The MRS Delphi group, the think tank led by the Market Research Society, in association with Kantar TNS and Lightspeed, questioned 1,001 people in the UK to understand the drivers of trust across seven sectors for its Great Expectations report.
Phil Sutcliffe, head of innovation and offer at Kantar TNS, speaking at the MRS Impact annual conference, noted that “we all feel somewhat vulnerable” with the sheer amount of personal data that companies now possess about us. It is fair, he added, to say that the rise of personal technology has contributed to the decline of trust.
According to the research, the first driver of consumer trust is that “the information they have on me is completely secure”. However, the study shows a conflicted public.
Ten or fifteen years ago, he said, “this wouldn’t have been up at the top, but there have been so many well publicised [data] breaches now that it has become important”.
The results of the research were surprising, with good customer service coming in as the third greatest driver of trust, and brands doing what they say coming in second. In all, three of the top five trust-drivers relate to data.
“I won’t be put at personal risk by brands having my data” comes in at fourth, while number five is that businesses and brands don’t take advantage of personal data.
Just one third of consumers were happy for their personal data to be used in order to improve services. Two thirds rejected this idea and the age breakdown showed that 60% of older consumers (over 55) and 42% of 16-34 consumers did not want their personal data used at all.
Remarking on the implications for brands, Sutcliffe noted that brands have to do three things: “provide guarantees, or at least reassurance in terms of data security”; be transparent in their reasons for using the data, “so they [consumers] don’t feel they’re being put at personal risk”; and the use of data should provide utility.
Ironically, the most trusted brand overall was Amazon, a company, Sutcliffe said, that “probably makes more use of our personal data than any other business I can think of”.
However, “they do so in a way that people feel fairly secure … they feel there’s transparency. For example, negative reviews are given equal weighting to positive reviews.
“They see a benefit from the data they’re providing, in terms of recommendations”, or pricing, or fulfilment.
Sourced from MRS Delphi; additional reporting by WARC staff