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Home Tech

Can Artificial Intelligence Enhance The Mass Customization In The Fashion Sector ?

by Guest
April 29, 2016
in Tech
Reading Time: 4 mins read
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Can Artificial Intelligence Enhance The Mass Customization In The Fashion Sector ?
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artificial intelligence fashionEverybody wants to look beautiful. We all like to be well dressed and keep up with fashion trends, but most times this is not possible. We are constrained by time, money and the skill to put together trendy outfits.

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The problem gets compounded when we go shopping online. Every store has 1000’s of items in each category. Products in different – brands, colours, styles, and price points. This is all very confusing and it is hard to decide want to buy, so we pick up something, get it delivered, try it and return it unsatisfied. Fashion as a segment has the highest number of returns in e-commerce, almost 25-50%.

On the flip side, every retailer is plagued by the question, “How many products per category should I carry?” AI can be very helpful here, not just with inventory management but it can enable the retailer to become a curator and not a clearing house. Personalizing the content for each customer to show her just the right products is more important than having zillions of products to choose from.

Visual search goes mainstream

Wenda Harris Millard, president and COO of MediaLink, thinks marketers are going to be obsessed by Visual search for the next few years and will use it to enhance everyday life, in ways that we can’t image today.

Fashion as a category being visual has embraced this technology. Most times it is hard to describe an apparel in words unlike goods in electronics or FMCG. If something can be described well, text search engines would work beautifully. Since we cannot describe apparel well, doing things using visuals is so much more intuitive.

Today, you can not only upload a photo of an item that inspires you and find similar ones online you can even upload an image and get a list of complementary products that complete the look!

[box type=”shadow” align=”aligncenter” class=”” width=””]Related Read:

Will Convenience of Virtual Fitting Rooms Make Physical Fitting Rooms Obsolete ?[/box]

Can AI deliver one to one services at scale?

Most decisions that we humans make can be assisted. Especially in cases of fashion where specialist input of what suits me, what goes well with what, is very desirable. We all have stylish friends who give us fashion advice, but they are not always around when we need them and it is impossible to get their advice on a daily basis.

AI’s ability to make predictions has particular implications for a trend-driven industry like fashion. Machine learning can enable brands to finely personalize their offerings to each and every customer. The AI engine remembers individual choices and knows their unique tastes. It consolidates fragmented customer behaviors to give true personalization.

Decoding fashion

The most basic features of a garment are Color, Shape, Print and Fabric. Computer vision techniques can be used to extract these attributes and convert it into data that is processed by machine learning Algorithms. Fashion Algorithm’s are nothing but an exhaustive set of rules that contextualize data. It is the collective mind of all fashion stylists processing consumer data such as body shape, skin tone, shoppers lifestyle, previous purchases etc. and mapping the requirement to extracted attributes and picking the appropriate products for the shopper, all in real time.

[box type=”shadow” align=”aligncenter” class=”” width=””]Related Read:

MyTryRoom – Try Before You Buy – Bridging The Gap Between Online & Offline Shopping ![/box]

It is not possible for even a large bank of stylists to crunch this data and make recommendation at the speed and scale required by retailers today. Machine systems can easily compute these vast data sets and be trained to learn correlations between different attributes and fill in the missing values. They even have inbuilt self correct mechanisms to process and learn from feedback, based on what shoppers do with a recommendation. So, the more a customer uses the service, the more accurate the results will be.

Complex processing at this scale and speed has been made possible today due to advancements in 2 major fields of computer science. Computer vision and machine learning. Algorithms developed in these fields were largely in academics. To make these accessible to general public would have required enormous computing power. Thanks to tectonic changes in the GPU industry in recent years, massive computing is now affordable. This is fuelling lots of new-age products like AI bots that can converse with humans and answer questions related to fashion / e-commerce / style etc.

It is only matter of time before each person will have an AI bot as her stylist to help her dress better, shop more intelligently and be stylish!

Reference: Quora, Adweek

(Disclaimer: This is a guest post submitted on Techstory by the mentioned authors.All the contents and images in the article have been provided to Techstory by the authors of the article. Techstory is not responsible or liable for any content in this article.)

Image Source: pixabay.com

About The Author:

Rajesh Kumarartificial intelligence fashion author, CTO at Streamoid Technologies.

Streamoid is a Fashion Focused technology company with Image Recognition and Fashion AI at its core.

 

[box type=”shadow” align=”aligncenter” class=”” width=””]Also Read:

Styletag.com is one stop solution for your curated fashion and lifestyle needs![/box]

Tags: algorithm-based personalized feedArtificial IntelligenceComputer VisionCustomizatione-commerceFashionInventory ManagementStreamoid
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