Buying a home appliance, like a TV, refrigerator or a washing machine, can be an overwhelming experience for many. First, users are boggled by the marketing jargon. Then matching them with the actual requirements can be quite overwhelming. Overall, it takes most laymen anywhere from a week to two months to finalize a choice.
Solving this problem, the brother-sister duo Rashin and Parvathy Pothan have come up with the idea of a chatbot that is essentially a personalized buying adviser. Users can tell their requirements to the Chatbot and, by processing through a database of home appliances, the Chatbot helps them find the right models that match their requirements. Finally, it narrows it down to one or two options that the user can choose from.
Rashin and Parvathy, who run Smart Home Guide a home appliance review and price comparison portal, stumbled upon this idea when they started receiving plenty of emails and comments seeking personalized recommendations for choosing appliances like refrigerator, TV, washing machine and AC.
Parvathy says, “Though we have detailed buying guides in our website helping readers understand about important features and aspects to consider while buying major appliances, we are unable to provide timely personalized recommendations to all. We often receive emails like, ‘We are a joint family of non-vegetarians. Can you recommend a side-by-side refrigerator suiting our needs that doesn’t consume much electricity?’ We try to respond to all emails and comments. But it is quite a time consuming, especially when we get about 40 to 50 emails a day.”
During a brainstorming session, the founders were discussing about possibilities of automation. Rashin, who is basically a developer who has built chatbots for various businesses in Australia and the USA, proposed the idea of developing a chatbot providing personalized buying recommendations. Surveys were quite positive, and the technical team, comprising of three members headed by Rashin, is now working on it. The team expects to launch the first prototype on Facebook Messenger and their website by September. Revenue will be mainly through affiliate commissions from e-commerce websites.
Rashin says, “Though the platform is ready, developing recommendations matching various features and functionalities with customer requirements require a lot of planning and mapping. The artificial intelligence employed by the Chatbot also learns from user feedback to improve its answer and, thus, refine the user experience. Overall, it requires a lot of information input in the initial stage.”
The present platform that includes price comparison and review was launched two years back and is completely bootstrapped. For the past six months, it has been breaking even too. The founders have been mainly relying on their personal savings for the Chatbot development and are in talks with a few investors for funding too.