We are soon to deploy virtual Tryons and selfie based recommendations to improve shopping experience: Suyash Katyayani

In an exclusive conversation with Suyash Katyayani, CTO & Co-Founder, Purplle.com sheds light on how technology is changing the game for Purplle.com
We are soon to deploy ‘virtual Tryons’ and ‘selfie based recommendations’ to improve shoppin

Being a beauty retailer how do you see the role of technology in terms of making the shopping journey easy for shopper for your patrons?

First and foremost, being an online player we have a lot of data which is a sustainable advantage over normal retailer. Typically, retailers use the data use not just user specific things but also mass wisdom things to tailor made the recommendations and personalized the shopping experience. However, when it comes to beauty things are slightly different because beauty is driven by persona factor, so the product recommendation for fair skin toned would be far different who has dusky complexion. Whereas, if you see other categories such as electrics, mostly products are bought based on customers’ budget and product features.  

Beauty is the third largest goggled category on internet where 85% queries are related to discovery of the product. As a beauty retailer, we have worked really hard to acknowledge two aspects one is discovery orientation which is need based search kind of thing and the second thing is persona

So we have to work around persona related data. Once we get the data, it is equally important to understand what queries are, and that understanding should be beyond text understanding. Let’s say, if someone is looking for shampoo for monsoon then we should also understand that monsoon also causes frill in hair so recommendation should consider all possible situations.

Are your using artificial intelligence (AI) tools in making personalized recommendation?

We used AI and machine learning very extensively so the moment customer logon to our website. Sometimes people are not able to figure out what exactly they are looking for, for example, if somebody is trying to buy an eye liner, so we don’t know the person concerned is pro or newbie and what kind of look she is trying to create. For such kind of people we have beauty assistance which is an interactive shopping assistance for shoppers.

What new technologies you have been working to improve front end experience?

There are two important technologies pieces we are working on is virtual Tryon  and selfie based recommendations where you can just click selfie and our system and machine learning will understand the facial  features and will offer personalized recommendations.

How you differentiate between mobile app and m-commerce? What sort of response the company is generating from its mobile channel?

Mobile is a very big channel for us.  Over 75% of our customers are on mobile which includes mobile app as well as website. And we expect if future existing percentage to go even higher. The kind of data we have seen, these two mediums serve completely different purposes.  Typically, most of the people discover the product first time on mobile website but loyal customer choose app to make purchase. Our most loyal based customers are on app.  So both channels are important for us, we cannot ignore one over other. We have received close to one million downloads.

 

 

 

 

 

 

Suyash Katyayani
 
 
 
 
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