How to Create Spectacular Consumer Experience Through Predictive Design

For some reason, the song “This Magic Moment” by The Drifters sprang into my brain this morning.

Our brains are characterised by their restless neuronal networks, which have the ability to connect ideas and concepts that, at first glance, appear to be entirely unrelated. This phenomenon can lead to the emergence of peculiar occurrences.

I slapped my forehead and thought, “But, of course…”

Lately, I have been reflecting on the remarkable experiences that happen when we interact with technology. It is remarkable how, when the timing and circumstances are just right, it can feel like a kind of magic. Whether it is through a banking service, car, vending machine, or mobile phone, these moments of perfect synchronisation create a truly memorable user experience.

I think we have reached, if not already entered, the age of anticipatory design.

With the advent of new technologies and improved input techniques, the few graphical user interfaces we currently have are undergoing a period of development. As it is now commonplace to engage in conversations with our electronic devices, this progression is both logical and natural.

For instance, when we are behind the wheel, we may request Siri to dial Anna’s phone number, set a timer, or provide information about films that are currently playing in cinemas in our vicinity. Similarly, we can ask Alexa to playback music or order coffee. Despite this, the metaphorical and visual components that were created more than 40 years ago have remained largely unaltered.

The Previous

Consider that the original Xerox PARC GUI is 44 years old, yet modern user interfaces still seem very similar to it.

In 1973, the Xerox Star workstation launched the first commercial Graphical User Interface (GUI) operating system.

Even in the present day, we continue to rely on two-dimensional displays to provide us with input, relying on keyboards and mice which were designed to complement the input needs of computers rather than the needs of people.

The technology that we use on a daily basis, such as computers, desktops, tablets, smartphones and vending machines, is often created with outdated models and technology. This means that these devices may not be as efficient or effective as they could be, and may not be able to keep up with the latest advances in technology. In order to ensure that our digital experiences are as seamless and efficient as possible, it is important to make sure that the devices we use are designed and developed with the latest technology and mental models in mind.

It appears that we are attempting to use communication models that are outdated for a technologically advanced world; these models still require a considerable amount of human involvement in order for them to progress to the next level and provide useful information.

What is predictive design?

If digital enterprises are to simplify and facilitate the course of our digital lives, the use of anticipatory design is more vital than ever before.

Consequently, what is predictive design?

It is output and requires little input. It involves using previous judgments to anticipate future ones.

In the near future, computing technology will be geared towards human-computer interaction, rather than only relying on user inputs to direct it. This will create an environment where the user’s intent is based on probability, instead of it being predetermined and specific.

Aaron Shapiro of Huge explains anticipatory design as a method for improving efficiency by predicting user needs before they are articulated. By responding to user wants before they are expressed, anticipatory design can help streamline processes and enhance user experience.

The highest level of predictive design goes well beyond personalisation.

Personalization is the practice of tailoring a product, service, or experience to an individual’s specific needs and preferences. An example of this is when Netflix recommends films to you based on your viewing habits and tastes; this is known as anticipatory design, where the interface of an application will modify itself in real time as you use it. This type of personalization allows users to have a more convenient and enjoyable experience, as the product or service is able to anticipate and respond to their needs and preferences.

Netlfix user interface customization to improve user experience.

Netflix is an example of customization. Not anticipatory construction

In the context of online shopping, anticipatory design would make the user experience feel almost like it was being personally curated. The system would be able to adjust the user interface in real-time, eliminating any irrelevant information and providing only the most pertinent choices in a speedy, straightforward and efficient manner. This would make the process of online shopping almost seem like a kind of magic, as if an unseen hand were guiding the experience.

Today, this is not very difficult to execute.

It can be hypothesised that customers who are purchasing a particularly expensive guitar on GuitarCenter.com would prefer to pick it up at a local store, as the website will automatically default to the “ship to store for pick-up” option at checkout. This is based on the website’s observation that those who have previously bought expensive guitars have opted for this option.

For another example, let’s imagine you’re purchasing a shirt on Amazon.

Amazon has already tailored a selection of items to meet your preferences based on your prior purchases of shirts from their website. This means that they should have a good understanding of your preferred shirt size and colour.

The product detail page should be optimised to pre-select the customer’s size, give priority to navy, white, and chequered shirts, reduce the prominence of pink and yellow shirts, and eliminate the need for customers to select their size each time.

What for?

The potential of anticipatory design to reduce friction and improve productivity is tremendous, with far-reaching implications for user experience and profitability. By delivering what customers want, when they want it, brands can improve customer retention and drive a positive bottom line.

As we increasingly rely on digital technology in our daily lives, we are discovering that many of these interactions are not without their difficulties and frustrations. The frequency of these conflicts can be incredibly frustrating, leading to a sense of annoyance.

Predictive design for the Amazon buying experience

Greater levels of customisation and personalisation are really required in order to please people and make their lives easier.

Consider the self-service ticketing devices for public transit, where commuters may top up their cards.

They are still made to be stupid, relying on human input and presenting each user with the same overwhelming number of alternatives.

One might readily envision a far enhanced, more individualised system in which your card could contain refill history.

It is possible to streamline the refill process for customers by introducing a system that allows them to insert the card they always use for refills. Upon insertion, the system would present a prompt asking the customer if they would like to refill the card with $20, using their Mastercard. This would eliminate the need for customers to navigate through multiple menus, as the system would immediately ask for their desired input.

Paying and leaving would be the following steps.

At least 75% less time would be required to refill cards if the process was automated, which would significantly enhance productivity, enable people to move through the process more promptly, and ultimately contribute to improved customer satisfaction.

Although it’s already conceivable, I’m not aware of a single ticketing machine that satisfies this need.

Futuristic interfaces.

A greater level of personalisation will make more predictive design possible as AI becomes more prevalent.

The system would be capable of recognising the user and predicting their subsequent action based on the analysis of their behaviour, which is monitored with their permission and includes such factors as their purchase history and preferences.

It is rather perplexing that predictive design is not more widely employed when there exist technology available today that would make it relatively easy to implement.

A few businesses currently use preliminary predictive design techniques. Uber and Google Now are two examples.

Google Now App

Google Now is one of the most groundbreaking developments from Google’s search engine. The concept is simple yet incredibly effective; it is designed to anticipate and predict a user’s needs and wants before they realise they have them, and presents the information in a convenient card-based format. This allows users to access the information they need quickly and without effort.

Google’s data mining capabilities are unparalleled. It can provide users with tailored location-based information, such as calendar events, local weather updates, news, stock prices, flight and boarding pass information, hotels, and recommended photo-taking spots. Additionally, depending on current traffic conditions, Google can estimate the time it will take for a user to commute from work to home.

Google won’t show anything that it determines you don’t need right now. It represents anticipatory design in its purest form.

Uber

Due to the high likelihood that you will desire to return to your original destination after your journey, the Uber app has been designed to offer a return option when you reactivate it following your trip. Locations for pickup and drop off are not necessary. This is an incredibly convenient feature.

The world is changing, as they say

Things are changing to more natural ways of interacting.

It won’t be long until our contribution is more naturally generated.

Augmented and virtual reality will soon be accessible through a variety of interaction techniques, including voice, gesture tracking, eye tracking and speech recognition. Google has already commenced work on a project called Soli, which seeks to make this technology widely available.

Artificial intelligence and machine learning will help anticipatory design techniques provide experiences at a whole new level.

How may predictive design be applied?

In order to provide our users with magical moments, it is essential that we explore the potential of predictive design. What strategies can we employ to create these magical experiences, now that we no longer have the convenience of a magic wand to do the work for us? By leveraging predictive design, we can begin to identify the actions necessary to ensure our users are rewarded with enchanting experiences.

Businesses have the potential to utilise their existing data to personalise customer experiences, which could potentially reduce any inconveniences or barriers encountered by customers. However, until more sophisticated predictive algorithms, artificial intelligence, and machine learning technologies have been fully developed, this remains a goal that is yet to be achieved.

They may also be actively involved in the user-centred design process, carrying out extensive research, executing multiple user tests, and leveraging technologies like Tensorflow, an open-source machine learning toolkit.

Through in-depth research such as contextual observation and ethnographic studies, we are able to gain valuable insights into how people interact with a product or service in their natural environment. By mapping out the user’s journey step-by-step, we can create a user interface that enables them to easily and effectively interact with the product and achieve their desired goals.

The ultimate outcome of incorporating data mining and customization with user-centred design approaches would be a smooth and effortless anticipatory experience that delights customers and generates loyalty by making things appear as if by magic.

By enhancing customer satisfaction, which would have a positive impact on profits, we could advance the standard of user experience and create a mutually beneficial arrangement for both businesses and customers.

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