A thought exercise on how to measure what matters in design work.

Today, we are designing the future for humans. However, we are taking for granted what “human” means.

We think we are first designing the future, and then understanding how it affects what it is to be human.


A more accurate description can put the design role in its proper place: we must design what humans will be, and as a consequence, affect the future. 

Following the arguments of evolutionary psychologists (...)  the "holistic nature of human experience" (245) (...) is manifested in emotions or "feelings," which, she argues, "are how the body communicates to the mind information about its structures and continuously varying states" (245). Indeed, she goes further, following Antonio Damasio, in arguing that the "'basic topic'" of representations in the mind are those of "'an organism anchored in the body'" and that therefore "[h]uman mind without human body is not human mind" (246). Hayles, Kathyn. How we became posthuman.

From all our interactions with the world, a great deal of what makes us humans is how we relate to one another. That’s where technology performs a huge, subterraneous, almost invisible part: technology is usually the seamless mediator and computer of our relations and, consequently, the data streams we produce and consume. One subset of this data is "a user". Another subset of this data, when financial transactions are involved is "a customer".


The point is, all our technologically mediated relations are data. Our task, as designers, is to manage how all these data streams flow.  The designer manages how the digitally computed data flows with the organically computed data (our human perception, emotions and non-mediated relationships).






the state of being numerous.

"they would swarm over the river in their multitude"

In the worst case scenario, it gives a peephole on how your subjects search — a great starting point for an interview.


Designers have an essential contact with real people. That may have an adverse effect: creating solutions for real people who, in the end, will not represent a significant market.

The solution for that is simple: look into databases before deep diving into your most strategic segment.

How would you cluster customer segments? What are the demographics of the three most significant customer profiles? What are the observable patterns in their behaviours? What is their average Lifetime Value? What can machine learning help you to understand?

Design is a strategic partner. So it should look into business numbers as often as possible.

Harvest the power of data multitudes. 

How 100,000 people search for a topic will give you strong insight abou its relevance.


The computational power of a small coffee house is higher than a factory built in the year 2000. Small businesses can measure who visited their webshop, who subscribed to their news, who showed up at the store, who bought the lighter blend of coffee, how frequently, for how long etc.


With the appropriate consent, companies may know more, deeper, and in a connected and predictive way. But companies do not need to be in a state-of-art analytics to make better, more informed design decisions. The biggest answers lie on the surface. Scratching the surface of user data is all it takes.

That is also because data should inspire design decisions, not constrict them. The sooner we have an insight, the sooner we may leave the Analytics dashboard and start designing.

That is the cornerstone of data humanism promoted by Georgia Lupi.

This also means that designers need to be truly creative to start measuring what discloses meaning. Often, what discloses meaning is subjective and hard to measure. And hence, it takes creativity to create proxy metrics to get  close enough of the experience your customers look for.

Relevance comes from madness, precision comes from method.

 (It's better to be relevant

Sean Ellis has developed a proxy score for traction in the Silicon Valley. It consists on asking how disappointed would you be if we no longer provide this service? It's simple, subjective, emotional — and it seems to work. His practice shows that when the score goes above 40%, companies may find product-market fit. 

Marie Kondo has discovered that the spark of joy is a very helpful metric to define "what people want to bring with them into the future". These very simple metric has helped millions of people around the world to stick with what matters.

Similarly, in 2003, Fred Reicheld introduced the world to the NPS score in an article at Forbes magazine, a score to the answer How likely are you to recommend us? It's been over 15 years, and now people may recommend anything on social media. Yet, time has attributed meaning to the NPS score. What other scores are bound to happen?

A personal case, now. Once, a client wanted to ask customers if they are happy with their delivered goods. My suggestion: let's add a hashtag to the boxes to instruct how they can express satisfaction when the event happens. Probably we would be listening to a sample of the total reactions — nonetheless, we would be able to listen, watch, follow up and know a lot more than if we just run surveys from time to time.

When you turn such meaningful metrics in indexes or scores, things start to get interesting. What is the "joy score" of your brand? What is the trust level of your sales people? What is the indicator that tells 

Here's the ABC to identify the core experience your customers get.

 1. Start from your known optimal state. 

Start to examine the data you have when you have already completed your goal. Look into your conversion funnel from the end. Take a deep dive in the dimensions contained on that step of the journey. 


a. Coffee shop example: Conversion — you have sold a cup of coffee with your app. 


 2. Identify the very best behaviours within your database 

You are researching the conversion step. Now, generate segments of customers. Select the ones that display best behaviours: they spend more, they come over more frequently, they stick with you. They inhabit your Retention Metric.

b. Coffee connoisseurs that own their own espresso machines. They buy cups of coffee and coffee beans.
Their frequency averages 3x per week, their expenditure is over €30/mo.

Only the core experience survive disruption ❤︎

Design has​ a task: to rise up to the strategy table, and to stay there, calling strategic decisions. The "heart of the matter" is one way of ensuring that.

Quantifying your core experience is a hard job. But it's worth it. It becomes your North Star Metric. It informs design about how to get what any business cares about: growth. All other metrics grow if this one does. 

Customer/User Experience can be measured. And it should be measured. To see how this can be achieved, we need to first dissect what an experience is, and for whom.

This is a quick guide on how to start thinking and doing it.

 3. Get qualitative data on the very best segment: why do they keep coming? 


Now is the time to get all the qualitative, ethnographic and soft power to understand these customers. They are not segmented by demographics only, they are segmented by past behaviour.

You will investigate the main reason your experience is rewarding, the motive your customers keep coming to buy from you, not from anyone else.

c. "It has great brands, the price is reasonable and the baristas know how to prepare espressos".​


 4. Find the proxy metric that is closest to the experience your best customers get. 


This is it. It's time to convert the very core experience of your core customers into metrics. Usually, a few variables get combined to compose the North Metric. When this metric is on the right level, there will always be long lasting, sustainable revenue. 

d. Score of offered beans in is higher than 3.5; barista training grade 4+ higher.
Prices averaging 20% higher than laggards. ​


What happens if we increase the brand selection?

What happens if we vary the price?

We are tapping into the gold segment — a new acquired customer is way more valuable than one-time buyers.

While the offered example is rather simple, the structure can stretch to very complex businesses situations that need to be transformed by design.



Past behaviour is the best predictor of future behaviour. Discover existing problems by surveying and consulting with various data sources. 



Individuals, segments, multitudes — the answer to problems is a safer bet when validated by statistically relevant data. 


Once you know who you will design for, and the problems you need to solve, test without asking. 


You will get live signals from the market to validate your value proposition, and indicators of business return on investment.

Throw a bait, see who bites, deep dive.

We never design the future, we design humans — one experiment at a time.

Understanding who you are designing for is the base for understanding how to generate cost-effective experiments to move ideas forward.



If it*s accepted without evidence, it*s dismissed without evidence.


C. Hitchins

Great ideas are a bit wild, and that's the great side of them. But after a while, they need to start to yield results.


A bad aspect of a 'wild idea' is not to be able to know if it failed. But a worst aspect is not knowing if it succeeded.

Reversing your ideas into formal hypotheses is a great leap towards a manageable, accountable design project — one that will "pay its rent" on the customer side and prove that every hour invested resulted in XYZ increase, improvement or revenue.


The main point of a hypothesis is its if/then structure. This structure is able to establish causalities.

Causality in design is not a straight line. You need to be creative, and start seeing data as approximations, rather than precision. You will need to create attributions and (as seen on the Convergence chapter), Key Performance Indicators (the numbers that tell you are failing or succeeding).


 THIS ACTION  is implemented,
then we believe 


We think this is a good idea because of 

We will measure the experiment with  THESE METRICS KPIs .

​Sérgio Tavares, ph.D. ✖ 2019

Connect with me on LinkedIn!
Work opportunities, news and all things Design/Culture/Technology.