Today, good marketing relies on having detailed and accurate customer data. And companies, not surprisingly, are eager to collect vast troves of it. For instance, Amazon continuously tracks the behaviors of its 100 million Prime members, an example of “first-party” data. And many companies have found that sharing their own customer information with other companies creates synergies for both parties, especially with the increasing availability of “internet of things” data (GPS sensors, smart utility meters, fitness devices, etc.). These are examples of “second-party” data. Finally, many companies supplement their first-party data with “third-party” data from companies like Acxiom, which collects up to 1,500 data points on 700 million consumers worldwide.
Protecting Customers’ Privacy Requires More than Anonymizing Their Data
The trillion-dollar question in marketing today is whether it is possible for businesses to reap the promised benefits of data-driven marketing while maintaining the privacy of customers’ data. The most common data protection approach currently being followed by businesses is to control access to the data after it’s been gathered. But this access control approach is woefully inadequate, as is pseudonymisation, which attempts to anonymize data, but falls short. Other approaches, such as data aggregation, lead to severe degradation of information. It’s time for businesses to consider using statistical approaches to convert the original data to synthetic data so they remain valuable for data-driven marketing, while adequately protecting customers.