are examples of dirty data that you need to remove.
Data hygiene is ideally a systematic approach that consistently keeps your CRM in tip-top shape rather than a one-off effort. A data hygiene policy starts well before you have to clean up dirty data. Using a systematic approach and setting clear parameters for data collection can save you a lot of headaches down the road.
Why is Data Hygiene Important?
Imagine what would happen if you had 20,000 contacts on your list and only about 2,600 people opened your emails.
Now imagine that, out of those 20,000 contacts, you only had the correct email address for 5,000. The metrics would be drastically different in each case — with the full, inaccurate list having an average open rate of roughly 13% pre-data cleanup and a 52% open rate post-data cleanup.
While it may seem more impressive to have a list with 20,000 contacts, you really want a list of engaged contacts.
With a data hygiene policy, you’re removing the background noise and honing in on those valuable people with the potential to convert into paying customers.
Implementing a data hygiene policy can significantly impact how you use your CRM and how effective your sales process is. Your data hygiene policy can increase your open rates, shorten your sales cycle, and save precious time for everyone on your team, from marketing to sales and customer experience. Not only will your team be in a better position to engage prospects, but each prospect will receive exactly what they need at every stage of their journey to becoming a paying customer.
These are some of the ways a data hygiene policy can positively impact your CRM:
1. Increased open and engagement rates
While it may be exciting to hit a big milestone like thousands of email subscribers, a list full of old email addresses, missing fields, or misspellings will produce lower performance across the board. Cleaning up obsolete information and outdated contacts results in better performance indicators.
As a business, of course, you need a big pool of prospects to grow. But, instead of collecting dirty data that will never convert, you want to focus on truly qualified prospects that engage consistently with your emails and eventually work with you.
2. Effective segmentation
If your CRM is filled with dirty data, you risk having contacts in the wrong segment and sending them irrelevant information, which may cause them to disengage or unsubscribe altogether.
3. Accurate lead scoring
One common problem with dirty data is the presence of duplicate contacts. In this case, each version of your contact may be scored differently based on the information associated to them, which can lead to a poor customer experience, and ultimately, it can cost you a sale.
Data Hygiene and Related Terms
The effectiveness of your CRM depends on the quality of the data your organization collects. And there are lots of terms that seem to overlap when it comes to data management and hygiene.
These are some of the most common terms you’ll find:
Data quality: Data quality is a measure of how accurate, reliable, and up-to-date your data is at any given point. Evaluating data quality will be one of the first steps of implementing a data hygiene policy.
Data integrity: Data integrity refers to how complete and consistent your data is throughout its lifecycle. In simpler words, this means that the data makes its way through your organization and comes out exactly the same as when it went in.
Data corruption: This is the opposite of data integrity. Data corruption is what happens when data becomes unusable or unreadable. Some of the most common causes of data corruption are tech failures (like a system crashing with no backup) and human error (like someone making a typo when entering an email).
Data enrichment: Data enrichment is the process of expanding your existing data with more accurate and relevant information about a contact. If we had to draw a parallel, data enrichment is the opposite of data hygiene in that it’s all about adding new data to existing contacts, while data hygiene is all about removing obsolete information.
Data masking: Data masking is the act of replacing sensitive data with fake versions that mimic the real data. The goal of data masking is to protect your company and customers from prying eyes.
You Rely on Data to Make Decisions
The more accurate this data, the more effective each decision can be. While it may seem like investing in a data hygiene policy is expensive and time-consuming, the truth is that having dirty data is expensive and can hinder your business growth.
But all is not lost if you haven’t implemented a data hygiene policy. It’s never too late to get started.