We used machine learning & predictive analytics to make the suit fit!

  • ClientThe Drop
  • scopeUX/UI Design \ Development
Real-time human pose estimation in-browser
Utilising complex data for better customer experience

AI was the perfect fit

Online tailor The Drop creates high-quality custom-made suits which can be ordered entirely online without the need to visit a physical store. Meaning they’re able to dedicate more cost to the tailor, compared to high street retailers, and sell custom suits at a more affordable price to customers.

Microsoft matched Pull to work with The Drop to create a custom AI solution to simplify the process of self-measurement and provide more accurate readings. This made The Drop more efficient and gave their staff more time to focus on the tasks that really matter.

Man in suit adjusting tie with logo

The Challenge

The Drop uses a combination of customer photos and self-measurements to create their suits. However, they were finding that some people had difficultly measuring themselves, and those with a less than typical body shape didn’t always get the right fit the first-time round.

The Drop wanted to streamline this process to ensure every customer had the best shopping experience possible, and had to do the minimum of measuring. With this in mind, they attended the AI Hackathon event hosted by Microsoft to try and find a solution.

But could machine learning and predictive analytics actually help to create a better custom suit?

Sowing machine
Measuring up suit chest
The Drop web site on tablet display

What we did

As a trusted partner, Microsoft recommended Pull to The Drop with the task of helping to solve this particular business problem. Over the course of the next 3 days Pull collaborated with The Drop and Microsoft to create a working solution using experimental AI.

One AI solution specifically detected anomalies in measurements. For example, if someone was unusually tall, the AI solution could detect this and flag that the customer may need to provide more manual measurements. The programme could also check that measurements taken were correct. To create this anomaly- checker Pull used Microsoft’s machine learning studio and The Drop’s data to create a machine learning model for anomaly detection.

Another AI prototype looked at solving customers concerns regarding providing too many measurements & the accuracy of these measurements. The prototype was able to measure a suit just through customer photographs, removing the need for a tape measure. The team worked together on developing a model which converted photograph pixels to cm’s, for the tailor to work from, using a technology called Posenet.

People in meeting looking at The Drop site on laptops
View of mobile app, scanning a user for measurements

Fit for the job

With the help of Pull, The Drop are currently developing these prototypes and implementing accurate working models within their web platform to streamline their business and creating a better experience for their customers.

Close-up of hand carefully sowing a button on to a jacket
Tablet view of product page

“The most immediate and obvious result is a streamlined supply chain.”

“With our AI concepts, we’ve been able to enhance what was always there – our workforce – to produce custom garments faster. Our people have more time to focus on the tasks that really matter. And our business can scale faster and perform better. That first AI investment is already paying us back, and it was easier to get up and running than we expected.”
Stephen Stroud, CTO and co-founder - The Drop
Montage shot of phones showing a suit product page

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