Online gifting has certainly picked up a notch with the rise of e-commerce in India. So what does one do if they are at a point when they don't have a clue of what to pick for their friends or loved ones?
That's where Indian startup Wishpicker.com comes in handy. Founded in January this year by Prateek Rathore and Apurv Bansal--both IIT Delhi graduates, their idea came into existence from a personal experience they faced.
Wishpicker helps people decide what to gift when a special occasion is around the corner, it is a social gift recommendation engine that ources gift ideas and products from across the Web. Users can search for gifts based on their relationship with recipient, age, and occasion at hand.
"Be it a 'romantic' birthday gift for a 'geeky' boyfriend, under 1,000 rupees, or a 'creative' anniversary gift for middle-aged parents delivered within three days," said Apurv Bansal, co-founder of Wishpicker. According to Bansal, gift ideas are completely customized depending on the personality of the gift recipient, and the type of gift that the user wishes to give.
Their key offering is the gift recommendations they provide and their relevancy to what a user is looking for. You can find the ideal gifts for anyone at Wishpicker, on any occasion. You can also use the filters (price, personality, type of gift, delivery days, and etc) to narrow down your search results to find the best possible gifts fitting in your criteria.
According to Prateek Rathore, the other co-founder, the recommendation engine has two components--manual and algorithmic.
On the manual front their team manually curates the best products from differentWeb sites to ensure getting rid of "boring" or "traditional" products from their portfolio. Unlike , or other aggregators, where users know what they want to buy, users of wishpicker do not know what they want to buy or gift. They are here to get surprised by the gift choices, and hence manual intervention is critical, stated Prateek.
He said their unique selling point was the algorithmic recommendation engine. Once the gifts have been curated manually, and basic tags have been applied, their algorithm then incorporates about 80 parameters, which vary depending on the search query--relationship with recipient, occasion, age, and etc. Based on these parameters, and through machine learning, the algorithm shows up the most appropriate gifts--which would differ for each and every search query entered by a user.
They use analytics to make it better each day. Their algorithm learns a lot from user behaviour. They believe that users need social proof while buying a gift, and this algorithm incorporates the gifting behaviour of people and other trends to increase the accuracy of the results that are shown. Thus, the final results shown to the user are dependent on: parameters defined by the wishpicker team, and behavioral trends identified by analytics. These together help us make the best gift recommendations.
One of the good things for them is that they are early in this game. As of now they don't have direct competition. Indirectly, competition comprises of online gifting and flower Web sites but given the fact that these Web sites are primarily e-retailers for gift products, and do not focus on gift recommendations. Wishpicker has tied up with a lot of these Web sites to source gift products. Considering the value chain involved in gifting, they focus on solving the most relevant and largely unaddressed problem--deciding what to gift.
Wishpicker.com intends to help:
- People living outside their home looking to send gifts back home--these are young Indians from small towns who have jobs in Tier 1 cities, and expats who wish to gift relatives back home.
- People looking for recommendations for gifting their dear ones on a special occasion--these people are unsure about what to gift, and are looking for customized recommendations for the occasion at hand.
Their marketing is varied across SEO, viral marketing, social media and specifically targeting users during festive ocassions. The primary target market lies in the age group 16-35 years. The current target market is India. However they plan to expand globally very soon.