TG盗号系统企业源码|【唯一TG:@heimifeng8】|电报盗号系统免杀破解技术✨谷歌搜索留痕排名,史上最强SEO技术,20年谷歌SEO经验大佬✨Retail tech: how Makip aims to transform sizing tech and create brand superfans
Sandra Halliday Published
June 23, 2025
The arrival of Japanese tech specialist Makip in the UK market this year highlights the importance of sizing technology — and beyond that, of technology in general — to the online shopping experience.
Fashionnetwork.com met its president Shingo Tsukamoto in London when he and his team were here to speak to potential UK clients and found that the company is more than just a sizing specialist with its tech and data able to offer much more.
At the moment, Makip is the sizing tech leader in its home market, and as well as working with hundreds of local retailers and brands, it’s also working with international labels in Japan, such as Lacoste, Tommy Hilfiger, Michael Kors, Calvin Klein, Vivienne Westwood and New Balance.
But Shingo Tsukamoto revealed that the tech Makip has available to it is opening up a whole new world of data-driven experiences that can potentially transform the experience of buying fashion online.
And one piece of tech is particularly interesting beyond simply helping shoppers find the right sizes. The firm’s still-new Hero Analysis product (which won’t be available outside of its domestic market for now) helps fashion retailers develop a data-driven sales strategy and maximise lifetime value (LTV) by "discovering the ‘Hero items’ that provide opportunities to gain fans”.
Its Al algorithm looks at data on items sold in the past and it “provides reports on items with a high potential to become Hero items from items currently on sale”.
Plus its KPI Report analyses data such as LTV, unit price, purchase frequency and repeat purchase rate, “to help turn shoppers into repeaters” and understand those one-off shoppers who didn't repurchase.
“When users become a fan of a brand, if you sell clothing to this one customer you want this customer to keep buying clothes from your brand,” Tsukamoto explained. “We’ve just launched this feature that analyses the timing of you becoming a fan, what makes you become a fan. Just buying something doesn’tmake you become a fan, each brand has specific items that make [it happen]. In order to make your customers a fan of your brand you have to recommend the item that makes it happen, predicting what makes a consumer buy.”
It’s certainly an interesting idea and is yet another example of how data can transform the way retailers operate and how generating data linked to one product offer (its sizing technology) can lead on to other tech solutions.
It’s also an example of how AI can be used to helpbusinesses (and their customers) rather than just being the potential problem some people are suggesting it might be.
THE SIZING ISSUE
For now though, the company’s core product is its Unisize tech that helps online shoppers find out whether an item might fit them.
Of course, there are a lot of sizing assistants out there already. So why does Makip think that it can gain traction outside of its home market and why did it go to Britain first?
“We are the leading sizing technology company in Japan. We want to expand our business to the global market because sizing issues are common issues globally,” Tsukamoto told us. “The UK is the first market [and] we chose it because the UK e-commerce market is really big. The e-commerce revenue share is really high compared with other Western countries. The US and China are the biggest [e-commerce markets for total sales]. But as a first step to enter the global market, we chose the UK.”
In terms of the product offer, Makip claims its tech goes deeper than other solutions do in terms of the questions it asks the shopper (include not just their size but how they like things to fit) and the wider data it brings in to help map a particular item to a particular shopper’s unique body. Consumers can also compare potential purchases with clothes they already own.
For its UK launch, Makip measured and analysed hundreds of Britons to create a specific algorithm for the country, because British bodies are quite different from Japanese ones.
The big point is the way all of this, plus the behind-the-scenes AI not only come back with size recommendations for the shopper but help drive higher conversion rates and lower return rates.
The potential for such tech is huge and the company said it’s already finding that around 30% of shoppers on webstores that have it are using the tech. That has helped reduce their returns on average by 20%, although for some of clients the percentage is much higher.
Meanwhile, research the company commissioned for its UK launch shows its opportunity is huge because “UK consumers don't trust online sizing technology to accurately predict their body size”.
It spoke to 2,000 UK-based e-shoppers who’d used online sizing technology bought minimum of 11 items of clothing online in the past 12 months.
Some 75% said sizes are inconsistent between brands and 60% don't believe the tech “can be accurate because every website seems to use a different system”.
That’s a huge problem for e-tailers because inconsistent sizing guides result in online shoppers needing to order multiple items of clothing to try on at home.
This exacerbates the problem of returns, which eats into retailer profits, and dents consumer confidence. Plus returns are more likely to end up in landfill.
There’s also the affordability issue. A woman who wants to try on, say, two dresses, might not be able to afford to order and pay for four of them upfront if she needs to buy each one in two sizes (or sometimes three sizes).
As many as 48% of respondents said they’ve used online sizing tech before, but the fit of the item was wrong. And given an earlier BFC report that showed 93% of customers citing incorrect sizing, or fit, as the top reason for returning items, there’s clearly an opportunity for more advanced tech to carve out market share.
Shingo Tsukamoto, said of this: “When it comes to creativity, inspiration and trends, the fashion industry is usually trailblazing, but in practice, the implementation of new technologies has moved along at a very slow pace.
“Ultimately, retailers need to get their heads out of the sand and take proactive steps to support their customers, giving them the confidence that their newest fashion purchase will fit as expected.”