From Trust to Transaction

Trust is something that runs deeply throughout our dealings with brands.  We are so used to it that it is only when it is absent that we can start to recognise its value, understand what it is and how it is built, as well as destroyed.  Having said that, there is a problem at the heart of this issue.  Trust in all institutions appears to be in crisis. Indeed, the 2017 Edelman UK Trust Barometer indicates that trust is in crisis around the world. [i] The UK’s population’s trust in all four key institutions — business, government, NGOs, and media — has fallen. It is therefore critical that we properly understand trust and how brands can address the apparent decline.

Despite levels of trust falling, it has not evaporated.  To understand this, it is worth remembering why we use trust in the first place.  The answer is that it is impossible for us to operate completely independently, which makes trust a necessary basis for any interaction.  So, for example, fact that we no longer live in a subsistence economy means we cannot grow and store all our own food!  We need others to help us with that, so inevitably we need to trust all the different companies in the chain from field to shopping basket.  We could check everything in their process to make sure that they were doing what was required but that would not only be logistically changing (or impossible) but in this case, trust would not be required.

Experience shapes expectations

This begs the question of why we are we seeing such a significant decline in trust?  There has been much discussion about this but with such a significant broad-based issue it is difficult to offer a definitive, evidence-based conclusion.  However, we can potentially understand this better if we look at the digital economy. The reason for looking in this direction is because of the way in which our expectations are driven by experience.  Bruner & Minturn (1955) illustrated how experience could influence expectations by showing participants an ambiguous figure ’13’ set in the context of letters or numbers e.g.


The physical stimulus ’13’ is the same in each case but is perceived differently because of the influence of the context in which it appears. We EXPECT to see a letter in the context of other letters of the alphabet, whereas we EXPECT to see numbers in the context of other numbers.

So how does this relate to consumer behaviour? Technology disruption means that new expectations of standards for product and service experience are being created by brands in completely different categories. So, my experience of the slickness of using Uber will influence my expectations of interactions with an online bank. The ease with which I use my iPhone will bleed into my experience when trying to book an appointment to get a new washing machine delivered.  Our experiences are shaping our expectations across all categories.

Implications for brands & trust

So how is the digital economy reshaping attitudes towards brands?  Fundamentally, we are seeing a decline in the degree to which we are willing to consider ‘human’ capabilities as a valid means of determining our response.  There is a decline in our willingness to place our faith in a range of very human attributes including loyalty, expertise, intuition and even love.  The dominant values in society are gradually shifting from intangible, ‘humanistic’ and subjective to ones that are tangible, ‘machine-like’ and ‘objective’.   We are arguably now much more convinced by virtues of transparency, reliability, optimization and personalization.

Why is this?  Largely because experiences of technology are reconfiguring the way we think about ourselves and the expectations we have of others.  As our relationships with others are increasingly mediated by technology, the features of the medium mean we experience others as more measurable, predictable and ultimately ‘knowable’.  This means that our expectations are slowly but subtly changing.

How does this apply to trust?  Well, trust is a very human characteristic.  We don’t expect machines to trust each other for example.  We may expect a machine to measure the reliability of another machine and then be programmed to act accordingly.  But we do not expect the machine to decide to take a risk on the trustworthiness of another machine.  There is something very human about that activity.

But arguably our experience with technology is leading us to reshape our expectations.  We are moving away from this human act of trust and instead, making assessments of the reliability of others.  In a way, we are almost becoming machine-like in the way we evaluate others.

In the past, we would not have been able to make assessments about the reliability of others as this requires us to have a checklist of all the things that we require of them.  But everything has changed.  Many of our transactions with brands (and indeed each other) are now identified, measured and scored.  Look at the way we now use peer reviews on most shopping sites to decide which brands we wish to purchase.  Indeed, a recent study found that 90% of consumers read online reviews before ‘visiting a business.’

And we use the same metrics with each other. When we use AirBnB we have a range of metrics on the owner (and on ourselves) that can be used to make decisions about who we do business with.  Or take babysitting services such as UrbanSitter which is wholly predicated on ratings of both the parents and sitters.  [ii]

The key point is that we are no longer relying on marketing messages about the trustworthiness of services being offered.  This has meant, on the one hand, that we can be more confident about using the services of absolute strangers – whether to rent their homes or look after our children[iii].  But it also means, on the other hand, that we are less interested in building a trusted relationship with third parties – with all the willingness to accept risks which comes with that.  Instead, we want a transparent, measurable and verifiable transaction.  This helps explain apps like FoodSwitch which allows you to scan the barcode of food and drink products and see the level of fat, saturates, sugars and salt.  There are many such apps on the market across all categories which offer ever greater levels of sophistication.

What does this mean for brands? 

There are three key lessons emerging from this:

  • There is little choice but to opt for ‘radical transparency’ concerning each aspect of the contents and process. Consumers are clearly looking for this and if they don’t find it they are likely to assume the worst.
  • Exercises in building trust are not wasted as it’s important to note that the trends we are seeing are not necessarily consistent across the market. Decisions concerning some products are still driven more by trust and less by transparency.  And some consumer segments (perhaps older consumers) will still be more likely to make decisions based on trust rather than transparency.
  • But overall brands will increasingly need to spend less money on ‘brand building’ and talk more about the tangible aspects of their product/services/processes in order to excite, engage and intrigue consumers. [iv]

These not only require changes in the way in which marketing and advertising are used but a more fundamental rethink to the way in which brands consider the entire business process.  Are there points there which may not bear scrutiny?  Alternatively, are there points which can be brought to the attention of consumers?  An era of radical transparency is upon us – the point is for brands to seize the opportunity and mitigate the threats.


By Colin Strong


[i] See

[ii] For more reading see

[iii] For more reading here see Rachel Botsman (2017) Who Can You Trust?: How Technology Brought Us Together – and Why It Could Drive Us Apart. Penguin

[iv] For more reading see Itamar Simonson (2014) Absolute Value: What Really Influences Customers in the Age of (Nearly) Perfect Information.  Harper Business

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Colin Strong is Head of Behavioural Science at Ipsos. In his role he works with a wide range of brands and public sector organisations to combine market research with behavioural science, creating new and innovative solutions to long standing strategy and policy challenges. His career has been spent largely in market research, with much of it at GfK where he was MD of the UK Technology division. As such he has a focus on consulting on the way in which technology disrupts markets, creating new challenges and opportunities but also how customer data can be used to develop new techniques for consumer insights. Colin is author of Humanizing Big Data which sets out a new agenda for the way in which more value can be leveraged from the rapidly emerging data economy. Colin is a regular speaker and writer on the philosophy and practice of consumer insight.

Categories Marketing, Technology, Trust