Dirty Data – Do You Care? – Marketing WTF?
I’m not a marketing or sales guy per se so please help me understand something here.
As the classic saying goes, “I know at least half of my data is bad…I just don’t know which half”.
Marketing Sherpa tells us that contact data degrades at a rate of 2.1% per month (and it’s probably gone up substantially given the current rate of job loss), it’s easy to see how this is essentially a self-fulfilling prophecy.
Having said all that, does it matter you could be sitting on piles of dirty data?
Contact data cleanup seems to experience a run-up of demand at the end of the year when marketers have just enough budget to burn on something small to mid-sized but not enough to do anything substantial with. Or at least this is what we saw. In fact, we cleaned up some of our own CRM data in December as well.
But come the turn of the new year and new budget, the psychology of “new” is the all the rage. Sales reps are innately in perpetual want for new leads, but as we say around here, it seems most marketing and sales teams would rather keep building new add-on rooms to their houses than spend the money to fix the basement that is flooded with sewage.
So what is the psychology behind using what you have vs. buying something new? Is it simply fueled by an unquenchable thirst for “new, new, new” (and the perception thereof)? Or do you have a more systematic approach to if and when you elect to use what you have vs. buy new stuff?
Is it the same mentality of buying something that is on sale even if you don’t really need it?
I just don’t get it.
One Response to “Dirty Data – Do You Care? – Marketing WTF?”
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April 15th, 2009 at 9:27 pm
>So what is the psychology behind using what you have vs. buying something new?
Jason, the psychology is visibility. Marketers and Sales reps have a limited view and, thus, a limited understanding of the data available to them in CRM and marketing automation systems.
Although they might be able to extract just about anything that is in the back-end, they rely for the most part on canned reports or pre-set queries to draw the data that they tend to analyze often as disaggregated lists through spreadsheets. These dynamic extracts return data in various stages of decomposition.
First impressions matter and, often, what the eye first captures is what colors the rest of the batch.
Reps and marketers are not known for being statistically minded. They’re not interested in random sampling, distribution curves and two-tail analysis. They get a first taste of data; it tastes sour and they curse the whole barrel. Give them a chance to recommend a solution to it, and they will say ‘Dump it all and fill the wine skins with new wine!’
So, the key to data reuse and moderated data acquisition is to measure the quality of production data across multiple dimensions and track these metrics within a model that can easily demonstrate to the data users the true significance of those first impression concerns about quality.
Typically I use 4 dimensions to track data quality: 1) Timeliness, 2) Accuracy, 3) Completeness and 4) Consistency. Together they define Integrity, and an integral data set is a sweet libation to the lips of any user.