Data ethics is a system of values and moral principles related to the responsible collection, use and sharing of data. Manage all collected data in accordance with legal regulations and customer expectations. Gain their trust and improve Customer Experience.
147 marketing executives found that 82% of them would consider leaving their employer if they felt the data approach was not ethical
Only 48% of advertisers admit to having a data ethics policy
31% of respondents are concerned that their data will be used for non-corporate purposes
25% believe that data will be shared with third parties
74% of CMOs believe data ethics will get even more important for their business in the next five years
modern business model and become transparent to gain your customers’ trust
transparency about what customer data is actually used for to ensure a better reputation, trust, retention, and loyalty of all customers
a universal framework to guide what will and won’t be done with customers’ data
strong data management, educate employees on transparently monitoring customers' behavior and preferences
the personal data rooted throughout the organization sustainably and ensure ethical responsibility in the short, medium and long term
any unintentional biases that can always happen or create a negative image of your brand driven by poor business decisions
the doubts about customers data shared with third parties
on taking ethical actions across all channels all the time
your contacts informed about actions taken with their information and data
Principles of Data Ethics
Transparency as a priority
Data processing activities have to be clear and understandable by the individual in terms of understanding risks, as well as social, ethical, and societal consequences.
The human being at the center
Business would not exist without people, so human interests must prevail over institutional and commercial ones. The human always has to stay in the center and have the primary benefit of data processing.
Individual data control
A person’s self-determination should be prioritized in all data processes and the person should be actively involved with regard to the data recorded about them.
Use but also protect personal data in a reflective, reasonable and systematic way. Make efforts to reduce the risks for the individual and to mitigate social and ethical implications.
Process data but still pay special attention to vulnerable people, who are particularly exposed to profiling that may adversely affect their self-determination and control or expose them to discrimination or stigmatization. Reduce bias in the development of self-learning algorithms.
Data ethics policy
Focus on zero-party data
Ensuring ethical AI
Consent management center
Content maximally relevant and tailored to individual user needs