Meeting the Need For Data Quality

A few years ago, I returned to Brazil after living in the United States for 16 years. Residency in both places gave me the chance to appreciate some key differences in the use of direct marketing tools in these two countries. One topic in particular — data quality — has not been discussed in detail.

In Brazil, and throughout Latin America, data cleansing tools and know-how are lacking.

Having worked as a technologist my first 10 years of professional life in Brazil, I had never heard of data cleansing. My first encounter with the need for data quality was when I joined a company in 1987 that was later acquired by Harte-Hanks.

What surprised me was that at least some data quality technology has been in use in the United States since the early 1960s. As far as I know, that need came after the 1960 census, when Jack Sweeney with two other partners won a bid to develop a system to clean U.S. census data. Soon after, Sweeney with two other partners won a bid to develop a system to clean U.S. census data. Soon after, Sweeney realized the opportunity for tools of that kind for banks, insurance companies and other businesses in the United States, and he further developed the application to provide services of data cleansing for the private sector. He had an instant success.

Through the many years serving different organizations in the Brazilian marketplace, I know that many organizations here face the same kind of data-related problems. For instance, it is common to see one customer record stored in product files multiple times. It is also common to have a customer's name spelled multiple ways. Add to that the multiple platforms and operating systems and support staff and geographical places where these files are held, and that is just the start of the problem of data duplication and accuracy.

The ability to know a customer's family group or business associations is also a challenge here. Such householding information would allow for improved sales opportunities such as cross-selling to family/business-related prospects, in addition to a better customer knowledge.

The problem of data quality does not end there, as a constant need exists for the rental, exchange and purchase of lists to support customer acquisition initiatives. How can a product be offered to a new customer if we don't first check whether that customer has the product? How much should we invest on offering a checking account to the spouse of our checking account customer? How can I avoid sending identical offers to a single prospect or household? How can I ensure that the marketing message even will reach that prospect?

Consider a direct mail example. I've seen returns of 20 percent on a “welcome” package for first-time customers. Such waste makes it easy to invest that throwaway money on an address-cleanup service as a first step in customer data management.

With the new investment in customer relationship management, which is finding its way to Brazilian companies and multinationals doing business here, the biggest problem in Brazil is the loading of customer data as is into these systems, rendering them useless for CRM because of poor data quality.

Among technical journals, practically no articles are published on this need for data cleansing. We also don't find them in marketing or business media, so it becomes difficult for business and technical managers – the decision makers — to learn that there is light at the end of this tunnel, as well as a reason why their investments in CRM and database marketing may not be optimal.

Several weeks ago, we held a conference in São Paulo about data cleansing and drew a full house. The market is starving for this kind of know-how and technology. Attendees asked us to do more events of that nature, and the event's ROI has surpassed anyone's expectation.

All in all, not a bad place to be or an area to invest.

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