Scalability of caring for users

Back when I was working at WeChat, something happened in our work group:

A former colleague’s child ate some problematic food bought from an e-commerce platform and had to be sent to the hospital.

Fortunately, with the help of a friend in the group who worked in e-commerce, the issue was quickly resolved:

• The merchant selling substandard products was penalized
• The e-commerce company’s Guangzhou team personally visited the family
• The child fully recovered

Of course, the first two measures wouldn’t be very feasible in today’s downturn in consumer spending. After all, eating something from P Dada doesn’t necessarily kill you, right?

Another colleague in the group said: It’s not the product that matters in e-commerce, but the operations.

This view, however, is rather biased.

Today, because the child’s father was a former WeChat employee, the issue was quickly and properly handled. But what happens tomorrow if another customer’s child shows symptoms?

Such user care is not truly scalable¹.

Schelling, in Choice and Consequence, discussed the distinction between “identified lives” and “statistical lives”:

Identified lives: A six-year-old girl with brown hair needs a few thousand dollars for a surgery that will let her live until Christmas. The community post office overflows with coins and small bills as people donate to save her.

Statistical lives: A news report says that after the sales tax is repealed, hospitals in Massachusetts will not be updated on time, leading to a slight increase in preventable deaths. Few people shed tears over this news, let alone donate money.

In this case, the e-commerce company cared for an “identified life.” But on its reports, there are three hundred million “statistical lives” who also need — and are more deserving of — care.

Being able to portray users at scale, understand their emotions, catch their complaints, and set rules in a way that accounts for these seemingly faceless, identity-less, genderless, preference-less individuals — that is far more meaningful for scaling, and prevents such incidents from happening in the first place.

The Posture of Caring for Users

There are different ways of caring.

Few people are willing to spend time thinking about how to truly understand and care for their users.

Compared with long-term product building, people would rather rely on purely numerical indicators like ROI, GMV, or DAU to measure product and business success.

While data indicators do abstract and summarize reality, they inevitably lose information.

Statistical users may not show faces, but that doesn’t mean they don’t have them. Only by seeing the faces behind the numbers can we create real customer value.

If we return to business and say “marketing is king,” then let’s revisit what the father of modern marketing, Philip Kotler, has said:

Marketing is not the art of finding clever ways to dispose of what you make. Marketing is the art of creating genuine customer value.

A product design that shows care for statistical users may seem to lack operational flair, but in fact, it reflects the deepest understanding of operations — doing the right thing at the source.

Because if I were that father, I’d much rather my child never go to the hospital at all than have twelve strangers come to visit her.