How Aistetic Tripled Listings Capacity
With Zac Hembry, CEO, Messina Hembry
Case Study | Read time • 3 mins
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3x
Listings
-70%
Workflows
Increased
Conversion
"Using Aistetic’s AI Listing solution has revolutionised our workflow. We’ve seen a 3X increase in our listing capacity, a 70% reduction in our workflows and increases in conversions linked to faster, more accurate tagging."
Zac Hembry, CEO, Messina Hembry
Company Summary
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Name:
Messina Hembry
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Website:
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Location:
Ipswich, UK
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Product Category:
Pre-loved Designer
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Aistetic Solution:
AI Enriched Data & Listing
Use Case:
Listings Capacity, Efficiency, Conversion Uplift.
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Messina Hembry Established in 2019
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Brothers Zac and Josh started by selling on their hand-picked finds from charity shops during uni. They realised that they could provide people with the designer brands that they wanted for significantly less cost and help reduce the environmental impact of the clothing industry by doing so.
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Messina Hembry's vintage wardrobe is full of one-off items that are replenished weekly. When you shop with us, you can save up to 90% on original prices as well as reducing carbon emissions and the demand for mass material production.
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With thousands of unique garments added every week - from vintage sweatshirts to designer jackets - Messina Hembry faced several pressing operational challenges.
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Each item needed to be individually tagged, described, and measured. This manual process was not only time-consuming but created a bottleneck that limited how quickly new stock could be listed.
They needed a solution that could:
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Accurately generate product titles, tags and attributes from images - capturing details like colour, pattern, style, brand and condition without relying on manual input
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Scale to handle thousands of listings per week - and do so reliably and consistently, regardless of garment type or brand
Without automation, their ability to grow and meet demand would be constrained by the cost and complexity of human-led workflows.
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Why this solution
"We were looking for a virtual solution to help our shoppers find the right TLC size and fit for them. We have a variety of fits and leggings so we wanted something that would work well for our specific designs and sizings whilst also being easy to use, integrate and track performance."
"We were looking for a virtual solution to help our shoppers find the right TLC size and fit for them. We have a variety of fits and leggings so we wanted something that would work well for our specific designs and sizings whilst also being easy to use, integrate and track performance."
The Complete Story
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Introduction
Messina Hembry is a vintage and pre-loved fashion platform, founded by two brothers while still at university. Today, they upload over 7,000 unique items each week and have built a loyal following around their handpicked selection of premium second-hand clothing – from Calvin Klein to Nike. But with scale came the challenge of efficiently listing such a high volume of unique garments.
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Problem
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​Every piece in the pre-loved market is different, meaning each item must be photographed, described and tagged individually. For a fast-growing business like Messina Hembry, this made their listing workflow time-consuming and resource-intensive. Manual data entry not only slowed the process but made it harder to keep up with increasing demand and the volume of incoming stock.​
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Solution: Aistetic's AI Enriched Data & Listing
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To unlock new efficiencies, Messina Hembry partnered with Aistetic to integrate AI-powered garment tagging and description generation into their listing workflow. Aistetic’s AI Listing solution uses computer vision to automatically generate product titles, categories and attributes straight from images – removing the need for repetitive manual work.
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Key Results