What is Anticipatory Design?
Anticipatory Design is a UX design principle that is one step ahead of the user. It uses artificial intelligence to collect data on user habits and preferences with an interface. This data is then leveraged to asses, predict and answer user needs ahead of time.
Its goal is to reduce users cognitive load by making decisions on their behalf, creating an ecosystem where decisions are never made and happen automatically without any input from the user.
Some popular use cases of this are seen with well-known brands such as Netflix (where films/TV shows are recommended to you based on your viewing habits) and Amazon (where products are suggested to you based on what you have bought previously). Spotify has also released a feature that creates a playlist for you based on past listens and preferences.
The Origin of Anticipatory Design
Technology has improved and made our lives more convenient but it has also given us access to vast amounts of information, products, entertainment etc. With this has come an abundance of choice and as a result it is said that we now make approximately 35,000 decisions a day.
Making so many choices has left us with ‘decision fatigue’, a term that means the quality of our decisions deteriorate the more we make consecutively.
Anticipatory design has been developed to help minimise this ‘fatigue’. The term was first coined in 2015 by Aaron Shapiro, CEO of Huge. He said;
‘ The next big breakthrough in design and technology will be the creation of products, services, and experiences that eliminate the needless choices from our lives and make ones on our behalf, freeing us up for the ones we really care about: Anticipatory design’.
Although this term has appeared more recently the overall concept is not new. An early example of this concept is Microsoft Office’s ‘Clippy’. Clippy would offer help based on what it detected the user was doing within a document. However, Clippys’ intelligence and features were limited by the technology available at the time.
Other, simpler examples that were seen in everyday activities included storing contacts in early versions of email services so that users would not have to re-type email addresses, saving people time.
What is different about current Anticipatory Design is that it is smarter and has been advanced by the improvement in technologies such as machine learning and artificial intelligence. These technologies allow products and services using anticipatory design to more accurately pick up on user habits over time and construct algorithms to deliver recommendations and make decisions.
Real World Examples of Anticipatory Design
E-commerce: Cook With M&S
This app provides users with a range of recipes (alongside beautiful photography and compelling copy), the app adds value by allowing visitors not only to read the recipe, but also create an editable shopping list of ingredients to purchase from their shop, which adjusts automatically according to how many people you are serving.
Home Technology : Nest
Online : Google Now
Google Now is an intelligent personal assistant developed by Google. It collects user data and it can display cards with personalized, location-aware information, such as calendar events, local weather, news, stock prices, flights, boarding passes, hotel’s, photo spots nearby, and more. It can also tell the user how long it will take you to get home from work, based on current traffic conditions. If Google doesn’t think you need something at the moment, it won’t be displayed.
The Benefits of Anticipatory Design
- Reduces Cognitive Load – Cognitive load is the mental effort needed by a user to do something. Anticipatory design decreases this effort by reducing or in some cases eliminating the number of decisions the user has to make. The less users have to think about what they need to do to achieve their goal, the more likely it is they will want to achieve it.
- Simplified User Interfaces – Fewer choices available on screen means that interfaces can be designed to be, cleaner with less clutter. This should make online user experiences more intuitive.
- Time Saving – Anticipatory Design ensures that users can find what they need or make decisions faster, saving them time and allowing them to do more.
- Increase Conversions – Personalized product recommendations on e-commerce sites provide opportunities for sales and in turn create more revenue for organisations
Potential Problems with Anticipatory Design
- Privacy – The biggest ethical concern surrounding anticipatory design is over data security and privacy. This is due to the fact that a lot of very personal data (e.g. online profiles, messaging and location) is required from users and access to this data may concern some users. User data should be protected and not used in an invasive manner.
- Restrictions – Algorithms can create a loop of events, actions and activities that can trap users and limit them from discovering new experiences. This has been termed the ‘Experience Bubble’. This can be more of a concern with children who are more easily persuaded.
- Loss of Control – Users have less control over what they see. Some users may not want this and so being transparent and providing users with the option to opt out of pre-made decisions may be necessary in some cases.
- Bad Decisions – Human actions are not always predictable. Making a wrong decision for the user can negatively impact user experience which can impact an organisations reputation.
Designing Anticipatory Experiences
Implementing anticipatory design into your product or service requires a combination of machine learning ,data collection and good user experience design.
The advice from Aaron Shapiro, CEO at digital agency Huge and the creator of the term anticipatory design consists of 5 things he feels organisations should keep in mind when thinking about designing anticipated experiences;
- Think of your brand as a service: What does it enable its users to do?
- Enable your service digitally
- Assess what you can do to automate the delivery of your service.
- Establish your automated service
- Draw a line between what is acceptable decision making and what isn’t.
Once your anticipatory service has been created the following advice can help to optimise your offering.
- Look to add value to an interaction through automation
- The context of where automation is offered is key, not just the content
- Putting in place a contingency when wrong decisions are made can minimise the loss to you and your consumers.
- Give users some control over what they want to see, implement a feedback mechanism to gain user opinions.
- Work to establish trust with your users. The users should feel as though they are benefiting from giving away their personal data.
- Continuously analyse and asses the data collected to help to minimise errors.
- Carry out user research and testing. Observe what users are inclined to do along the user journey and design the interactions accordingly. Combining this with data mining creates fluid anticipatory experiences.
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Anticipatory Design & the Future of the UX Industry
Anticipatory Design is a design pattern within the field of predicative user experiences. It is formed around 3 elements;
- Machine Learning – allows devices to learn from users past behaviours and use it to adjust anticipate on.
- The Internet of things (IoT) – the means of and the context in which anticipatory design operates and is executed in.
- User Experience Design – is crucial to deliver seamless anticipating experiences
The development of these new and smarter technologies means that the skills required of UX designers is changing. Anticipatory design is resulting in UX designers getting more involved in areas such as ethical design since a lot of personal data is involved in predictive experiences.
Other forms of user interfaces (e.g. voice interfaces such as Googles’ Alexa) have presented different ways of designing thinking based around personas and conversation design.
A step further from this is being developed in the form of gesture based interactions, requiring even more effortless user inputs.
Google is currently working on a project called ‘Soli’ ; a new sensing technology that uses miniature radar to detect touchless gesture interactions. This would provide the opportunity for anticipation to be transferred by gestures and the technology has many application opportunities once the UX industry embraces gesture controls. Everything, from phones heavy machinery can integrate this technology to anticipate user’s intentions and react effectively.
It is clear that we are moving towards a future with more smart operating systems and anticipated experiences. Prediction will most definitely drive the future of users interaction with digital systems.