As promised earlier today, here is the first post in an endless row of positive posts about success in data quality improvement.
This beautiful morning I finished yet another of these nice recurring jobs I do from time to time: Deduplicating bunches of files ready for direct marketing making sure that only one, the whole one and nothing but one unique message reaches a given individual decision maker, be that in the online or offline mailbox.
Most jobs are pretty similar and I have a fantastic tool that automates most of the work. I only have the pleasure to learn about the nature of the data and configure the standardisation and matching process accordingly in a user friendly interface. After the automated process I’m enjoying looking for any false positives and checking for false negatives. Sometimes I’m so lucky that I have the chance to repeat the process with a slightly different configuration so we reach the best result possible.
It’s a great feeling that this work reduces the costs of mailings at my clients, makes them look more smart and professional and facilitates that correct measure of response rates that is so essential in planning future even better direct marketing activities.
But that’s not all. I’m also delighted to be able to have a continuing chat about how we over time may introduce data quality prevention upstream at the point of data entry so we don’t have to do these recurring downstream cleansing activities any more. It’s always fascinating going through all the different applications that many organisations are running, some of them so old that I didn’t dream about they existed anymore. Most times we are able to build a solution that will work in the given landscape and anyway soon the credit crunch is totally gone and here we go.
I’ll be back again with more success from the data quality improvement frontier very soon.