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5 highly disregarded consequences of Privacy Compliance for Digital Intelligence, Marketing Analytics and Big Data

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We have all heard it (even louder in Europe, of course):

  1. It will soon become virtually impossible to make use of third party cookies, due to legal constraints if not technical ones (eg. Safari’s default settings and Do Not Track features in new browsers)
  2. Social media profiles cannot be so happily tied into our CRM (thus achieving “Social CRM nirvana”) without express user permission, however public our tweets are
  3. IP addresses are already deemed “personal data” in many countries, obliging web analytics vendors (think Google Analytics or Adobe) to obfuscate them, and resulting in marketers’ inability to use them in any possible manner
  4. The “single view of the customer” across mobile, web or other channels (think Google Universal Analytics) can only occur under the scrutiny of privacy watchdogs, with many platforms expressly forbidding the storage of encrypted customer IDs (even when they do not represent PII by themselves) and all of them being subject to a legal requirement for express permission regarding such cross-channel integration.

What is left of a marketer’s big data dream after all this? Reality will settle in, but here is an advance (together with a small illustration that we could title “the revenge of the silos“):

pre-privacy check vision and post-privacy check vision: data collection, analysis and integrated reporting/delivery

  1. There is no (such) control over the customer journey. You can entertain yourself defining “personas”, though, and establishing anonymous links between channel-specific segments. Or perhaps you are lucky to count on a large enough sample once all of the above hurdles are overcome
  2. Multichannel attribution will require wild assumptions. Positive side? Marketers will focus instead on the things that do matter when it comes to optimizing campaigns – namely, building a single version of the truth that is based on first party cookies and brand-led data integration
  3. SocialCRM may never really take off beyond areas of very clear control (ie. a closed community). Instead, try sampling with those individuals that do give you their permission
  4. Integrated analytics may not get much further at data collection level, and efforts to build a single analysis layer often end up in the realm of joint reporting
  5. Multi-source (highly personalized) dashboards represent your best shot at short term success. They will also spare you a waste of resources and redundancies at data collection level.

It is no coincidence that we recommend making the most of aggregate data as a first step towards data-driven management. There is always time to dive into the perils of customer data integration once you know which KPIs and tables will actually need analysis capabilities at such a granular level.

What do you think? What is your experience?

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Sergio Maldonado

Founder & Chairman at Sweetspot. Author, speaker on analytics, marketing technology, privacy compliance. JD, LLM (Internet law). Once a dually-admitted lawyer. Father of three. I love surfing and cooking.


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You made some good points there. I looked on the web for more info about the issue and found most individuals will go along with your views on this website.

Published on March 18th 2014, 8:02 am   

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