The bottom line of trust

Trust disproportionately impacts bottom line. It’s no longer a ‘fuzzy’ concept organisations can hypothetically value yet practically ignore.

If you, like so many of the people I speak to daily, are focused on designing more trustworthy experiences for your customers, this article is for you. Specifically it will;

  1. Help you understand the factors that lead us to believe the timing to take action is now

Market forces

People distrust ‘the system’ and its leaders. This is a somewhat global phenomenon. Yet the trust people place in organisations data practices is even lower. We call this the data trust gap.

Organisations are beginning to understand this. They recognise they are information driven. They recognise their use of information has real world impact. They’ve begun to place ethics, privacy and customer trust atop their list of organisational priorities.

But why is this the case?

Think about it. Organisations need access to customer (and other categories of) data to run their business and deliver a competitive proposition.

Traditionally customer data has been acquired with limited active participation from individuals. People are not informed, empowered and capable of making choices.

This is changing. People are increasingly informed about how their data is being used (Note: They aren’t too happy about it. They feel powerless). The media onslaught is assisting with this.

Regulations are evolving. They too are gaining significant media attention.

Technologies and standards are progressing. The idea that privacy means limited data utility is dying (too slowly, but it is happening). In any case, privacy is so often misunderstood. Zuckerberg’s recent 3,200 word essay showcases just how misunderstood privacy is, even amongst the most powerful of the tech elite.

Moving on.

The trajectory we are on is clear; data sharing events are becoming more explicit.

Learning to design these experiences is something organisations must take seriously. This means developing new capabilities, engaging in more cross-functional collaboration and producing truly differentiated outputs.

The result of these efforts should be a more informed group of people (read: customers) with a high propensity to willingly share their data. The organisations who achieve this will be competitively differentiated. They will get to know their customers better. They’ll develop the most valuable, meaningful and engaging propositions.

But let me be clear, this is not about designing for trust. Trust is a variable outcome design can influence. It cannot be controlled.

What can be controlled are the steps an organisations takes to become verifiably trustworthy. This is what we advocate. This is what we grapple with on a daily basis.

Okay. If you’ve watched the video and read the content above, we trust you’ve got enough to invest in the next step. Let’s talk about the tools you need to develop an actionable body of evidence.

Your new toolkit

Let me start with a truly critical point; too many organisations overvalue stuff they can count. They have a bias towards quantitative data.

This is a problem.

Actionable customer intelligence isn’t the result of just knowing the what. It’s the result of a deepened understanding of the why.

This sounds simple. Most people nod their heads at this. But all too often (four times over the last fortnight to be specific) we engage in conversations with experienced, assertive leaders who just don’t get this.

They say things like, “we know almost everything about our customers”.

You can imagine my excitement.

After a short pause, I reply with, “Brilliant! Can you tell me more?”

The 5 Whys are then put into practice. What we uncover is that the organisation has access to a lot of behavioural data. Let’s say they’re a Telco. In most cases the organisation does not have explicit access to this information, meaning customers have no idea what’s happening.

We learn that effective (and usable) inferential analysis is limited. We also learn that this data is almost never used to frame hypotheses and put them to the test with actual customers.

As a result they know almost nothing about why people do what they do.

We often refer these people to Christian Rohrer’s 2014 post, When to Use Which User Experience Research Methods.

Basically we need to help people understand what research methods to employ and when. We do this based on the questions we’re trying to answer.

By understanding the questions we can employ the most appropriate method.

My point? If we limit our approach based on an organisations bias, we are unlikely to design the most effective outputs. This hinders our ability to increase comprehension, decrease time to comprehension and increase people’s propensity to willingly share information.

These customer outcomes are crucial for modern information businesses.

There’s plenty more about this in our recent playbook, Data Trust by Design.

Now let’s talk about our Data Trust by Design workflow.

We engage in two distinct practices. We bring the practices together through a specific approach to collaboration.

This workflow helps us;

  1. Learn about customer attitudes and behaviours (as it relates to privacy, data sharing and the relationship these functions have to the outcome of the product and service) on an ongoing basis

Practice 1: Trust Mapping

Drawing on well established service and experience mapping exercises, this process enables us to;

  1. Design a proposed experience (conscious of our principles)

This is a relatively light touch, low cost way to get us closer to an experience that delivers customer value and achieves business objectives.

Practice 2: Experiments

After getting close to customers (in the context of privacy and trust) via our experience mapping exercise, a larger scale experiment can help us learn more quite quickly. Ideally it’ll help increase the confidence interval we assign to the experience we’d like to implement.

This is also how we begin to better understand whether any clear attitude to behaviour gaps exist. Do people say they’ll do one thing and then do another?

The Experiment Card is designed to be printed out and used in its physical form. This way the cross-functional teams designing and executing experiments have a clear view of priority, experiments in progress and insights revealed throughout the process.

Fostering collaboration with Pair Design

Bringing Data Trust by Design to life effectively requires buy in from the entire business. It also requires cross-functional teams to design and implement service experiences together.

Pair Design, and the process accompanying it, increases the likelihood we design service experiences that balance business, technical and regulatory considerations.

It starts with establishing shared context. Then mapping and challenging the desired experience. The output is then put to the test, refined and repeated (prior to implementation) if necessary.

Specifically, pairing designers with data protection practitioners or Privacy Engineers, to tackle a shared challenge.

Across a variety of projects this approach has decreased time to usable output (design output that is implemented) by >25%.

Executing this workflow will help you build a new body of evidence. You might focus on broken terms and conditions, moving away from dark patterns, or requesting access to new categories of data that will help the organisation competitively differentiate. The direction is up to you.

Now to what matters most.

How to ‘sell’ internally

Let’s be frank. The best place to start is with the board. They are responsible for governing the organisation. They help set strategy and manage risk.

If the board buys in, the authorising environment has been created to develop the strategy, execute the tactics and define the measures that will enable your organisation to make progress.

But, you don’t have to start here. You can start with something specific. You can build a body of evidence and you can utilise that body of evidence to attain buy in across the organisation.

Although context really matters, there are three things we’d suggest you do;

  1. Define an area of focus that matters to customers and the business. Your agreements and how you ask for access to data are the obvious places to start. Use the intelligence you’ve gathered and the experience you have to direct this focus.

If you’re looking to make this process more systematic, check out the bottom of this post. The switching canvas may be of use.

Although this isn’t an exhaustive representation of what we do daily, we trust it gives you enough to get started. If you’ve got any questions about where to start or how to keep moving, chat to us.

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Nathan Kinch

A confluence of Happy Gilmore, Conor McGregor and the Dalai Lama.