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DAVE's Dirty Dozen Data Disasters: Unusable Data




DAVE’s ‘dirty dozen’ of data disasters continues!

Over 12 weeks, we’ll break down each of the 12 dastardly data disasters for you, so you know what to look for and what to avoid –the last thing you want is your day to be dragged down by data.


We’re continuing this week with #8: Unusable Data


We are all human (except for DAVE) and sometimes data is entered incorrectly. What is known as the good old-fashioned “typo”.


Email addresses: A prime example is email addresses that get keyed in wrongly and end up with, dare we say, an illegal format. Emails need to conform to a legal format, such as akyiet@demandflow.com.au . If we let a comma creep in instead of a dot and get akyiet@demandflow,com.au , then your email won’t know which way is up. Copy an email address and paste it in with the angle brackets still in place to make “<akyiet@demandflow.com>” and you are also in some potential strife.


Both these email addresses will bounce or not get sent. Your reach will be reduced and your eDM campaign won’t have the impact you’re hoping for.


DAVE identifies invalid and missing characters and flags these for easy resolution.


Phone numbers: It’s the same situation with incomplete phone numbers. See how far you get when you try dialling 02 9439 383 or 0402 45602.


You are a vital digit short. The calls won’t connect. You’ll need to do unnecessary research to figure out the correct number and that’s another way to slow things down and rack up more cost.


DAVE identifies these numbers and flags these for easy resolution


Postal addresses: If you want to go old school and just stick with the old ‘snail mail’ way of getting your message out there, you are going to want to avoid having incomplete addresses.


“54 Smith Street, NSW” isn’t going to do you much good without the suburb and postcode. Without these key features, the address cannot be used for a direct mail campaign or for any geographically-based target marketing.


DAVE looks at other data available and completes the suburb, postcode, state and country fields, wherever possible. Any remaining and unusable addresses are flagged for easy resolution.


DAVE can tell you how.


Check out some examples


Next post: Junk records!

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