Marketing Operations - Data

Data

A company will often say that its people are its greatest asset; but when it comes to Marketing, that may not be true. Data is arguably Marketing’s greatest asset. The quality of a Marketing campaign depends entirely on the quality of the data that it leverages about existing and prospective customers. ‘Database marketing’ is the term used for the marketing techniques that are aimed at leveraging data to deliver more highly personalized, relevant campaigns. The Direct Marketing Association (DMA) sponsors an annual conference called The National Center for Database Marketing focused on just this topic.

Database marketing emphasizes the use of statistical techniques to develop models of customer behavior, which are then used to select customers for communications. As a consequence, database marketers also tend to be heavy users of data warehouses, because having a greater amount of quality data about customers increases the likelihood that a more accurate model can be built.

Data quality refers to the uniqueness, accuracy, consistency, completeness, timeliness, currency, conformance and referential integrity of a data set. Relative to Marketing, quality data attributes accurate name, address, company, title, firmographic, demographic and preference information to the contact record for a customer or prospective customer. Obtaining and maintaining quality data is an ongoing challenge that often falls to Marketing Operations. A comprehensive effort involves the following steps:

• Evaluating the condition of the existing marketing data
• Conducting a ‘spring cleaning’ process to separate out duplicate data, dummy data (e.g. Santa Claus), and incomplete data
• Establishing a process to conduct routine cleansing of incoming and existing data
• Putting in place a process to augment data with new lists or purchased firmographic or demographic data
• Installing a database or data mart in which to store all marketing contact data

It is good practice to measure the quality of the data before implementing these steps, and then measuring again when done, and every quarter thereafter. Some relevant metrics include: the number of duplicates, email bounce-backs, percentage of dummy data, response rates, etc..

An entire category of software companies facilitate data quality management. Gartner lists DataFlux, IBM, Trillium Software, Informatica, and SAP Business Objects as leading data quality tool providers. Other related technology categories include ‘Data Integration Tools’ and ‘Customer Data Integration’. There is also a set of companies that sell data, or services to clean and enhance data. Some of these include: Dun & Bradstreet, Experian, Equifax, MarketWatch, and InfoUSA.

A related subject—and an area that requires a separate effort—is information privacy or data privacy. Data privacy refers to the legal issues that surround the capture, use, storage, and sharing of personally identifiable information. This has long been an issue for healthcare and financial services companies. It is now a concern across all industries. To complicate matters, every country has a different set of legal and political concerns relative to data privacy (sample list here -http://www.informationshield.com/intprivacylaws.html) Global companies must be sensitive to the laws in every country in which they do business.