This presentation talks about how to keep your database clean and why you need to improve email data quality and scrubbing. How to build a high performing database? Steps to know that you have achieved an optimal database. Various tactics for replacing redundant data and how data cleansing helps?

1. How to keep
the email database clean?
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2. ,
Table of contents
What is data cleansing?
Keeping your email list healthy (Knowing
and tracking)
Warning signs you need to improve email
data quality and scrubbing
How to build a high-performing database?
Steps to execute
Parsing and correcting
Standardization and matching
Consolidation
How do you know you achieved an
optimal database?
Tactics for removing dirty data
How data cleansing helps?
Comprehensive steps for the entire
process
Conclusion

3. ,The many definitions of data cleansing 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
What is data cleansing

4. ,
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

5. ,
What does list hygiene keep track of?
Finding the invalid addresses
Removing the addresses with typos
Deleting the emails from all the bounces- soft and hard
Updating the valid addresses
Dummy values
Multipurpose fields
Lack of unique identifiers
Data in the contradictory form

6. ,
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%

7. ,
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

8. ,
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

9. ,
Steps to execute:
Parsing the data
Correcting the data
Standardization
Matching
Consolidation

10. ,
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.

11. ,
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

12. ,
Consolidation:
It finds the relationship between the entire merged and the compared records
It is consolidated in a single presentation

13. ,
How do you know you have achieved an optimal database?
Validity
Consistency
Accuracy
Uniformity
Completeness

14. ,
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

15. ,
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

16. ,
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

17. ,
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 techniques in this presentation.

18. ,
InfoClutch is a leading suppilier of most sought after segmented
global mailing database. We offer fully customizable prospect
data of your preferred specification.
940 Amboy Avenue, Suite 104,
Edison, NJ 08837, US.
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