Shoppist: Your Personalized Google for Shopping

eCommerce has revolutionized the way a consumer shops for goods and services in a mobile world. Today, the biggest scope for disruption in this avenue lies in product discovery- through hyper personalization with the help of cognitive technologies and smart data. Here’s a startup which has identified this opportunity, and aspires to serve as a one stop destination for online shoppers by facilitating interactive based discovery.

shoppist team

Founded in October 2014, Bangalore-based Shoppist is a “personalized” product discovery platform which employs an intelligent agent to search online on behalf of the users and get them the most relevant products curated out of entire web.

It is the brainchild of Shankar Singh, Ex-Head of technology at Vedantu and Divij Goyal, Ex-CEO at

Problems Addressed by the Startup

Searching for the desired product online, across multiple platforms could be an onerous and time-taking task. Usually, when a user wants to buy something online, he/she browses at least 5 shopping apps/websites and skims through a number of products before making the final buying decision. This is the key problem, Shoppist attempts to address. It not only economizes users’ time but also, makes the experience hassle free and smooth.

Features of Shoppist

  1. The app recommends appropriate products based on user behaviour, trends etc. Shoppist articulates fashion in accordance with the user’s taste, body statistics, and the selected price range.
  2. It employs Artificial Intelligence and Machine Learning to make the searches personalized.
  3. Besides recommending the apt products, the app also keeps the user informed of the running deals and discounts.

Traction Details

The startup claims to make 4 transactions a day which gives it over 4% conversion rate. (The standard conversion rates are 0.5%). It has 1000+ users (App + Web) and 387 clicks on BUY NOW button which is over 30%. (The standard engagement percentage is 10%)

“90% of user are giving all the information about them. That gives us a vast Shoppist profile data of users”, says Divij.
Monetization Model

  • Affiliate commission (5-20%): The company gets commision on every sale facilitated through its platform.
  • B2B Paid Subscription: As it is giving niche players like Ebony Twist, a platform to compete with big shots, it is charging subscription fee on month-month basis for complete consumer insights.
  • Shoppist Advertising platform: Which will enable brands to advertise their product in a highly targeted manner. For example, they can target what user as per their body sizes, profession, education, hometown, color preferences, brand preferences, shopping budget.

Funding status

The startup is currently bootstrapped. However, it is soon to raise external fund.

Scope and Future Plans

Elaborating on the scope of this sector, Divij maintained, “If you talk amount market size, we are playing in product discovery platform. By 2018, India shopping discovery market size will be $2.4 billion, and US will be $21 billion. We are a global business and targeting to expand to other geographies like US by end of 2016.


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One comment

  1. 1

    Thank you Varnana for this article. I think we are many who has faced the problem that Shoppist are trying to solve. I hope they will raise funding soon so we can enjoy this service in greater extent.

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