How to keep the email database clean?

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• How to keep
• the email database clean?
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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  

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What is data cleansing

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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
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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
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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

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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
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Scrubbing your email list It wont transfer the
bad contacts Reputation would be intact Only
paying for the active subscribers Warmup process
would be quicker

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How to build high-performing database   Collectin
g 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  

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Steps to execute   Parsing the data   Correcting
the data   Standardization   Matching
  Consolidation

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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.

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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

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

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How do you know you have achieved an optimal
database?   Validity   Consistency Accuracy   Uni
formity   Completeness

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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   Appendi
ng the data

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  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  

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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

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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.

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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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940 Amboy Avenue, Suite 104, Edison, NJ 08837, US.
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