A couple of years ago, a very hot topic in the web design world was “Mobile First”. Luke Wroblewski originally conceived the term in 2009 as he witnessed an extreme increase in mobile web traffic, and anticipated that mobile traffic would surpass desktop web traffic in the upcoming years. His idea was to design websites for mobile phones first, and afterwards adapt them to desktop screen sizes. This was a huge change from the previous decade of web design, where websites were designed and built only for desktop screens, which resulted in poor user experience when viewed on a mobile phone screen.
In the following years, tablets were introduced, adding new screen sizes to the mix of where a website could be displayed. With the introduction of Media Queries in CSS3, the Mobile First approach changed into the concept of Responsive Web Design, where the design and the layout changes fluidly and responsively to fit any screen or device.
However, just responding to screen sizes is no longer enough. Not all users need the same content all the time on all platforms and devices. They are on a journey composed of a sequence of interactions that span channels and devices, contexts and locations, and they expect every interaction to be easy, relevant, timely and tailored to their needs.
At the same time, we can see that Luke Wroblewski’s predictions might be right: Over the last 12 months mobile usage has increased 60%, tablet usage has increased 50%, and desktop usage has decreased 20%. If this trend continues, mobile and tablet usage will surpass desktop usage within the next 12 months.
Adaptive digital solutions
All this tells us that we need to create digital solutions that can respond to the user’s context and to where he is in his journey, and thereby add value to his experience. With the increased usage of mobile and tablet devices, we can leverage contextual information gathered from sensors and our previous history with the user. We can create adaptive digital solutions that can adapt to a user’s needs and goals in different situations and contexts, on different devices.
Let me give you 4 examples of adaptive solutions:
Large department store / IKEA
I am at home, browsing the online IKEA product catalog for a new desk for my daughter and dwell on a couple of offers as well.
The upcoming Saturday, I go to IKEA to buy the desk. When I enter the store, proximity sensors trigger a welcoming message:
Welcome to IKEA, would you like assistance?
I press yes, and the app now switches to a virtual shopping assistant mode:
- Get a map of the store
- Get directions to your recently browsed products
- Find a specific product
- Explore mode: Get offers and recommendations as you walk around
I choose the second option, and the app shows me a list of the products I was looking at the other day. I click on the desk I was looking for and get directions to the room setting where it is on display.
In the kids area, I see a different room setting with a different desk and open the app. Proximity sensors can tell the app which setting I’m looking at, and give me quick access to extended product information as well as the option of adding products to my pick-up list.
In the pick-up area, the app will go in pick-up mode, guiding me to pick up the products on my list, starting with the biggest items to make packing the trolley easier.
When I arrive at the counter, the app can give me quick access to my bonus card, payment, home delivery and trailer rental information.
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I’m sitting at home in the evening opening the airport app on my tablet. The GPS can tell that I am not near the airport, so the app stays in default mode. On the tablet, I check in to a flight scheduled for the next morning followed by random browsing for whisky in the duty-free store.
When I arrive at the airport the next day, proximity sensors will trigger information on my phone about my flight:
“Dear Mr. Jacobi, you have plenty of time to catch your plane to Paris. It will leave from gate A20 at 9:55, and security will only take a couple of minutes”
If I check my phone near the duty free store, proximity sensors will tell the app where I am, and the app can give me valuable information about my flight and a teaser based on my behavior the previous day:
“Still 15 minutes before you need to walk to gate A20. Do you want to check out our current offers on whisky in duty-free?”
If the gate is changed, the airport can push a notification to the app, including estimated walking time to the new gate and a map indicating how I get there, based on my current location.
It is morning and I am at home and just opened the app. The app knows that I am at my house based on GPS history or address book access. Normally, I commute to work, so the app shows a status of the bus and train lines I normally use. I choose to make a route plan to an address in a different city, and buy my ticket for the fare.
When I open the app on the train, the app can tell from WIFI and GPS that I am actually in the train that I bought the ticket for, and it then displays status information about the fare, that it is on schedule and when I will arrive at my destination.
Then the train breaks down, and can’t go any further. The railway company can now push information to my app about the breakdown and help me with alternative means of transportation:
- If you take the next train, you will be 30 minutes late.
- If you walk 10 minutes to the bus stop, you can take a bus and get to your destination 20 minutes late. This is the direction to the bus stop.
- If you take a taxi, you can be at your destination 5 minutes before original arrival time. This is the number for the local taxi service.
- Here you can read about our compensation rules.
A new approach to customer centricity
All of these examples use off-the-shelf standard products and technology and, from a technical standpoint, are already applicable tomorrow. But to ensure that we build successful solutions, we need to understand our customers completely.
Traditionally, we have used personas for designing user experience. We would take the entire target audience, split it up in segments, and, based on research, we would create a fictional character for each segment, describe their behavior patterns, goals, skills, attitudes, environment and fictional personal details. This would be the foundation of our customer-centric approach to user experience.
But classic personas represent just a point in time for each persona. In order to design adaptive solutions, we need more than that. We need a solid understanding of the entire customer journey for each persona: their needs, pains and actions on each step of their journey. And how we can help them, interact with them, and adapt our digital presence to suit their needs in the best possible way.
By creating customer journey maps for our personas, based on input from empirical data, we can identify opportunities where we can relieve anxiety, anticipate needs, or surprise expectations. Customer journey maps give us the new foundation for customer centricity, and enable us to create magic moments, when we give the user a better experience than they expected.
The insights and data we can harvest from these types of solutions are not only useful for the digital channel. They can also be used on a more holistic level to create better customer experience across all channels and through the entire customer life cycle, and perhaps even to create better products. But the sword is double edged: with all the data we can harvest and all the detailed information we can get about individual customers, there lies a great responsibility not to misuse this data and to protect the privacy of the customers. But that is another story and shall be told another time.