User:Sascha Noak/sandbox: Difference between revisions
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Isabelle Ohnemus, Founder and CEO. Born in Geneva. Lived her first 18 years in 8 countries and 3 continents, fluent in 6 languages. University studies in Geneva: BA in Economics and Marketing. |
Isabelle Ohnemus, Founder and CEO. Born in Geneva. Lived her first 18 years in 8 countries and 3 continents, fluent in 6 languages. University studies in Geneva: BA in Economics and Marketing. |
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Isabelle’s career started in investment banking. She worked for more than ten years in a well-known investment bank, as a broker in stocks and derivatives. |
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Fashion was always part of her life though and, for this reason, she decided to turn this passion into something more concrete. |
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Isabelle started organising private sales at her home, for her busy girl friends who wanted to access the world of fashion in an easy way. The sales included new and ground- breaking designers from Italy, Denmark and France, who had no actual stores. Isabelle’s own place became their exclusive store and in this trendy and funny environment she realized the inconsistency of sizing. |
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== Platform and functionality == |
== Platform and functionality == |
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Sizing Methodology |
Sizing Methodology |
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The Problem - Sizing |
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Apparel brands don’t use standardized sizing. |
Apparel brands don’t use standardized sizing. |
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Sizing across brands and countries is inconsistent. |
Sizing across brands and countries is inconsistent. |
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Brands increasingly use Vanity Sizing or size inflation. |
Brands increasingly use Vanity Sizing or size inflation. |
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Shoppers don’t know their measurements. <ref name="onesizeforall>[https://http://womenuk.co.uk/style/one-size-fits-all-not/#prettyPhoto One Size Fits All? NOT…], Women UK, November 21, 2016</ref> |
Shoppers don’t know their measurements. <ref name="onesizeforall>[https://http://womenuk.co.uk/style/one-size-fits-all-not/#prettyPhoto One Size Fits All? NOT…], Women UK, November 21, 2016</ref> |
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‘smart’ learning technology which continues to ‘learn’ from billions of data points, matching clothes not only to measurements but ultimately to typical body shapes and style preferences globally. Via the app and the web users can browse through each online store not wasting time worrying about what will fit. |
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The app is available on iOS and Android devices. |
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EYEFITU enables consumers to find and buy clothes in their right size from the most popular brands and online stores in the world. Sizing is the largest issue when ordering online and EYEFITU solves this problem by giving users size recommendations. Users can create their own individual shop to browse and buy garments in their size from their favorite brands. They can create multiple fashion profiles and share their own to shop for family and friends and allow gift purchases in the right size. |
EYEFITU enables consumers to find and buy clothes in their right size from the most popular brands and online stores in the world. Sizing is the largest issue when ordering online and EYEFITU solves this problem by giving users size recommendations. Users can create their own individual shop to browse and buy garments in their size from their favorite brands. They can create multiple fashion profiles and share their own to shop for family and friends and allow gift purchases in the right size. |
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In order to give sizing recommendations, we match user body sizes, measures and preferences with the sizing of the clothing. We are using a combination of information provided by users, brands/retailers, statistical data and crowdsourcing to provide the most accurate sizing recommendations. |
In order to give sizing recommendations, we match user body sizes, measures and preferences with the sizing of the clothing. We are using a combination of information provided by users, brands/retailers, statistical data and crowdsourcing to provide the most accurate sizing recommendations. |
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User data |
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We capture user data in various ways: |
We capture user data in various ways: |
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The user provides gender, age, height and weight in order to get sizing recommendations. Our system statistically correlates this information with a large database of human body measurements and automatically fills it into the user profile. |
The user provides gender, age, height and weight in order to get sizing recommendations. Our system statistically correlates this information with a large database of human body measurements and automatically fills it into the user profile. |
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Users provide their actual body measures using a measuring tape. This is more accurate but only a limited number of users will use a measuring tape. |
Users provide their actual body measures using a measuring tape. This is more accurate but only a limited number of users will use a measuring tape. |
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Shopping history and sizing preferences. Consumers can specify their preferred size for brands and garments. Based on big data/crowdsourcing, groups of users with similar profiles and sizing preferences act as sizing recommendations for other users with similar profiles. By incorporating this user-generated content, the algorithm is continuously improved. This is in fact crowdsourcing of virtual size charts. |
Shopping history and sizing preferences. Consumers can specify their preferred size for brands and garments. Based on big data/crowdsourcing, groups of users with similar profiles and sizing preferences act as sizing recommendations for other users with similar profiles. By incorporating this user-generated content, the algorithm is continuously improved. This is in fact crowdsourcing of virtual size charts. |
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As technology improves, we will be able to use input from body scanners and photos. |
As technology improves, we will be able to use input from body scanners and photos. |
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Sharing |
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Users can share their fashion profiles (size information – not personal information) with friends and family to allow gifting in the right size. They will also be able to create wish lists of the most wanted fashion items and share these socially on Facebook and other social media. This will engage users and make the App feel more personal to them. This will trigger worth of mouth growth. |
Users can share their fashion profiles (size information – not personal information) with friends and family to allow gifting in the right size. They will also be able to create wish lists of the most wanted fashion items and share these socially on Facebook and other social media. This will engage users and make the App feel more personal to them. This will trigger worth of mouth growth. |
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See what is relevant to them according to their size preferences. |
See what is relevant to them according to their size preferences. |
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Have immediate access to deals and discounts. |
Have immediate access to deals and discounts. |
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== Awards and nominations == |
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EyeFitU is already gaining industry recognition. It was awarded the Nouvo Prize, conferred by RTS (Swiss National TV) for being the most promising start-up in February 2015 and recognised by Netcomm Suisse - Ladies in e-commerce, in July 2016, for the best pitch. Both awards were publicly voted for. |
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The EyeFitu app was named as one of the Favourite Fashion Apps 2015 from FashInvest, in December 2015, recognising it as the app that made the most impact on the fashion tech scene in 2015. |
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Revision as of 20:44, 2 December 2016
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| Founded | Zurich, Switzerland |
|---|---|
| Area served | Worldwide |
| Founder(s) | Isabelle Ohnemus |
| Key people | Isabelle Ohnemus, CEO Henrik Steffensen, COO |
| URL | eyefitu |
| Launched | December 2012 |
EyeFitU is a Zurich based company using app based technology that lets users create a profile of their clothing measurements and matches this against sizing charts from thousands of brands, filtering online shopping results down to the items most likely to fit. [1]
History and background
Isabelle Ohnemus founded EYEFITU on the 12th of December 2012. To get quick access to highly talented software developers and to remain flexible, EYEFITU started up by working with Ergon Informatik AG in Zürich, Switzerland, an award-winning, respected, experienced and knowledgeable software company and system integrator for large corporations and successful start-ups. Together with Ergon, a significant effort went into development and prototyping of QR-/Bar-code scanning capabilities, a feature that will be appealing when brands and retailers start attaching garment data to these and to fashion print. In order to reduce costs, speed-up and keep development of our App/Platform agile, we are now working with Ciklum, a Danish software company with a big development center in Minsk, Belarus and with whom the EYEFITU team has worked with previously.
Isabelle Ohnemus, Founder and CEO. Born in Geneva. Lived her first 18 years in 8 countries and 3 continents, fluent in 6 languages. University studies in Geneva: BA in Economics and Marketing.
Isabelle’s career started in investment banking. She worked for more than ten years in a well-known investment bank, as a broker in stocks and derivatives.
Fashion was always part of her life though and, for this reason, she decided to turn this passion into something more concrete.
Isabelle started organising private sales at her home, for her busy girl friends who wanted to access the world of fashion in an easy way. The sales included new and ground- breaking designers from Italy, Denmark and France, who had no actual stores. Isabelle’s own place became their exclusive store and in this trendy and funny environment she realized the inconsistency of sizing.
Platform and functionality
Sizing Methodology
Apparel brands don’t use standardized sizing. Sizing across brands and countries is inconsistent. Brands increasingly use Vanity Sizing or size inflation. Shoppers don’t know their measurements. [2]
‘smart’ learning technology which continues to ‘learn’ from billions of data points, matching clothes not only to measurements but ultimately to typical body shapes and style preferences globally. Via the app and the web users can browse through each online store not wasting time worrying about what will fit.
The app is available on iOS and Android devices.
EYEFITU enables consumers to find and buy clothes in their right size from the most popular brands and online stores in the world. Sizing is the largest issue when ordering online and EYEFITU solves this problem by giving users size recommendations. Users can create their own individual shop to browse and buy garments in their size from their favorite brands. They can create multiple fashion profiles and share their own to shop for family and friends and allow gift purchases in the right size.
The user enters gender, height and weight to get size recommendations for all brands. For more precise recommendations, the user can enter body measurements. If a user happens to know her or his correct size for a certain garment type or brand, these can be entered alongside the EYEFITU recommendations. By incorporating this user generated content, the algorithm is continuously improved
In order to give sizing recommendations, we match user body sizes, measures and preferences with the sizing of the clothing. We are using a combination of information provided by users, brands/retailers, statistical data and crowdsourcing to provide the most accurate sizing recommendations.
We capture user data in various ways: The user provides gender, age, height and weight in order to get sizing recommendations. Our system statistically correlates this information with a large database of human body measurements and automatically fills it into the user profile.
Users provide their actual body measures using a measuring tape. This is more accurate but only a limited number of users will use a measuring tape. Shopping history and sizing preferences. Consumers can specify their preferred size for brands and garments. Based on big data/crowdsourcing, groups of users with similar profiles and sizing preferences act as sizing recommendations for other users with similar profiles. By incorporating this user-generated content, the algorithm is continuously improved. This is in fact crowdsourcing of virtual size charts. As technology improves, we will be able to use input from body scanners and photos.
Users can share their fashion profiles (size information – not personal information) with friends and family to allow gifting in the right size. They will also be able to create wish lists of the most wanted fashion items and share these socially on Facebook and other social media. This will engage users and make the App feel more personal to them. This will trigger worth of mouth growth.
Personalization
The personalization aspect of EYEFITU is unique because it offers shoppers the ability to:
Create their individual shop with their favorite brands.
Browse and shop clothing in their size selected from hundreds of brands and online stores on one platform.
See what is relevant to them according to their size preferences.
Have immediate access to deals and discounts.
Awards and nominations
EyeFitU is already gaining industry recognition. It was awarded the Nouvo Prize, conferred by RTS (Swiss National TV) for being the most promising start-up in February 2015 and recognised by Netcomm Suisse - Ladies in e-commerce, in July 2016, for the best pitch. Both awards were publicly voted for.
The EyeFitu app was named as one of the Favourite Fashion Apps 2015 from FashInvest, in December 2015, recognising it as the app that made the most impact on the fashion tech scene in 2015.
References
- ^ Fashion turns to data analytics to cut number of returned items, Financial Times, October 5, 2016
- ^ One Size Fits All? NOT…, Women UK, November 21, 2016