How to keep the email database clean?
                     How to keep 
the email database clean?
, 
Table of contents
 
Consolidation   
What is data cleansing?
  
 
How do you know you achieved an 
Keeping your email list healthy (Knowing 
optimal database?
and tracking)
  , 
Tactics for removing dirty data
 
 
Warning signs you need to improve email 
data quality and scrubbing
How data cleansing helps? 
 
 
How to build a high-performing database?
Comprehensive steps for the entire 
 
process
Steps to execute
 
 
 
Parsing and correcting
Conclusion
 
 
Standardization and matching
What is data cleansing
The many definitions of data c, leansing are:
Process of removing the errors
Identifying incomplete parts of the data
Deleting the obsolete data
Act of finding the data that do not belong to the specific dataset
Helps in the email list management process
Keeping your email list healthy, how do you know?
Frequent soft bounces , 
Contact never opens your email
Hard bounced email contact
Recipients that are inactive
What does list hygiene keep track of?
Finding the invalid addresses
Removing the addresses with typos
Deleting the emails from all the bo, unces- soft and hard
Updating the valid addresses
Dummy values
Multipurpose fields
Lack of unique identifiers
Data in the contradictory form
Warning signs to improve your data quality: 
Industry average open email rate, - 21.33%
Industry average conversion rate- 3%
Industry average click-through rate- 2.62%
Industry average ROI- 122%
Scrubbing your email list
It won’t transfer the bad contacts
Reputation would be intact 
, 
Only paying for the active subscribers
Warmup process would be quicker
How to build high-performing database:
 
Collecting email addresses from all the best means
Validating the data while it is collected
  , 
Not sending emails to addresses that have spammed you
 
Segmenting the subscribers based on demographics and behavior
 
Segmenting the inactive users and bringing them on the same page as you
 
Replacing the dead email addresses
 
Steps to execute:
 
Parsing the data
 
Correcting the data , 
 
Standardization
 
Matching 
 
Consolidation
Parsing the data:
The process scraps the data from the emails.
 It locates the different elements in the source files to isolate in the target files
  , 
For example: All the data is entered into the individual fields, name, location, city.
 
Correcting the data:
It is the verification of the data whether the data is entered into the relevant fields
 
For example: The city name in the city field or the firm name in the firm field.
       
Standardization:
The process follows transforming the data into its standard business 
format.
For example: It follows the rule where all the fields are included in a 
specific order. , 
 
Matching:
Step followed to match records across the database to eliminate 
redundancy
Consolidation:
 
It finds the relationship between the entire merged and the compared records
 
It is consolidated in a single presentati, on
 
How do you know you have achieved an optimal database?
 
Validity
 
Consistency
, 
Accuracy
 
Uniformity
 
Completeness
Tactics for removing dirty data:
 
Developing the data quality plan
 
Validating the data accuracy , 
 
Standardizing the contact data at the entry point
 
Identifying the duplicates
 
Appending the data
 
How does data cleansing help?
 
It helps improve the customer segmentation
 
It improves the email deliverability
 
Accelerates the customer acquisition process, 
 
Streamlines the business practices in the long-run
 
Target customers in an efficient way
 
Avoid the compliance issues with GDPR
 
Increase the overall ROI
 
Removing errors means happier employees
 
Comprehensive steps for the entire process:
 
Removing the irrelevant data
 
Taking care of the outliers , 
 
Standardizing the data
 
Validating the data
 
Checking structural errors
 
Flagging the missing data
Conclusion:
 
Data cleansing is required to maintain the efficiency of the database. There 
are various steps that could help you cleanse the same. Understand the best 
methods, practices, and each of the te, chniques in this presentation.
InfoClutch is a leading suppilier of most sought after segmented
global mailing database. We offer fully customizable prospect
data of your preferred specification.
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