Nudging for Good – Behavioural Science and Product Design

During a recent Capita webinar on ‘The Future of Work’, David Haigh from the Money and Pensions Service was asked what he’d learnt about financial wellbeing in the 20 years that he’s worked in the space.

His response was that understanding how people interact with software products and having a knowledge of fields such as Human Computer Interaction (better known as HCI) was just as important as understanding how and why people make economic decisions.

This article is about the intersection of product design and behavioural science, particularly in the context of personal finance and financial health.

When Nudging goes bad

If you are lucky enough to have a signed copy of ‘Nudge’ by Richard Thaler, the Nobel Prize winning pioneer of behavioural economics, you’ll know he always signs it ‘Nudge for Good’.

This sentiment has gained real currency of late thanks to a film called The Social Dilemma which was released on Netflix in September 2020 and has been making waves ever since.

For those not yet familiar, it concerns the extent to which social media firms have been applying behavioural science in the design of their products, especially their mobile apps, to drive user engagement.

How they’ve done this is a fascinating story which starts with a fellow called BJ Fogg.

Fogg, a professor at Stanford University in California, established what became known as the Persuasive Technology Lab over 30 years ago.

Having more or less invented the field, he has been studying the impact of technology on human behaviour ever since.

After decades of research he published his equivalent of Einstein’s famous formula. In his case it’s B = MAP, which stands for Behaviour = Motivation + Ability + Prompt (sometimes called ‘trigger’.

And Fogg maintains that the co-ordination of these three factors at specific moments is what constitutes behaviour that, over time, becomes habitual.

While Fogg remains largely unknown outside of Stanford’s niche academic circles, that can’t be said of his students.

Like many who attended Stanford in the early 2000s, many of them went on to be early members (and occasional founders) of social media companies that ultimately became some of the most well-known and valuable corporations in the world.

These included Justin Rosenstein, the Facebook engineer who invented the ‘Like button and Kevin Systrom, one of the founders of Instagram.

Thanks to the advertising-based revenue model that all the social media companies adopted, these and other former students began drawing on Fogg’s formula to try to help them compete in what became a global arms race for our attention.

Fast forward to 2017 and these students of BJ Fogg have become more successful and influential than they ever imagined.

However, a story begins to surface in Silicon Valley as various engineers from these companies begin to raise concerns about the impact that their products might be having on all our lives.

Another famous student of BJ Fogg is Nir Eyal. He wrote a book called ‘Hooked: how to build habit forming products’ in which he adapts Fogg’s behaviour model to establish his own ‘Hook’ model.

In his book, Nir Eyal suggests that addictive loops of behaviour were being implemented in social media companies consisting of:

a ’Trigger’ event such as a notification.

an ‘Action’ such a click on the notification

a ‘Reward’ moment, typically a piece of information such as seeing a photo that someone has posted

and finally an ‘Investment’ of the users time or effort that helps to make the product even more customised to their individual profile (and therefore more engaging.)

Nir Eyal suggests that these loops were now powered by powerful AI algorithms designed to keep users coming back to these social media apps endlessly.

This story culminated in 2018 with a famous series of interviews given by Chamath Palihapitiya, one of the very early engineers of Facebook who founded what became known as the ‘Growth Team’. Under his guidance Facebook’s user base went from millions to billions of people in only a few years.

Chamath, like the others, admitted contrition about the cost of the success that Facebook and other social media companies had achieved.

One of the most interesting moments in the Social Dilemma occurs during the final credits when most of the contributors, who all worked at social media companies, are asked whether they allow their children to use mobile phones.

Like Chamath, they all reply that they rarely do so but never let them use any social media apps at all.

From Sludge to Nudge

So where did social media go wrong and what can we learn from them about behavioural science and user engagement as UK fintechs in 2020?

Above all, we learn that all software products (not just social media) should be aligned around the best interests of their users and customers. And that their commercial model should never be at odds with this.

Whereas social media companies applied what are known as ‘Dark Patterns’ of product design, we should employ light patterns.

Whereas social media companies were driven purely by profit, we need to be focussed on beneficial user outcomes.

Social media companies were covert in their application of these tactics, never disclosing them to users and making it hard for them to turn them off. We must be completely transparent about how we do this.

And finally, they employed what Richard Thaler likes to call ‘sludges’ – tactics that actually prevent users from achieving certain goals.

The best example of this would be unsubscribing from a service which is almost impossible through many apps or digital products, often requiring a lengthy offline experience such as a phone call in order to complete. Whereas we will always ‘Nudge for Good’ as Thaler encourages us to do.

So where do we start?

Anyone who works in the wellbeing sector would acknowledge that we are ultimately in the business of changing behaviours or trying to effect positive behavioural change.

But somewhere there’s a line between paternalism and manipulation that we don’t want to cross.

And there are a number of frameworks we can refer to guide us and establish rules of engagement.

These include assessing vectors such as transparency, the extent of possible consequences and the degree of control a user has in the interaction.

At the tactical level, we have principles of implementation such as these outlined by Richard Thaler.

One of the first things we established at Level Financial Technology, before we even released a product, was an Ethical Charter. We publish this on our website and it defines the operating principles we adhere to in all our product decisions, especially as regards user privacy and how we handle user data.

Next, as Thaler recommends, we made nudge controls clear to the user and easy to turn off.

We all know that changing entrenched behaviours is very hard. One of the most important things we can learn from BJ Fogg is the role that a person’s motivation plays in behaviour.

“You can’t ‘hack’ motivation long-term – it naturally waxes and wanes over time.”

And BJ Fogg tells us that the best way to start is to identify moments when someone’s motivation to change is very high and then to offer them what he calls ‘hot triggers’ which give them the opportunity to enact a new behaviour.

But we also know that motivation occurs in waves. And Fogg likes to say, you can’t ‘hack’ motivation long-term – it naturally waxes and wanes over time. So it’s pointless expecting someone to change their behaviour at times when their motivation is low.

In terms of personal finance, there’s a consistent high point of motivation that provides great opportunity for us to establish new habits and that’s payday, which typically occurs monthly.

So the obvious ‘hot trigger’ is to make it as easy as possible for someone to make a savings contribution at the same time they get paid and when their motivation is highest – this is how our Savings product works at Level.

And what behavioural science also shows us is the powerful role that employers can play in financial wellbeing solutions, beyond what banks or consumer fintechs can offer.

By enabling deductions on payday, direct from salary, employers are actually uniquely positioned to offer more compelling and effective solutions to financial wellbeing than anyone else.

Turning back to Nir Eyal’s model, his observation about the role of user investment in a product is a key tenet of behavioural science theory.

Thanks to our partnership with the Behavioural Insights Team, we know this is called ‘the IKEA’ effect. It’s a cognitive bias in which users place a disproportionately high value on products they partially created or invested time in configuring.

Level apply this principle in the design of their budgeting tools, notably a key feature we call ‘Left to Spend’.

By connecting each of their bank accounts to Level and identifying their regular monthly expenses and incomes, users can get a hyper-accurate, real-time indicator of what they actually have Left to Spend as opposed to what their bank balances tell them.

This helps them to micromanage their cashflow on a daily basis, avoid reliance on flawed ‘mental accounting’ and reduce the risk of financial shocks that can tip them into overdraft or even debt between pay days.

We’ve also learnt from BIT about the importance of visualising goals and the extent to which they drive inner motivation and reinforce commitment. Therefore, users of Level’s Savings product are encouraged to upload a photo of the item or event they are saving for.

There is also the ‘goal gradient effect’, which means that as people get closer to achieving a reward they accelerate their progress towards their goal. People are more motivated by how much is left to reach their target rather than how far they have come.

So we also display a users’ Savings in the form of a progress tracker on the Level homescreen, to help them maintain motivation.

Lastly, in the spirit of Nudging for Good, we do very occasionally use SMS as a delivery channel for bespoke nudges.

There have been a number of behavioural science studies into the impact of SMS and they largely concluded that it’s both an inexpensive and effective channel to use given that it’s mobile and typically has open and read rates of up to 90% which is far higher than read rates for email.

Level currently uses SMS for nudging in two scenarios: either to help users avoid financial shocks such as annual or quarterly bills that are forthcoming but which they may have overlooked in their monthly budget.

Or alternatively to make suggestions in the event of a positive change in our users’ financial circumstances, such as a pay rise or the reduction of a monthly bill.

In this scenario, Level will automatically send a message suggesting that the surplus could be deployed to savings rather than absorbed into their monthly budget. This is a classic example of a BJ Fogg ‘hot trigger’ applied at a high point of motivation.