Transpromo Threatened by Poor Data Quality

By | June 25, 2008 has a short article on the quality of data used in Transpromo campaigns. The article cites a study in customer data standards conducted by direct marketer DsiCMM.

According to the DsiCMM study:

Government, credit card, mobile phone, banks and storecards emerged as the major offenders in large part, not because their data standards are substantially lower than the other sectors, but because they generate such high volumes of transactional documents. Misdirected bills and statements are most severely experienced by the 25-34 age group, with almost two thirds (62.2%) having received such transactional documents addressed to the wrong person, consistently reducing across the older age bands up to the over-55s at 25.4%. This is perhaps not surprising in that new home activity also tails off with age. However, even amongst the more static but wealthier empty-nesters aged 55 and above, still fully one quarter are experiencing misdirected bills and statements.

Yesterday, published an article by Barb Pellow on using data to drive a marketing campaign. In the article Pellow states, “Data-driven marketing starts with good data. You must work with your customers to examine both internal and external data sources. Internal data sources abound, and marketers must work across the array of internal data points. These include: Purchase or transaction histories; Customer service; Trade show leads; Prepaid business reply cards; Web leads.”

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One thought on “Transpromo Threatened by Poor Data Quality

  1. Pat McGrew, EDP

    Let’s not confuse deliverability of a mail piece with the data that generates it. The best TransPromo does not take data fields directly from a database and plop them into an offer on a billing statement. The best TransPromo aggregates data you have about your customers, develops trends and profiles, and coordinates offers based on what you have learned. While the physical address has an impact on some of the aspects of the profile, it is often not such a key factor. An exception, of course, might be if you profile people y post code who live at a marina or golf course and who then move away from that landmark and change spending habits as a result, but honestly that is something that should be caught well in advance of an offer being made.
    To net it out, good data goes well beyond the physical address data.

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