There’s an old saying about data and data quality: Garbage
in and garbage out. It still holds true, as long as there have been databases.
Data quality is essential. Nothing can undermine or torpedo user adoption in a
new CRM than having bad data. Bad data costs you money. It could be upwards of $100
per duplicate record, for example, which is quite serious.
1. Analyze Your Data
Before you can start cleaning your data, preventing bad
data, and enhancing your data, you need to know the overall state of your data.
In other words, how dirty is your database? The first step is to analyze and
benchmark data quality.
Analyzing the state of your database requires you to ask
yourself the following questions:
How bad is our duplicate situation?
Where are the duplicates coming from?
How does your data quality stand up against other
salesforce.com customers?
Establishing a data quality dashboard will tell you not only
how many duplicate Leads you have, but where they are coming from, when they
were created, and other key, actionable information.
2. Clean Your Data
Bad data comes in many shapes and sizes, and therefore,
cleaning it does too. Here’s a look at a few of those, including data
standardization, duplicate data, and completing missing data.
Data Standardization
A lot of bad data comes down to human error. If an
organization doesn’t have any sort of standards or policies to articulate how
the data is entered into their CRM, different iterations of your data will
exist and be committed to your CRM. The solution is data standardization, also
known as normalization, which creates an enforced, organized and consistent
environment for entering data into your CRM.
Duplicate Data Cleanse
Duplicate removal is not the only consideration when looking
for a fresh start, but is arguably the most critical. The solution is to cleanyour existing CRM and then stop duplicate data before it enters your system
ever again.
Complete Missing Data
CRMs include is a vast number of Data Markers. These
markers are a literal road map to filling in missing data. For example,
if 100% of the emails for a particular company have the email format of
Firstname.Lastname@domain.com, then you can probably fill in missing emails for
other contacts with confidence. If you have the email domains for
contacts, but the account record is lacking a website, that can be filled in
too.
Data Validation
Data validation ensures that your CRM operates on clean,
correct and useful data. It’s important to routinely check your data validity
via set validation rules, constraints and routines identified from the start.
This makes sure there is correct and meaningful data in your system.
3. Protect Your Data
Without a protection strategy, your data will continually
decay. Not only do phone numbers, emails and titles change, but as your
employees are entering data into your CRM, they are creating duplicates and entering
data inconsistently.
Protecting your data includes:
• Ongoing duplicate prevention
• Ongoing standardization
• Continuing to Complete Missing Data and
Validate Data
4. Enhance Your Data
Without enhancing your existing data, you limit your data
potential. Additional information on the record will help to complete the
contact’s information, giving you a 360-degree view of the contact. Enhancing
your data ensures accuracy by verifying the email addresses and saving your
salespeople time from sending bad emails.
When sales teams, customer success teams and other employees
do not have access to a complete record, they waste time looking in external
systems and on the internet in search of that contact information. According to SiriusDecisions,
this results in over 30% of an employee’s time being wasted on contact
research.
