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The third pillar of any proper Data
Quality initiative is Enhancement – which comes as a result
of the successful application of the first two,
Standardization and Validation.
With Enhancement though, your data takes a giant leap forward
in usability and value. While
Standardization and Validation clean and correct your data;
Enhancement supercharges
it and takes it from the realm of “what
you’ve got” to the realm of “what you want”.
Let’s take a look at Mr. Doe
again and ask some questions a savvy marketer might ask…
| 1. |
How old is Jon?
|
| 2. |
What does he do for a living?
|
| 3. |
Is he married or single?
|
| 4. |
Does he have
any children?
|
| 5. |
If
so, how many and how old?
|
| 6. |
Does he own
a home or ?
|
| 7. |
If he owns
his home; how long has he owned it?
|
| 8. |
What’s
its value, or square footage?
|
| 9. |
How
much does Jon earn in a year?
|
| 10. |
How many cars does
he own?
|
| 11. |
What’s
are their makes, models?
|
| 12. |
Does
he like to hunt, fish, golf, play computer games, purchase online?
|
....and so on.
There are over 1000 different
self-reported data elements for B2C
data, and hundreds more for B2B,
that can be used to enhance your data.
What would this kind of information help you achieve?
For one; your efforts to retain clients for the long-term
will be greatly enhanced, as well as your ability to cross-sell and
up-sell. In addition, your prospecting efforts will yield a
better ROI - in less time - by being able to target better, qualify
better, and close better with the additional information on the
data.
Ultimately
this results
in a better overall relationship for both you and your
clients.
Remember,
Enhancement allows you to undo all the deficiencies in your data as
related to your past collection efforts.
With Enhancement you can intensify the level of detail you
have on your clients and prospects, getting you much closer to
a true 360-degree view of your customers and prospects that is sure to propel
your business forward at speeds you’ve only dreamed of before.
Increase your data’s depth and breadth, and you
intrinsically increase its value and usability at the same time.
Standardization
Validation
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