Business, boiled down to its simplest terms, is often one elaborate game of risk. Come January 1, 2020, a slew of companies doing business in the United States will be forced to weigh theirs like never before.
Effective on that date, a landmark consumer privacy law, the California Consumer Protection Act (CCPA), goes into effect. As a result, for the first time, many US businesses will be subject to a far stricter set of privacy regulations.
In short, American consumers will now have the legal right to instruct a given company to disclose what personal data has been collected about them, and request the company immediately dispose of it. This process is known as a consumer request to be "forgotten."
As a consumer, the new law is straightforward: One's right to privacy has been significantly elevated. And if a company chooses not to comply with the new regulations, it will incur a financial penalty larger than ever before.
But that's only the start. Because things get far more complex—and, for marketing measurement and consumer tracking analytics people like me, quite interesting. That's because as it stands, so many companies remain unsure as to how these new regulations will impact their marketing strategies:
- What will need to change about their data collection processes
- How sensitive their current models are as it relates to consumer privacy
- Whether the marketing measurement tools employed by their respective vendors are compliant—and less accurate—with the new regulations
The new law also has wide-ranging implications for a company's marketing strategy. Even if a company audits its process and complies with the new regulations, it's no exaggeration to say the law will greatly affect the accuracy and efficacy of long-held marketing measurement approaches like attribution.
When consumers remove themselves by invoking the right to be forgotten, gaps are introduced in the measurement picture. And, mind you, those are not random gaps. Attribution approaches attempting to stitch together a "path to purchase" now have missing pieces, and the entire approach starts to crumble. Brands today are also using a host of probabilistic mechanisms to identify consumers; additional holes in this data throws off its accuracy more significantly.
The result is a swarm of potential problems in terms of both overstating and understating the value of marketing, and so getting that part of the equation wrong.
Take the first step (it's free).
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