The dreaded scale stares at you from the corner of your bathroom, daring you to face the truth. You step tentatively onto its hard plastic surface. You close your eyes tight, then open them. The big digital numbers blink at you. There’s no way to ignore the facts: Today you are heavier. Regret washes over you. You step off, the cold truth of the numbers vanishes, and your day begins. It’s off to a rough start.
According to the social scientist and entrepreneur Dan Ariely, the entire experience is a problem. He believes that the feedback about your health that a scale can give you is valuable and can help you lose weight–but the process of receiving that feedback is negative and ultimately deeply flawed. Because human weight tends to fluctuate, often due to water retention, exercise, and whether you just ate or used the bathroom, watching your weight go up and down a few pounds doesn’t say much about your health–yet the negative feedback can nevertheless be discouraging. Still, 2015 research from Cornell shows that stepping on a scale everyday can help you lose weight, so that’s not the part of the experience Ariely wanted to fix.
“Standing on the scale is like a little ritual,” he says. “You step on the scale and you say, you want to be healthy.” Instead, he figured, “Let’s separate the scale from the feedback.”
So Ariely created the Shapa, a smart scale that doesn’t tell you how much you weigh at all. Instead, it places you on a weight loss spectrum. It can indicate that you’re gaining weight or losing weight, but mostly it indicates that you’re doing just fine–a middle option that takes into account those weight fluctuations that don’t mean anything about your overall health. Its design is odds with much of the health tracking industry, where the assumption is that the more data you have the healthier you’ll be. It aims to change the user experience of your average scale from one of shame and hate into something positive.
Instead of a screen with those damning numbers, Shapa’s scale features two metallic curves meant to indicate where you should put your feet, and the Shapa logo–and that’s it. The curves and round shape make it resemble a giant “on” button more than a medical device. When you do step on the scale, which is connected to a corresponding app on your smartphone, the app tells you how you’re doing, in general terms. Instead of getting feedback about your health through the number of pounds you weigh, the app shows you a color spectrum. One end indicates you’re gaining weight, the other if you’re losing weight, but crucially, the large, soothing green middle section means you’re the same as you have been. It takes into account all those weight fluctuations that you really shouldn’t be worrying about and and translates that into a simple green color that means, simply, all is well.
Ariely likens the interface to an analog scale that has a big needle obscuring whether your weight has gone up or down tenths of pounds. Most technology-enabled health trackers communicate how you’re doing–whether it comes to sleep, exercise, weight, or any other elements of your health–through cold hard digital numbers, often down to a decimal. Much of the wearables and activity tracking industry is built on the assumption that this access to more and more granular data improves your health–and many startups claim that their particular way of showing you those numbers will enable you to be a better, healthier person. But this premise has also led to the overly quantified self–and a debate in healthcare circles about whether quantifying everything is actually good for you.
Ariely thinks that giving people so much data is often more confusing than enlightening–and finding the right level of granularity for the data is the key. That’s why Shapa is supposed to give you a general sense that you’re doing fine, which he believes is all people really want to know anyway.
“Those [trackers] are incredibly hard to use in a reasonable way,” Ariely says. “I think that unless you’re a statistician, they’re not very helpful.”
So that Shapa can measure your weight effectively and not let fluctuations throw you off, the scale can’t give you instant feedback on day one. Instead, it takes 10 days of weighing yourself morning and night to give the Shapa enough data to work with. From there, as you weigh yourself every morning, it gets more accurate over time.
Besides telling you how you’re generally doing using the color-coded spectrum, the app also gives you recommendations, framed as “daily missions,” to encourage you to live healthier. Ariely says these recommendations–which encourage you to do things like drink a glass of water before going to sleep, find an exercise class by asking friends what they like, and plan out your workouts for the week in your calendar–are drawn from social science and tailored to who you are. When you sign up for the app, it takes you through an extensive questionnaire where you fill out basics like your age, height, and relationship status, as well as your work schedule, food habits, and exercise tendencies. He says that while initially, the recommendations are based on your answers to the survey, a machine learning algorithm will learn what you prefer and give you better recommendations over time.
According to a randomized control trial with 645 people Ariely conducted, the product works. Over the course of 12 weeks, people who used Shapa lost .61% of their weight per month, while those in a control group who used a standard scale gained .91% of their weight per month. The results are promising, but the study was commissioned by Shapa and is not peer-reviewed.
Of course, there are other ways of monitoring your progress that don’t cost nearly as much money–like measuring your waist or calculating your BMI. Shapa is also a pricey piece of technology. The scale costs $129, and the app costs $9.99 per month (though these prices are discounted through the end of January). Ariely is betting people will pay for the opportunity to track their health without the shame that comes with stepping on the scale.
More than anything, Shapa may indicate that a shift in thinking is coming to the health tracking industry: Skip the particularities and nuances of the data, and focus more on telling people what it means.