Perfect Fit, Sneaker Measuring App

What if you always knew what size sneaker to buy, without trying it on?

What's the problem?

Sneaker collectors and fans are often under time limits when purchasing limited number releases of sneakers. With online raffles shoppers don’t have the liberty of being able to try on the shoe. They need to make a decision now and whilst online. The pressure is real.

I’ve personally experienced this problem on multiple occasions when trying to buy sneakers online. You can't try them on before you buy them because sometimes they're only sold online.

This is just an assumption so far. Do other sneaker collectors experience the same issues I have? What about normal people?

No really, what's the problem?

Knowing that this is more than a personal problem and it is shared amongst all online shoppers, I felt confident that this was a valid problem that needed solving. First of all, I needed to define who my user was and what their key frustrations are. And one question kept coming up:

But will it really fit comfortably? - Sometimes a size 9 in one brand is more of a size 8 in another. Even if you know that your foot will fit, can you be sure that it won’t be too tight, or too loose?

Users want a comfortable fit, and they can’t be confident they will get a comfortable fit because the size of their foot doesn't translate to the same shoe size across different styles, colours and brands.

From my research, I found out that people from all walks of life experienced the same issue. I needed to focus into a primary persona that could inform all of my future decisions. Heels and boots came with additional complexities such as arch and heel height that affect a perfect fit. Because of the time constraints of just two weeks I decided to focus deeper on the Sneaker collector and fan segment of the shoe market.

Who is Alabama?

Using the painpoints identified, I put together a primary persona, Alabama, to anchor my solutions.

By creating this user persona I was able to better articulate the frustrations, needs, and goals that the users have so that they can be front of mind when conducting further research and ideating solutions going forward.

How are companies helping Alabama?

They aren't.

Size charts are a great way of knowing if your foot will fit into the shoe, if you have a measure tape handy and if you ignore the tightness and comfort of the shoe. Not a confidence instilling experience for sure.

This brought to light that any solution needs to use tools that are easy to use and readily available/handy as well as reaffirming that when users ask ‘will it really fit comfortably?’ The solution needs to confidently make the users think ‘yes’.

But will it really fit comfortably? - Sometimes a size 9 in one brand is more of a size 8 in another. Even if you know that your foot will fit, can you be sure that it won’t be too tight, or too loose?

Don’t need an extra tool - Users don’t always have a measuring tape handy, or a foot measuring apparatus. Can they get the perfect fit using tools that are readily available?

What about competitors in the market?

I looked at apps and websites to look for solutions that solve my users problems and I came across Xesto fit and Feet meter.

Both measured your foot and provided a recommended size for a different variety of shoes on their database. Xesto fit even creates a 3D model of your foot which helps the app recommend shoe sizes that will not be too tight or too loose. I made sure to keep this technology in the back of my mind as I progressed as it seems to be a successful way of accurately measuring the length, width, and shape of a foot.

However when I showed my users they displayed the same level of confidence they had when looking at size charts. They still couldn't trust the recommendations, even though their foot had been measured. These apps were close but no cigar.

I looked back at my conversation with Isaac - the Sneaker collector, do you remember him? And one thing really stood out to me:

When in doubt, and in the absence of a physical store, social proof is the most trusted way to verify if a shoe is going to fit. This can either be via blogs, forums, youtube videos, and many other platforms, however one thing is constant, trust is gained from word of mouth, people trust people. Helping me to understand that any solution will benefit from a social element.

People trust people - Users don’t always trust the recommendations in sizing apps. The trust is gained when people are personally testing and verifying how a shoe really fits. Just like they would when personally trying a shoe on in store.

How did I go from problems to solutions?

But will it really fit?

Don’t need an extra tool

People trust people

Now that I had my three areas of focus, I grabbed a pencil and paper and started to sketch out how I could potentially solve the problems Alabama faces when buying shoes online in a Crazy 8’s session. Features started to come to light and so did the potential flows that Alabama would go through.

I quickly went from quick sketches to mapping out the flow for each solution.

So, what are the solutions?

Based on my interview insights and Crazy 8’s ideation session, I mapped out flows for 3 key solutions to Alabama’s problems of wanting to know if it will really fit comfortably, not needing an additional tool, and trusting the size recommendations.

3D foot scan - Users don’t have measuring tapes and pieces of paper, but they do have their phones and the ability to create a 3D foot scan.  Understanding the tightness and looseness of a sneaker provides better size recommendations.

Sneaker Collections - ‘People trust people’ and by allowing users to add a sneaker to their collection and rate how the sneaker fits sizing recommendations are now based on community driven data as well as your 3D foot scan.

Size recommendations - Users asked “Will it really fit comfortably?” and to solve this problem users will be able to search for sneakers and be given the perfect fit for them using the 3D foot scan and Community generated sizing reviews that display the tightness and narrowness in Sneaker Collections.

Onboarding, scanning and size review flow

Time to grab a pen and paper

Now for the fun part! I pushed my keyboard aside and started by throwing my envisioned solutions onto paper in lo-fi wireflows. Keeping things analog allows for quick changes. Once I’m happy with the flows I move into Figma to level up to some mid-fi flows.

What do the users think?

When creating the mid-fidelity screens on Figma, my aim was to have an MVP so that they could be tested with users. As the screens are mid-fidelity, the users can focus on the experience instead of being distracted by the colours and images that come with high fidelity prototypes. I ran unmoderated usability tests with 13 users between the ages of 18 to 35, matching Alabama’s persona. The prototype scored a 76 with an average success rate of 79% on all screens.

I noticed some frustrations and pain points the users were experiencing through the quantitative data and the following qualitative feedback the users provided. This information was crucial to helping me iterate to the hi-fi prototype.

I looked at the iOS Human Interface guidelines that state a button should have a minimum height of 30 pixels and a margin of 10% meaning a minimum height of 33 pixels. But there are buttons that are smaller than that on iOS 15...something was not adding up.

Ready to find your Perfect Fit?

Watch prototype on Vimeo

What were the results?

• Users trusted Perfect Fit’s size recommendations more than competitors because they were community driven.
• Users enjoyed building their collection of sneakers and sharing how their sneakers fit and contributing to the community driven algorithm.
• Users finally felt confident buying sneaker sight unseen as they now know what their perfect fit is, every time.

What did I learn in this project?