My First Try At Entrepreneurship

So this journey started in June of 2020 amidst COVID 19 lockdown. I visited a hair salon only to find that the place was overcrowded. It was only after trying 5 salons, I got the job done. The process which used to take 20 mins usually, took more than 2 hrs & a large chunk of inconvenience. June 2020 was the month when COVID 19 was on an exponential rise. The whole country was in lockdown & social distancing was the buzzword. It is at that moment, I felt that this was something that would help people plan their visits to nearby essential services in a much safer way. The idea was to provide the real-time occupancy information of nearby services to the masses. I was pretty convinced that it would be an interesting project. Two of my friends too shared the same view & we started the project named Trufynd! A two-step process was designed to get the occupancy data of the shops. The first step was the Human Input, wherein the service providers would update the occupancy & provide with the wait time once a request for information is made by the customer. Using the combination of occupancy input & wait time, the estimated real-time information would be reflected by color-coding. The second step was to automate the data input process using a People Counting Sensor. The sensor would be placed at the entrance of the stores & would relay the real-time information. We built a prototype of the sensor & tested it inside our homes. We planned to give people counters to stores that hit a threshold activity/orders via Human Input.

We were building a data pipeline of people density wrt the time of nearby stores/services. Our hypothesis was that the value of this data pipeline would outweigh the costs involved (prototyping, servers, operations, marketing). Some of the possible revenue streams from this data could be providing analytics-based insights to aggregator firms (Dunzo, Udaan, Swiggy, JioMart, etc), locality-based real estate consulting to franchisees/businesses, marketing services to the nearby services, etc.

The mode of delivery of the obtained information was via a webpage & a native mobile app. We booked a domain & started developing the prototype, webpage & native apps. In the meantime, I designed surveys for quantitative & an experiment for qualitative idea validation. I targeted my locality market. The market consists of 3 Kirana stores, 2 Hair salons, 2 fast food joints, 1 Cybercafe & 2 Multi-Purpose Shops. The motive of running the experiment was to validate the need for occupancy information & its priority to users. The experiment was that I would stay in the market for a 4-hour window between 4–8 pm & would pass on the occupancy update to my locality families & tell them about the expected wait time. I passed my contact details to about 50 families in my locality. I planned to run the experiment for 3 days in a 4-hour evening shift.

On the first day, I sent a reminder to the sample families to try to use this service. In the initial hour, I got 8 calls & 3 Whatsapp texts. The next hour, the calls dropped to 6 & Whatsapp texts to 1. At the end of my first day, I had assisted 21 calls & 5 Whatsapp texts. Still, a lot of people who visited the marketplace didn't use the service. The next day, I decided to run the experiment without sending a reminder. The results were contrasting. I assisted only 10 calls & 2 Whatsapp texts. The most unexpected thing was that some of the users who used the service yesterday came to the market without asking for occupancy. Their predominant reply to this was “ Beta, aaj jaldi jaldi mein bhul gye, agli baar call krke aayenge.” The trend continued on the last day too & I assisted with 7 calls & 3 WhatsApp texts.

To sum up the experiment, I assisted with 38 calls & 10 WhatsApp texts in the 12 most active hours of shopping or about 4 calls & 1 text per hour. The most interesting finding was that majority of people who used this service once, didn’t feel the compulsive need to repeat the process. One more correlation I made was that in spite of the ongoing fears about COVID 19 & the expected rush in the 4–8 pm slot, people still found using this service a bit trivial.

I connected with a few mentors & incubators discussing idea validation. They provided two major downsides: (a) What after COVID 19? (b) The value proposition for the service providers was very weak. They suggested us to do something in addition to providing occupancy information like take online orders, provide delivery/manpower options, do online cataloging, etc. In my 12 hour experiment, I had talked in detail with the service providers & they echoed the concerns raised by the mentors. Using the results of the experiment & the surveys along with the learnings from talking to mentors & service providers, we decided that the underlying value proposition for service providers was weak & the need for real-time occupancy information from the consumer’s perspective looked a bit dicey. While talking to the service providers, I had figured out a problem related to retail operations & we pivoted to solving this problem. For more, follow on!