In recent years, data on people are becoming increasingly accessible, and important to organizations. When data collection came on the scene, it left a lot of people excited about the amount of information that could be gained, and the potential to leverage business growth.
But what can we actually do with these data? How can they be used? And, mainly, what do they mean? We see much concern in just collecting and storing all this data on a great mountain – just as Smaug did with the dwarfs’ gold at Erabor – even without an answer to those questions.
I confess that I am excited to realize that the market seems to be maturing and moving away from the phase where these questions were irrelevant and going to a level where they are experienced and discussed, and to find ways to take advantage of this information to bring consistent return.
We are going beyond macro view, and entering a layer where this data becomes increasingly segmented and personal. Large service companies have begun to develop complex and intelligent systems for content recommendation and evolving experience, such as Netflix, 3M, Disney and Spotify.
Netflix, for example, conducts research, tests, and analyzes metrics to improve not only the user experience but also the product positioning itself. An example of this is in the evolution of the company’s business model, going beyond streaming and starting to produce its own content, based on data and preferences of its consumer, as was the case of the great success of “House of Cards”. They can, for example, identify in which episode the person actually engaged with the watched content.
To understand how we can use all these questions as a way of delivering solutions and experiences that are more coherent and able to keep up with people’s needs, it is important to first understand the importance of the data, and how this access to relevant information impacts our discipline.
Data, behavior and context
“When I look at these same numbers, I see patterns of behavior, needs, and motivations.” – Arianna McClain
More relevant than knowing when and where to impact people is the opportunity to begin to understand better their need and how they behave in a given context.
Clayton Christense, a professor of business at Harvard, acknowledged for his study of innovation within large corporations in one of his videos for the University of Phoenix, speaks of a situation where numbers indicated that launching a new product would be a success, But after the release it proved to be a failure. Intrigued, he and his team had to go to the store to observe people’s behavior and understand the context in which they bought the particular product, and how that was impacting the customers’ journey.
Looking at the metrics without purpose does not allow us to see what they really mean. In our universe, when strategically thought out, these metrics can help us understand people’s behavior. The needs and expectations of people in a given context has always been the focus of our discipline, supported by two characteristics that are the basis of a UX professional: empathy and questioning.
Empathy helps us to understand the needs, feelings, context of use and expectations of people who relate to our product or service. The questioning, the basis of any discipline related to design, makes us able to go beyond the briefings and goals of the organization, which often end up painting the true scenario.
The search for understanding through observation and monitoring of results were methods that structure the way we work today. The monitoring and analysis of data allows us to think of reactive solutions that can evolve in stages, taking into account data that allow the identification of patterns and are contextualized.
Max Mckeown, author of the book “Strategy from Planning to Execution,” states that the world is more complex than our ability to plan, and so responding to events it’s as important as planning. He further states that our visions about the future are incomplete and that we are subject to small, medium and even major events that challenge the initial proposal but that bring opportunities to do an even better job. And these statements fit perfectly into the product / UX view. As much as we conduct tests, follow-ups and interviews, people’s needs and expectations are susceptible to change.
Clayton Christense argues in “The Innovation Dilemma,” that many organizations use all the resources and involve multiple sectors to launch new products, but they do not know what to take next.
The analysis of data for monitoring and evolution of products leads UX to a new stage. Now it is possible to observe and understand patterns in different parts of the process, being able to establish a reactive experience according to the responses and needs of the people in a contextualized way, and providing information for the constitution of new hypotheses in the development of new solutions, steps and processes.
Big Data and UX
There are many reasons why organizations do not think before planning / design, and the most common are lack of time or difficulty in justifying the investment needed to develop a consistent experience.
In such situations, when the result is positive, the lack of method or planning is exalted as a great knowledge about the business or about its consumer public. But when the results are negative, no one can explain why, and an internal war begins where each sector justifies the decisions throwing the problem up. It is like imagining a ship leaving the shipyard without a crew or a definite route, completely drifting, with people celebrating the fact that this ship did not sink, but without knowing for sure where it goes.
The truth is that we often do not fit correctly into the strategic steps of the project. Different from what happens in other countries, where our discipline is more mature, in Brazil it is still very common to relate the UX professional to the structure or the surface of an experience, associating UX entirely with Information Architecture and Interface Design. Therefore, designing or planning without knowing the people, contexts, needs and what the solution to be delivered represents to the ecosystem of the organization, unfortunately, is still a reality.
Toi Valentine, in his talk “The Death of Creativity” for Adaptive Path, says that our generation has forgotten the importance of observing and researching, and that we care much more about execution and rapid responses, leaving aside research, testing And accompaniments. At the end of the talk, she proposes a balance between execution and research, uniting the best of both generations.
Data-driven decision making is critical to begin positioning ourselves as strategic professionals within organizations. In addition to creating value experiences, we need to know how to justify the investment of time and resources to achieve the necessary goals.
How to use data in our favor: Bottom-up-Bottom
John Steel states in his book “The Art of Planning” that research development is essential to communicate with people, but that it also carries a great deal of responsibility for what is being said. Often poorly developed research can have negative impacts on the organization.
Rochelle King, product designer at Spotify, warns in his TED Talk “The complex relationship between data and design,” that the more we delve into the data, the more likely we get lost among the numbers and forget that they represent actions of real people in a real world.
To deliver consistent solutions that enable a scalable development, capable of anticipating and dealing with improvements and needs not previously predicted, it is imperative to go beyond monitoring data question intelligently: what do I want to know? Why do I need this data? Which scenarios do I want to validate? What do I need to keep up with for my future decisions? What do these data tell me about behavior? Can they be validated / compared to other information?
These questions can and should happen at distinct stages of a project, so that’s why it’s interesting to bring Jesse James Garret’s Bottom-up Method with an additional layer of over-the-top surface data that can feed the strategic foundation.
The UX team from 3M’s health solutions area, for example, brings all the data available for validation of qualitative methods (surveys, maps and interviews) still in the strategic base, that is, at the beginning of the project, where the Strategic basis is being formed, and will eventually direct the other stages of development.Here are some rather longer stages of research and hypothesis-gathering. The macro questions are “where are you?” And “where do you want to go?”
- Who are the people who consume your product or service? (People)
- How is your organization’s market?
- What are the specifics of the niche?
- What are the opportunities?
- What are the points of attention?
- How is your organization’s ecosystem impacted?
- What have your competitors done?
- What other companies from different segments have done?
- What are the objectives of the project?
During project development, the definition of KPIs (Key Performance Indicator) is essential to determine if a project is going well or poorly. What do I need to keep track of and which tools do I use?
- What are the objectives of the project?
- What can be mapped at each of the contact points?
- What will I follow?
- What needs to be improved?
Tracking of Pending Issues
Monitoring and analyzing metrics gives us the opportunity to be reactive, that is, to change the direction of product strategy, transforming problems into opportunities, and offering a contextual experience with people’s needs and expectations.
- Are your goals being met?
- What are the opportunities?
- What are the points of attention?
- What are the insights?
- What patterns have been identified?
- How can you evolve the solution?
The use of data in products should be seen as a tool to evidence behaviors, because a project does not end after its launch, and having smart metrics is essential to plan, improve and evolve your product or service constantly with the organization’s goals.
But this should not be understood as the solution to all problems. Christenses has a speech that makes a lot of sense in the context of this subject, stating that data are based on past actions, and so they do not provide us with clarity of what to do, and we need to get consistent hypotheses built from a way of thinking, and Which it is interesting to seek the understanding of planning and strategy concepts.
The relationship between the data and UX has positively impacted our discipline. Despite the overload of functions and knowledge, it is enabling the formation of professionals who can base and execute their actions with agility, evolving their products and services with contextualized needs.
Some good points we can take advantage of:
- Involve the UX team in strategic steps of the project;
- To provide justification for projects and investments;
- Enable the development of scalable solutions;
- To enable the reactive monitoring of products and projects;
- Increase understanding about patterns of behavior, people and context;
- Give more visibility to impacts on business-related chains;
- Allow for resolution of events before they become problems;
- Facilitate team engagement and participation;
- Transform hypotheses into decisions.
If you want to delve into this subject, I leave below some references of study and research. Good reading:
- Estratégia, do planejamento à execução (Max Mckeown)
- A arte do planejamento (John Stel)
- O Dilema da Inovação ( Clayton Christensen)
- What Chicken Nuggets Taught Me About Using Data to Design (Arianna McClain)
- A Netflix sabe exatamente qual episódio de cada série fisgou o público
- How To Design With Discipline: UX Lessons From 3M
- Understanding the Job
- The complex relationship between data and design in ux
- The death of curiosity