NANDINI NAYAK: Design is creative-centric, but with sensors and big data a lot more information about the consumer is becoming available. And design may not be exploiting the full power of the insights that reside there. More and more, we are beginning to see that we can know more about the context of the target consumer we’re designing for by looking at what insights we can gather from data. With the Internet of Things, we are beginning to design specifically targeted interfaces that actually visualize data in a very consumer-centric way.
Is there a workable marriage between programmatic and creative?
If you look at any type of user experience, that experience is usually designed with a specific customer goal in mind. Lets say I want to buy some milk. In order to do that online I have to go through several steps. Or I can walk into a store. But if someone intends to buy milk, and they have that same intent every week at the same time, why bother going through an interface? We can predict that intent and, like magic, milk shows up.
So how can programmatic begin to enter those experiences? Designers can start to think about what aspect of an experience, based on data that we have, can be completely automated or removed so that the magic of having what you want when you want it happens.
At the same time, however, you want to make sure that process is done in an elegant way. As big data, programmatic and predictive models enter the design space, you begin to think about what aspects of the experience can be simplified because machines can do it and what aspects the human touch actually makes possible.
Is this all theoretical, or is it happening now?
It is in its infancy and at the beginning stages of integration, but it is not theoretical. What’s standing in the way of programmatic and creativity working together is that typically, in client organizations, the analytic program aspects and design aspects are not working as closely together as they should. Clients are just beginning to think about taking advantage of the data they possess and are looking for strategic design thinking to pave the way to new service innovation.
As this need becomes more common, data and design disciplines will begin to work more closely together. We will see an emergence of capabilities that are creative as well as analytically driven. The design of data-centric products such as smartwatches and Fitbits are early examples of how data becomes a lot closer to design. As the ecosystem of the Internet of Things evolves, we will naturally begin to see a closer connection between these two disciplines.
How does data flow between Fjord and Accenture Interactive?
Fjord and Accenture Interactive collaborate 90% of the time in finding solutions for clients. There are two ways that client engagements can emerge. One is where Accenture client account leads identify a customer experience opportunity that is adjacent to work that we are already doing for the client, and bring in Accenture Interactive and Fjord. In that case, if it’s primarily strategic design, Fjord will take the front seat. If there’s an involvement of marketing services, analytics or technology, we will bring in Accenture Interactive.
Second, if there is a service design opportunity originated by Fjord, Fjord leads the opportunity and the broader Accenture Interactive and Accenture team will solve any adjacent services required by the client, depending on what is needed. Fjord provides the design service strategy element and follows up with the appropriate design realization capability that comes from the broader Accenture and Accenture Interactive teams.
What’s trending in the world of creative design?
A rise in the variation of experiences we can deliver based on the variation in context, devices or location. We talk about this thing called fluid expectations. A customer’s need is never set, and it changes consistently based on the context they’re in, their location or big life changes.
Design has to be flexible enough to be able to adjust to those variables. Structurally, design cannot be one size fits all. Once a designer has created a design pattern, he or she has to break it up to figure out which parts of that design fit with different individuals or different audience segments. And anticipating variations that require a different type of design approach of that modularity allows designers to assemble experiences based on the signals they receive from data.
Does that type of segmentation happen device to device?
In general, the whole idea behind big data and design is that designers have to think about the message they want to send. Not only does design have to respond to data, it has to also be able to listen to data. In that sense it has to listen to which device an end user is on. There’s something called responsive design that’s really an automated way of designing for one device. It helps designers generate experiences automatically on certain devices.
But that doesn’t take into account the adaptive work you have to do, because not all experiences can be done on a smartphone or in a small banner. Beginning to think about what the device of choice is for a specific touch point or within a specific context is really important.
Can content creation based on geolocation happen in real time?
It’s already happening in real time and there are two parts to that process. First, there’s creating the strategic framework for a design and making it modular. Then, we’re beginning to see what we call creative production. In order to fill the experience on a one-to-one basis for a particular consumer within a segment, somebody who is at a specific locale with a phone in their hand, we have to be able to create millions of different variations that address the specific context.
Is that type of targeting happening programmatically?
Content production based on specific locale is expanding, as is scale across different channels in different locations. You create a framework for any particular unit, and you’re trapping information that says if a user is in a particular locale and has visited X, Y or Z store, the type and the length of content can be adjusted based on what you know about that consumer. You create four or five pieces within the framework, and the system might automate the combination of those elements that are required for a specific context. It’s what programmatic is all about.
Even if you layer out the headline, what the actual copy may be and what type of specific medium of content is reflected, delivery can be programmatically rendered. There are systems that are beginning to be used to do that. And this will be where personalization becomes programmatic, because humans cannot handle the level of variations that are required.