In 2015, Aaron Shapiro (CEO of Huge) coined the phrase “anticipatory design” to describe how the next big evolution in design and technology will be the creation of predictive, proactive multi-channel user experiences. It’s the perfect marriage of design, data and technology to simplify complex decisions and, in some instances, even eliminate some tasks and decisions from our lives entirely.
The word anticipatory comes from the Latin anticipare, which means “taking care of ahead of time”. Think of it as personalisation 2.0 – a system that interprets users’ past behaviours and choices in order to automatically make informed decisions on the user’s behalf, by utilising machine learning algorithms.
In the future, the design around us will sweat the small stuff — Aaron Shapiro
The easiest way to think of anticipatory design is a service or user interface that’s always one step ahead of you in removing unnecessary effort or decisions. Consider the app by online grocer Peapod which uses a recommendation engine to fill your cart with just a few clicks based on what you’ve ordered in the past. Or your internet-linked printer that will automatically order new ink cartridges before you run out. Similarly, the Nest learning thermostat will automatically adjust room temperature based on the owner’s historical preferences, time of day, etc., and even adjust the temperature accordingly when it knows they’re away from home.
Perhaps one of the most sophisticated examples of a fully autonomous anticipatory design is Google Now, whose sole premise is to predict what you need to know before you realise that you want it. It knows who you are, your habits, your location, and can pull in third party data accordingly based on your anticipated intent and behaviours. Time to leave work? Or dinner reservation booked in your calendar? No problem, Google Now has you covered and can suggest the best route based on current traffic conditions.
The tyranny of choice
The goal of anticipatory design isn’t to turn us into unthinking automatons, however. Instead, the service model of anticipatory design is to use data, prior behaviours and business logic to minimise superfluous actions on our behalf, by making them happen automatically. We live in an increasingly complex and noisy world. Shapiro notes that, “Technology has made our lives more convenient, but it has also subjected us to the tyranny of choice” and near constant distractions.
Every day, we face tens of thousands of decisions, all of which place a load on our working memory. Each choice takes genuine effort and leads to the phenomenon of decision fatigue, whereby the more things we’re forced to decide upon over the course of a day, the progressively worse our ability to make effective decisions becomes. By removing some of this cognitive load, anticipatory design presents the opportunity to not just save us time to focus on the things that are genuinely important to us, but moreover to help us make better decisions.
Financial service examples
How can financial products lighten the load for customers to make more room for the decisions that really do matter? One market that’s making good steps in this direction is savings fintechs, and here at 11:FS we find ourselves endlessly impressed by companies such as Plum and Digit, both of whom are utilising learnings from behavioural economics and anticipatory design to feed a market of customers looking for smart solutions for saving money.
Plum’s Facebook chatbot allows its customers to shape discussions about their savings or investments based on their mood, and take over from there, making simple decisions for the customer, yet still allowing them the power of veto. They’re going beyond this, though, offering a range of other services, such as making the switch to more affordable energy providers simple. This is something fellow fintech disrupter Flipper is already doing; it automatically and effortlessly switches customers onto the best energy deals available.
Digit connects to users’ bank accounts and assesses their financial habits, along with data about their income and expenditure, to make intelligent choices about how much they should be saving each month. It then automatically takes this ‘safe’ amount and moves it into a savings account. Digit doesn’t completely remove all decision-making, however, as users are able to adjust its saving aggressiveness.
This is just the beginning of this new anticipatory process, and we would expect that the future will yield further fruit as we race towards ‘marketplace banking‘ – like that recently unveiled by awesome challenger Starling Bank.
Banks need to be able to offer their customers a service that makes investment decisions on their behalf, one that moves a customer’s money around for them based on their habits and appetite, and offers access to third party service providers. Anticipatory design should allow banks to reduce the amount of decisions their customers have to make, while providing simpler, albeit more proactive and useful user experiences.
AUTHORS: Tom Evans is UX director at 11:FS, and James Safford is a market research consultant. To find out more about 11:FS, visit the website.
– This article is reproduced with kind permission. Some minor changes may have been made to the text to reflect BankNXT style considerations. See more 11FS content here. Image by Peshkova, Shutterstock.com