A Q&A with Wishpicker co-founder Apurv Bansal. The New Delhi, India-based startup, which offers a gift recommendation service for the Indian market, launched out of beta earlier this month. It was founded in 2012 by Bansal and Prateek Rathore.
SUB: Please describe Wishpicker and your primary innovation.
Bansal: Wishpicker is an exciting new startup that helps you figure out what to gift. This is an extremely useful product that provides great gift ideas to anyone unable to figure out what to gift when a wedding or anniversary is around the corner.
Gifts are curated from the best online stores, and this helps the user get access to the best that is available across the web, all at one place; essentially, a one stop shop for the best gift ideas. They can choose from a wide range of gift products, gift vouchers, experiential gifts, etc. Users can also filter results based on personality, budget, type of gift and various other parameters.
We have 20 ecommerce partners as of now, including Flipkart, HappilyUnmarried, Ferns N Petals, etc. We plan to increase the number of tie-ups soon. To ensure that if someone comes to Wishpicker looking for a gift does not go away disappointed, we incorporated machine learning in our gift recommendation algorithm. Wishpicker’s algorithm reads user insights, and becomes more-and-more intelligent as the number of people using it increases. As a result, we are able to maintain a conversion rate much higher than that of vanilla ecommerce stores.
SUB: Who are your target markets and users?
Bansal: Our target market is currently Indians—both resident and NRIs—in the age group of 18-to-40. People struggle with finding the right gift for their loved ones, and are looking for someone to aid them [to] find a good gift. Also, a lot of people living away from their homes are usually looking to send a gift back home to make their loved ones feel special on important occasions. We are looking to target both of these segments.
Bansal: The online gifting market is about 12-to-15 percent of the total e-retail market. Most of this takes place on vanilla ecommerce sites—both niche and horizontal—and hence these are our biggest competitors. Our focus is to create an intelligent layer on top of these websites, and make the purchase decision of people easier by helping them decide what to gift. We have built a highly-efficient gift recommendation algorithm that incorporates machine learning to help people figure out the perfect gift for their loved ones.
SUB: You just launched out of beta. Why was this the right time to launch?
Bansal: When [we] did a beta launch, our primary aim was to launch a prototype and see if people find any use for the product that we have built. We noticed that people found value in what we were trying to build, but our product was far from what the market needed. We had to redo a lot of things and work towards achieving product-market fit. We launched out of beta when we were confident of having achieved product-market fit.
Bansal: Wishpicker.com was launched in June, 2013 by Prateek Rathore and I to fix the broken gifting market. I [was] an IIT graduate looking to gift my girlfriend on her birthday. I searched online for ideas, but was overwhelmed with the large number of options that came up. With every website claiming to sell the best gift, I got mighty confused. Around the same time, Prateek, my batchmate from IIT, was pursuing his management studies at IE Business School in Spain. He was looking to send a nice anniversary gift back home to his parents. He turned to the Internet, but returned disappointed. He had to call up his sister, and asked her to buy a gift from the mall.
We had always wanted to start a venture of our own, and spoke about this. We realized that this was a problem faced by a large number of people on a regular basis. Prateek, a computer engineer, knew that he could use technology to help people figure out what to gift. He convinced me to quit my high-paying corporate job at Bain & Company in Mumbai and return to Delhi. Prateek completed his course in Spain and flew back home.
In early-2013, we began working on our venture from the terrace of Prateek’s parents’ flat in Delhi. Soon after, we roped in Tejendra Singh as a core technology member, and there has been no looking back ever since.
SUB: What were the first steps you took in establishing the company?
Bansal: Finding a place we could call office: Cleaning it, arranging furniture, registering a company, tapping into our network to build a team, doing magic.
SUB: How did you come up with the name? What is the story or meaning behind it?
Bansal: The concept behind the name was fairly simple. We wanted the name to directly reflect what we are doing, which is helping people ‘pick’ the right gifts for their loved ones; hence the name ‘Wishpicker.’
SUB: Have you raised outside funding to this point?
Bansal: Started with a Seed capital of 15 lacs, which we put in from our personal savings. Funding is also on the cards for us—we are in [an] advanced stage of talks with a few investors. We are waiting for the right time, but it will happen soon.
SUB: What have the most significant challenges been so far to building the company?
Bansal: The biggest challenge was in building the right team. Without a great team, your business is destined to fail. At a startup, you will never be short of work, and will constantly feel the need for more people. The key is to not hire in a hurry, and make sure that the candidate is not only talented and hardworking, but also fits in well with the culture of the company. An additional team member may help you take a step forward, but a wrong hire will push you two steps behind.
SUB: How do you generate revenue or plan to generate revenue?
Bansal: Customers are redirected to our partner websites when they select a particular gift. The partner portal pays us a commission for every transaction that is processed on their website via Wishpicker. The consumers do not have to pay a penny extra.
SUB: What are your goals for Wishpicker over the next year or so?
Bansal: A host of new features shall be rolled out over the next six months. We are launching a dedicated mobile site very soon. We are building a social layer on top of our current recommendation algorithm—this will enable us to crowdsource gift recommendations. Apart from these, we shall introduce email gifting and gift registries.
The problem that we are trying to solve—deciding what to gift—is intrinsically global in nature. We have an extremely scalable model, given that we are completely cloud-based. As a result, we plan to expand internationally soon after cracking the Indian market—around Q3.