Human Data Privacy

DataSift’s mission is to provide insights while protecting consumers' identity.


The need for a privacy-first approach to data

Great businesses are built on consumer trust. Many businesses are putting that trust at risk due to their handling of consumers’ personal data. Consumers are becoming more concerned about the way their information is used and these concerns are being taken seriously by social networks and governments around the world. Changes to terms of service and new regulations mean that Human Data insight needs to be more thoughtful.

At DataSift we believe that respecting data privacy needs to be the starting point of any Human Data project. Technology needs to be built with privacy protection at its core and respecting personal data should be part of the culture, strategy and practice of every business.

A privacy-first approach doesn’t have to be difficult - just follow our seven founding principles to ensure that you stay on the right side of your customers, the social networks and the law

Be ethical - DataSift Data Privacy

Be ethical

Doing the right thing makes business sense. Unethical behaviour erodes consumer trust, which in turn erodes revenue. Before you decide how you are are going to use Human Data, think about how you would feel if it was your data, or your family’s. Don’t get carried away with the “art of the possible”. Don’t just consider whether you can do something, but also whether you should.

Be transparent

Always be clear on what personal information you are collecting, how it will be used and why you require it. The most successful Human Data initiatives provide a mutual benefit for the company and the consumer. Your “why” should be something the consumer actively wants to get involved in.

Be transparent - DataSift Data Privacy

Respect data provenance and integrity - DataSift Data Privacy

Respect data provenance and integrity

Privacy doesn’t end with the click of an “I agree” button. Consumers need to be able to trust that their data is being used appropriately and that they retain control of its use. Respect social networks’ terms of service and ensure that user controls such as delete propagation are in place.

Practise active data governance

Storing personal data on individuals incurs a responsibility to protect that data. The more data and the wider its use, the more of a burden this becomes. You need an active policy to define retention limits for each data type and need to review the policy regularly.

Practise active data governance - DataSift Data Privacy

Aggregate and anonymize - DataSift Data Privacy

Aggregate and anonymize

Most Human Data insight can be drawn without personally identifiable information. You can make decisions on brand, product and operations from audience level data. Understanding industry topics and trends is much easier when working in aggregate.

Use opt-ins for consumer-level analysis

When consumers have opted-in (e.g. via a social log-in) you can gain insights for customer service or targeted marketing. Make sure you are transparent about how you are joining different data sources to gain this 360 view.

Use opt-ins for consumer-level analysis - DataSift Data Privacy

Protect minors - DataSift Data Privacy

Protect minors

Don’t collect or analyse personally identifiable information from those too young to consent to data usage terms. Legislation in many countries prohibits use of this data without the parent’s permission.

Balancing Human Data Intelligence and Consumer Trust white paper

Balancing Human Data Intelligence and Consumer Trust

This DataSift white paper examines the rise of Big Data analytics, explores consumer concerns surrounding how their data is used, and provides a framework for organizations as they process Human Data.

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