The Biggest Missing Element in Most Product Experiences, According to Behavioural Science (Does Yours Have It?)
Libby was new to backpacking. Her first trip was a 4-day trek through the Sierras with a good friend who was far more experienced. Before setting off, they downloaded an app that tracked their speed, elevation gain, and miles.
At the end of the first day, they were eager to see how far and fast they’d gone. Unfortunately, the app showed that their pace was slower than expected. They’d gained 3,000 feet and gone 7 miles, but only managed a 1.7 mph speed.
Libby’s first thought was the most “logical” — they should just walk faster. She ideated things like picking up the pace on downhills to compensate for slower uphills; or taking a few 2-minute breaks instead of a full 10-minute stop.
The experienced hiker had a different answer that hadn’t even occurred to Libby: Reduce weight.
Experienced backpackers know the easiest way to improve speed is to reduce the weight of your pack. When you carry less, you go faster. Her friend suggested things carrying less water and re-distributing weight.
Now consider how little the fancy hiking app itself helped a smart person like Libby. It provided lots of pretty charts and graphs, but no guidance as to what to actually do with all that info. In other words, it didn’t help Libby to just have the data.
And the cost: Had Libby been hiking alone, she’d likely have tried to “just walk faster” … and failed. Then she’d have gotten frustrated, blaming herself for not being strong enough. She might even have injured herself by trying to go too fast and tripping, or overexerting herself by skipping much-needed rest breaks.
Pretty graphs don’t drive meaningful user behaviour
The fact is, consumer apps do this all the time — provide pretty data with no expert suggestions alongside it. This is like giving you the ingredients to bake a cake but asking you to come up with the recipe.
Case in point: the Fitbit sleep app gives me incredible data about my sleep patterns. Yet even in the premium version (which is supposed to have quality recommendations), 90% of app space is dedicated to data and just 10% to the punchline — what I should do to improve my sleep.
The Peloton app also leaves me hanging. It gives shockingly fun data about my rides but leaves out the most important point — how do I improve my output (wattage) to get into better shape?
In the case of Peloton, the novice biker assumes the obvious (much like Libby) — pedal faster. But an experienced biker knows that it’s far more effective to increase resistance. Instead of pedaling faster, they’d bump up resistance by 1–2 points to drive up wattage.
The worst culprits, however, are fintech personal financial management apps. These companies spend most of their engineering budgets improving categorization and data visualizations. This results in beautiful pie charts and trend graphs of your spending last month vs prior months.
But what does it leave out? What a user should do to change their spending.
For example, Clarity, the popular “Mint replacement” app for Millennials, spends almost zero UI/UX space on helping you figure out what to do with the data. The implicit assumption is that you’ll know the best way to decrease spending once you see the chart.
Sadly, this is not the case. Most people think they should cut back on lattes or forgo avocado toast to reduce costs. In reality, experts all say tackling housing, transportation, and healthcare costs are far better ways to save.
Reports and insights aren’t enough — users need your help to connect the dots
And the research is clear — simply tracking your behavior is not enough to change it. This is especially true in complex environments where the “best action” may not be obvious to the beginner. For example, researchers paid diabetics to monitor their glucose levels, and peopledidsucceed in tracking their levels. But despite heavy monitoring, there was no actual change in glucose levels.
In simple environments, where the insight and the action are one and the same, just displaying data has more hope. For example, when it comes to step trackers, there is evidence to suggest if you track steps, people will take more steps. But if someone desires weight loss (a more complex issue), using a step tracker can actually backfire! In a comprehensive 2 year study designed to encourage weight loss, participants who were using step trackers lost 5 pounds less weight than the control! Why? People with the step trackers took more steps, but walking displaced the high-intensity exercise that would be more likely to help with weight loss.
This finding holds for financial behaviors — researchers have yet to find compelling evidence that solely giving people information (e.g. about compound interest or FICO) is enough to change investing or credit habits. Data just doesn’t get you all the way there.
You can make the recommendation: you’re the expert
To truly support users, app developers should focus on guiding people on the behaviors (actions) they should take based on the data. Your users are Libby, and they need you to be the expert backpacker.
Of course, this is a challenging thing to do. How do you know your recommendations and guidance is optimal for Libby? Sadly, we find it’s fear that prevents teams from providing any guidance.
At Irrational Labs, we worked with a group of world-class engineers faced with this issue. They were building an ad platform and didn’t want to recommend keywords for the small businesses, reasoning that the small business would be the best person to decide their own keywords.
Is that true? The florist thinks about flower arrangements and the baker thinks about cakes. Small businesses are not experts at ad platforms and keywords. The engineers are world experts at keywords — the engineers think about keywords every day, all day! Who better to make an educated guess than them? Certainly not the florist who doesn’t even know what a keyword is.
As product managers and designers, you are the experts in your domains. It’s likely very few people in the world think more deeply about your problem space than you do. And so while it’s challenging to make recommendations, it’s your job. You’re in the best position to bridge the gap between beautifully-presented data and helping people improve their lives.
How do you guide user action? With behavioural design
Now, as a designer, taking this path opens up a whole new set of problems. How do you convincingly propose the best action, knowing your user’s assumption is probably different? How do you make it easy to do what you suggest, knowing any friction will reduce their likelihood to do it? And how do you show charts and graphs without triggering disappointment such that a user loses the motivation to do anything?
These are meaningful and worthwhile questions to ask and answer. Because once you go beyond just furnishing users with data, you move into behavioral design, which is where things get really exciting.
We also used behavioral design in collaboration with a bank, helping them to decrease their rate of auto loan defaults by 69% year-over-year. Behavioral science revealed that the opportunity to intervene with repayments wasn’t after someone missed a payment — but at the point of loan origination. We, therefore, designed the bank’s welcome call to include setting up auto-pay and bill pay reminders. Imagine the human cost saved — the stress reduction for people who got to keep their cars and feel like they had things under control financially.
You will more deeply serve your users when you go the step beyond just providing data, and provide smart, expert guidance. Behavioral design helps you to facilitate the kind of transformational change that uplifts and inspires both you and those you serve.
Want to learn more about applying behavioral economics to product design? Irrational labs has an online 8 week bootcamp. Use the code “” to get 20 percent off.
Originally published at https://bermster.medium.com on October 31, 2020.