Edelman and The University of Cambridge Psychometrics Centre have carried out the largest study in history of public’s vs marketers’ perception of predictive data & technology

Brands are at severe risk of overestimating consumers’ trust in and willingness to adopt predictive technologies, according to a new report from Edelman and The University of Cambridge Psychometrics Centre. Trust and Predictive Technologies 2016, is the largest study of its kind ever conducted, and surveyed more than 34,000 people around the world, and found that 71 percent of consumers believe brands with access to their personal data are using it unethically. Seventy eight percent of the public also view the threat of negative media coverage as an insufficient deterrent to prevent businesses from misusing personal data. These concerns stand in stark contrast to the 94 per cent of marketing professionals who say predictive technology is important for them to understand the psychological attributes of their customers.

The Key Findings

1. Fears relating to privacy are consistent across age, gender, country and personality Psycho-demographic variables explain less than two percent of the variance between yes and no answers to questions about uses of Big Data. Privacy is a universal concern, not an esoteric interest.

2. There is a deep lack of trust in data-driven businesses and in government 71 percent of people thought most companies with access to their personal data did not use it ethically; only 26 percent of people trust the government not to sell their electoral roll and demographic data without their consent.

3. Marketers are at serious risk of overestimating how comfortable consumers are with predictive technology Across sectors, marketing professionals were consistently more knowledgeable and more open to sharing data for prediction than the general public. This reveals a clear need for companies to better communicate their data practices, or face potentially dire consequences.

4. There’s a clear gap between how consumers want predictive technology to be used, and how it’s actually being used 84 percent of people thought predictive tech should be used to improve the quality of healthcare and 47 percent of people thought it should be used to determine the price of their car insurance.

5. Yet Businesses are investing in smarter Big Data regardless 77 percent thought their organization ought to invest in predictive data and 94 percent said it was important for them to understand the psychological attributes of their customers.

6. Consumers’ fears, whilst universal, are nuanced There is demand for personalized finance, yet distrust of actuarial prediction. The majority think predictive tech should not be used to assess mortgage eligibility or likelihood of default (62 percent and 67 percent respectively), but were open to its use for better account management and advice.

7. Overcoming peoples’ fears requires Privacy, Transparency & Relevance 66 percent of people would prefer to see personalized advertising, assuming they have to see some advertising. Privacy, transparency and relevance are the building blocks of effective Big Data-based marketing.

8. Beyond fear lies opportunity ‘Pay for Privacy’ is a real opportunity for traditionally data-dependent businesses. 27 percent would pay $3 a month to use Facebook without their behavior being recorded. Offering paid options helps remind consumers that their data has value, and that even if they use a service for free, they are still effectively paying for it.

9. Demand for secondary services from IoT data is soaring 57 percent of people thought that e.g. smart fridge data should be used to recommend groceries to them when they go shopping; 58 percent would like to be automatically warned of unhealthy dietary habits.

So what does this mean for brands and business leaders? 80 per cent of the general population believe business has a responsibility to solve the challenges facing society, up from 74 percent in 2015. Thus it is clearly down to marketers and business leaders to address the public’s fears around predictive data and technology. Privacy, Transparency & Relevance are key to achieving this, which means offering accurate, detailed information about how customers’ information is being captured, stored, used and shared. The good news for brands willing to, or already following best practice, and striving to educate and engage the public via a two-way conversation - is that they will benefit from a competitive edge, due to enhanced public perception and new business and revenue opportunities. The ability to see around the corner is a superhero power that new predictive technologies enable. However, if brands fail to recognize and deliver on their duty of care regarding privacy, transparency and relevance, they are at severe risk of losing the public’s long-term trust. Everyone in a leadership position now has a responsibility to ensure this new power is used in the right way and for the greater good. Otherwise one of the most powerful tools to have emerged in our society for decades could be lost, setting back innovation in marketing and business by years.

Click here to download the Trust & Predictive Technologies 2016 report. You can also view a presentation below, which covers the results and key findings in more detail, to learn more about trust in Predictive Data & Technology.

Jonathan Hargreaves is global vice chair, Technology.