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Personal Data Collection: Privacy Concerns May Degrade Data Quality

In an effort to protect their privacy, consumers may be providing merchants with inaccurate data.

Many years ago, customer data collection efforts were limited to demographics such as name, address, age, religion, race, and ethnicity. It also encompassed purchased data such as credit ratings, home purchase price, and real estate tax data gathered by visits to town halls, and details provided by consumers when they responded to survey questions on warranty registration cards.

Today, organizations can capture (or purchase) psychographic data such as attitudes, values, interests, and lifestyle data and track your website activity, searches, physical location, and social media postings. They can also use WiFi signals to track prospect and vehicle movements. This may lead to a high degree of customer segmentation and result in one-on-one sales pitches, targeted marketing campaigns, and personalized discounts that might benefit consumers. However, it also involves what some consider to be a violation of their privacy.

Despite consumer concerns, it is almost certain that, unless specifically forbidden to do so by law, commercial and governmental organizations will continue to gather and analyze consumer data. Furthermore, due to industry acquisitions, consolidations, and marketing partnerships, e-mail contacts, telephone contacts, credit card transactions, and purchase histories may now be more readily available. For example, although some companies have a started policy of not sharing consumer data with non-affiliates, an acquisition can suddenly turn a non-affiliate into an affiliate.

When combined with the recent paranoia (both real and imagined) about the NSA's data collection efforts and the seemingly continuous reports of data compromises at supposedly secure vendor sites, many consumers may attempt to take steps to better protect their privacy. Efforts to maintain confidentiality may be further intensified in light of the May 2014 release of a report on data brokers by the Federal Trade Commission. The report noted that some data brokers used the data they collected to characterize individual consumers into a variety of classifications. These categories ranged from relatively innocuous "Dog Owner" to more sensitive categories such as "Financially Challenged," "Urban Scramble" (e.g., low income and minority consumers), or "Rural Everlasting" (e.g., single people over age 66 with low educational attainment and net worth). (Source: Data Brokers A Call for Transparency and Accountability, Federal Trade Commission, May 2014)

Consumers React

In an effort to protect their privacy, consumers have resorted to a variety of tactics, including:

  • Supplying false information when applying for in-store customer loyalty cards
  • Providing phony e-mail addresses at websites that require one before allowing downloads
  • Periodically rotating mobile devices among their friends or turning off WIFI when not needed
  • Setting social media permissions to their highest level of privacy
  • Reading the "fine print" and opting-out of granting organizations permission to share their data
  • Paying for transactions with cash rather than credit cards (after the Thanksgiving hacking event, weren't you just a little concerned when you used a credit card at Target?)
  • Answering surveys with incorrect answers (please do not do this with Census questionnaires!)
  • Setting high privacy or "do not track" levels when surfing the Web
  • Disallowing or frequently deleting cookies

Advice for Organizations

It is important for the analytic and marketing staff of organizations tracking and analyzing prospect data to realize that some of this data may be not only erroneous but perhaps even deliberately false. The data may also not be timely because data brokers, a major source of consumer data, may not update their databases in real time. Even if they do, the organization obtaining brokered data may choose to refresh this data much less frequently, if at all.

Organizations can minimize (or at least identify) some of the falsehoods in several ways. For example, they can:

  • Verify data such as e-mail addresses or distribute downloads via an e-mail address
  • Deploy phone number and address verification services
  • Allow users to set preferences for website advertisements and avoid bombarding them with ads they have previously ignored many times before
  • Avoid following every customer interaction, no matter how trivial, with surveys that take more time to complete than the interaction itself
  • Letting customers know what data is being tracked and how this potentially benefits them

Also, although not the result of consumer falsehoods, employees of stores with customer loyalty "discount" cards (a favorite method of tracking customer purchases) may inadvertently compromise the purity of the data collection process. Organizations need to educate employees about the goals of the customer loyalty card and explain to cashiers that they should not use their own cards to help customers that don't have one.

The Bottom Line

Consumers are becoming more concerned about their privacy and taking steps to protect it. Data warehouse practitioners need to advise their users that that when analyzing prospect data all consumer-related "big data" is not necessarily quality data. Remind them that GIGO (garbage-in, garbage-out) still applies.

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