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WITH FIT:MATCH MIDDLE WARE, FIT TECH IS FINALLY HERE TO STAY.

March 8, 2021

With FIT:MATCH MIddle Ware, Fit Tech Is Finally Here To Stay.

 

Fit technology is not new. That it’s finally become commercially viable, is.

 

Fit tech has been around for a while, along with the fit-related problems it is intended to solve. Getting fit right has always been central to customer satisfaction, and therefore a huge driver of apparel retail economics. With the advent, growth and now pandemic-induced acceleration of online shopping, the centrality of fit has become even further amplified, and fit-related challenges further heightened. Who would ever have thought that fitting rooms would be closed, and that shoppers would fear and even abstain from trying on clothes? 

 

Entering the Fit Tech space as a founder has afforded me a front-row seat to the skepticism that exists among brand decision-makers and potential investors. They’ve seen numerous attempts at cracking fit for shoppers come and go, and that has led to what one potential partner calls “Fit Tech Fatigue”. Fit Tech has had a bad wrap based on what the market has seen to date, making it more challenging to prove the long term benefits and its significant potential.

 

It is exactly this skepticism that has propelled my team and I to dig deep into why retailers have been dissatisfied with Fit Tech solutions in the past. And what we’ve learned has informed our vision to become the enabler of Fit Tech... the catalyst to finally make Fit Tech work, stick and stay.

 

To date the solutions we’ve been seeing on the market focus on what we call “the front end of Fit Tech”. This is the part where customer measurement intake takes place. Whether it be 3D measuring or survey-based self reporting, this part has been in play for some time. With the innovation we are seeing in technology, like Apple’s recent launch of LIDAR in the iphone, we expect the accuracy to get better and better with the capability for shoppers to have powerful and accurate scanning technologies in their pockets, making the technology ubiquitous.

 

What hasn’t been in play until now, at least successfully, is a focus and solution for the back-end to make Fit Tech truly integrated into the apparel buying and selling journey. We think of this as “the battery” that makes it all work for brands...the process by which customer measurement data truly fuels commerce and creates significant value for both retailers and shoppers.

 

There are two critical components to a successful Fit Tech integration 1) the front end customer measurement intake and 2) the back end data algorithms and processes. For a long time, many large retailers and brands have implemented fit tools that have focused solely on the front end. This approach has yielded subpar results, with low conversions and high returns still persisting. 

 

FIT:MATCH is addressing this need in the market. As a middleware platform, our expertise is to handle all the back end “fit matching”. This means each SKU will be accurately onboarded onto our matching architecture so that shoppers are matched with items that fit their exact bodies. FIT:MATCH therefore powers the fit-centric shopping process, helping brands operate with fit transparency that translates to unprecedented levels of consumer confidence. This fit-based confidence translates to a positive impact on conversions and returns. And the rich insights garnered, inform future design and buying decisions to further hone a brand’s product market fit from season to season, flow to flow.

 

The FIT:MATCH software can agnostically plug into almost any front end fit solution (whether in stores or online) on the market, making these fit tools viable and scalable for commerce. Importantly, product and marketing teams can utilize this robust match software to inform upstream and downstream decisions and efforts.

 

With the front end and back end now solved, fit tech can finally be here to stay.

 

For more information on how FIT:MATCH can power Fit Tech for your brand, contact sales@fitmatch.ai.

 

 


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