All posts by "Ken Dreifach" →

About Ken Dreifach

Ken Dreifach

Ken counsels clients on complex issues involving information privacy and data law, online liability, consumer regulatory and gaming law, including regulatory response, and adherence to self-regulatory guidelines for online advertising. Ken has had more than twenty years of experience in high-profile regulatory, in-house and private practice roles, including as Chief of the New York Attorney General’s Internet Bureau. He is one of the nation’s leading authorities on the relationship between emerging advertising technologies and online privacy.

Recent Posts

Podcast: Data Do, Data Don’t

August 16, 2017 | 0 Comments

Most websites and apps collect information from its users. But are you doing it in a legally-compliant way? We won’t be taking over any New Year’s countdowns, but listen to our radio-ready voices as we...

Read More →

The FTC sent a loud signal, in the form of a $925,000 settlement with mobile ad network InMobi, that the Commission’s focus on ad tech data privacy is not limited to app developers and websites,...

Read More →

As “native” ads have become an increasingly effective way to engage users and generate revenue, we have also seen several recent developments towards creating standards for native ads. These include FTC guidance issued in December...

Read More →

I draft and edit a lot of data licensing and data services agreements for online, offline, social and mobile data. I often find myself revising or deleting certain reoccurring provisions because they invite disputes, raise...

Read More →

Precise geolocation data is increasingly being used to “geo-target” consumers’ devices, to serve ads relevant to either where they are at a given moment, or where they tend to be during a given time frame....

Read More →

Data “onboarding”—also called “CRM retargeting,” “CRM onboarding,” or just “audience targeting”—is a relatively new way for marketers to reach highly particularized audiences online. It differs from behavioral tracking models because it uses de-identified data originally...

Read More →