Creativity is finding solutions to problems with limited resources : AMA with Aditi Sinha (Cofounder Locale.ai)
A deep dive focussing on product, challenges, learnings and Aditi’s advice to other young entrepreneurs
About Locale.ai
Locale.ai is a real-time operational analytics platform using location data.
It converts the location data of demand (users), supply (vehicles, riders) and static locations (stations, warehouses), and converts them to meaningful insights. The idea of locale came from the own challenges which were faced by the founders in their previous company SocialCops
Now without wasting any time, lets go straight to our questions :
Q. If a product like Locale existed when you were working at SocialCops, what benefits could have brought it there?
At SocialCops, we had to build our own internal tools because there weren’t any suitable analytics tools for geolocation data. This is also when we realised that companies of all shapes and sizes are collecting a huge amount of location data and they themselves didn’t have the right products.
So, if a product like Locale.ai existed back then, it would have helped at SocialCops spend more time running analysis & getting insights rather than spending time processing the data.
Similarly, if a company uses our product, the business teams and decision-makers can get the right insights at the right time, without any compromise or dependency. Analysts can spend time-solving business problems, rather than writing queries and putting together reports.
Q. How does Locale.ai converts location data into the right insights? Does locale.ai only use the location data a particular firm collects or it curates all sorts of data obtained from different firms and the data vendors associated with it?
At Locale.ai, we are building a location analytics tool for city and business teams for companies with ground operations. Think of us as Google Analytics for demand, supply, and ground operations that converts your raw location data into actionable, real-time insights. Companies typically collect location data in four ways:
- User data from an event analytics tool like Mixpanel or Clevertap,
- Ping data from vehicle sensors
- Rider app stored in S3 or Cassandra
- Order transaction data in Mongo or PostgreSQL
We ingest all of this, bring it all into one place and aggregate in the form of hexagonal grids of different sizes.
We started by focusing completely on company’s own internal data but have started working on a data marketplace where we would external data available that you can overlay on top of your internal data. So, we are establishing partnerships with data vendors in this regard.
Q. How has your experience been as a super young entrepreneur and any problems that you might have faced any time during the journey?
The community is overall very helpful, if you are passionate about your problem and know the problem deeply.
The challenges were primarily personal:
How do we grow and learn things as fast as possible, Whether it is building a product, selling to companies, or managing a team.
In my experience, doing your homework and reaching out to people who are best in what you are trying to learn with specific questions and asks always helps. If you don’t do your homework, you mostly end up getting generic advice which is not very actionable.
Q. Did you need to pivot anytime during the journey? How did you collect customer feedback in the initial days?
Of course! We went about it through a different approach.
We first validated the problem by just talking to as many customers as we could all over the world.
Post that, we built a prototype (and made it feel like an actual product) that we showcased to different companies. We then picked up some of the fastest-growing on-demand companies to do short PoCs, which helped us to spend hours in their offices, taking interviews and talking to different personas of people. This helped us go into a lot of details on what the problems are, who has the problem etc that we used to build our MVP and then our product. So, we essentially built an MVP after 4 months of starting up!
Q. Since locale.ai is a B2B model, what do you think are additional challenges of the same and how can a B2B model gain early customer feedback?
Problem: Finding that problem which a large number of companies face, in a recurring way that could be productised
Solution: Making sure your solution solves the problem that you finally decide to go with and customers are willing to pay for it.
Persona: Who is your buyer and who is your user? Which industries are you targeting?
Value: If you are selling to an enterprise, typically you showcase value with a PoC or a pilot. However, in the case of mid-market and a more self-serve approach, how do you ensure your customers find the value in the first 10 mins?
To gain customer feedback, just have in-depth interviews with your potential users. Ask them if problems like these are important for them, have they tried to solve it in-house and what have been some of the challenges with that. These questions will give you a very clear picture of where the gaps are and where your product can fit in.
Q. Did Locale.ai made any changes in the operations during Covid 19? With the growth in online delivery how is the company handling the surge?
Since the outbreak of Covid, delivery and logistics companies have been reaching out to us to adopt location intelligence. We have been helping them manage demand better and become more operationally efficient. Some very interesting use cases that we have seen companies adopt:
- Analysing the gaps in demand and supply with root cause analysis
- Monitoring of KPIs( Key Performance Indicators) in real-time & getting alerts of anomalies
- Setting up alerts in case of deviations, halts & bottlenecks
- Expansions based on latent demand & user churn
- Understanding order patterns in last-mile delivery
- Identifying which areas are SLAs not met and why
- Debugging where and in which step is the most cost incurred
Q. How are the WFH days for locale.ai? How are you guys ensuring proper communication and any special challenges that you feel Covid have brought in the day to day functioning of the firm?
Work from home has been hard, for a team like us who loves to work together, brainstorm on a whiteboard, and share conversations over dinner.
However, the definition of a startup is that we adjust to ever-changing situations. Some things that have worked with us in the past few weeks during this lockdown have been:
AMAs: We had Nachiketas from Accel, Vaibhav, our investor, from Better Capital, Arpit from Appsmith do AMAs with the entire team.
Projects Beyond Work: We encourage everyone to have side huddles and do projects other than work.
Workshops: We have been having workshops internally conducted by different team members on topics such as how to use figma or Notion, how to plan your financials better etc.
Q. Any message that you would like to give to young entrepreneurs that would motivate them to step forward to chase their dreams?
Problem: Love the problem dearly, it will make the hard days easier. We saw how the process of getting insights about operations & movement is broken at almost every company & how it’s just waiting to be solved. If we don’t solve it, someone else will.
Mentors: We didn’t just take advice. We asked questions, showed that we know what we’re talking about & along the way, we met people who helped us out in all possible ways: our mentors, investors & advisors.
Inspiration: Like everything else, staying inspired & motivated requires effort. On the very hard days, my inspiration comes from within: My personal goals & the opportunity to be working on something from scratch help keep me afloat!
Being Creative: I read somewhere that creativity is finding solutions to problems with limited resources, money & time. Even in times of crisis, we’re trying to find unique opportunities & leveraging them frugally. Frugal requires more effort, but it’s long-lasting.
Q. What traits/ qualities do you look while hiring members for your team?
We are looking for two broad qualities:
- Skills: We are looking for some of the smartest people, who are good at what they do & most importantly can learn fast! We go through a rigorous interview process to understand how someone thinks about problems. Can they think fundamentally? Can they explain in clear words?
- Culture: In terms of culture, we are looking for people who can build this company with us. This just means doing whatever it takes to make things work!
I have written more about it here:
