We have launched finally and you can find our product and are proud to present to you: Locale.ai! Use this link, you choose your industry and your job role and experience what Locale has to offer for your business.
I have always felt that a product launch is like a marriage proposal- you want a positive response, you’re scared of a failure and you are nervous about everything. That makes the pre-launch like a preparation of the proposal.
But this preparation also gives a good excuse to sit and reflect through this one hell of a journey with all its ups and downs, sometimes all in a day. And also to express gratitude to everyone who has helped us in any small way to get here– especially our team members, to whom we dedicate this piece.
Taking the Plunge
A very common question thrown at me is, "How did you come across this idea?"
My friend and now co-founder, Rishabh had lived through this problem first hand. At SocialCops, Rishabh had worked on a wide range of projects with Government Ministries, FMCGs, startups and supply chain companies on different business problems related to location.
While Rishabh himself had to build quite a number of internal tools for his day-to-day workflow, we also realized that companies of all shapes and sizes are collecting a huge amount of location data and they themselves didn’t have right products to leverage this data. Often, they had to build internal products which were extremely painful to use as they were not well-maintained.
It was then we started asking ourselves questions like– "Why do companies need to come to us to crunch their data and solve their problems? Can we build a product to empower local teams inside these companies to solve at least some of these problems on their own?"
"Right now, to get any insight, I need to depend on my analyst teams to write queries– A process that takes 24 hour to 48 hours. To get a live dashboads, I need to depend on my engineering teams which usually takes a sprint."– PM, Shadowfax
We then set out to validate this problem: We spoke to around 50 companies or so all over the world asking them all kinds of questions about what insights they use from their location data, which tools do they use and what kind of decisions they took. Their answers gave us the much needed confidence we were looking for!
And that's how the journey started, both of us, packed our bags and moved to Bangalore with this vague problem statement in our mind and a head full of dreams.
March 2020: The Birth of Locale.ai
This desire to fix this “problem” led us onto a journey that gave birth to "Locale.ai". The journey was, and continues to be an emotional roller coaster: we question ourselves every day and that is what I love about our journey- the questions it makes us ask.
It is a common misconception that starting up is the hardest part there is, but I’m sure that any entrepreneur who has built a business will agree that starting up is by far the easiest piece of the puzzle. What comes ahead are the biggest hurdles to an entrepreneurial journey- the team building, reforming the product for the ideal user profile, and dealing with rejection.
Lap 1: Conceptualizing the v1 of the Product
While those customer calls gave us confidence of the problem, we were still clueless about the solution. So, there was only one way to find out – We demoed our prototype to some leading on-demand and mobility companies in India with that we bagged our first set of small PoCs.
These PoCs gave us an excuse to sit in their offices, brainstorm and interview our potential users. After all, we still had to find answers to questions such as– "What's the real problem? What's the current solution? What's the product going to be? Who would be the target user? How do we position it?"
To make these analyses, companies required engineers to create custom-made dashboards. But this approach to create internal tools came with two problems- the engineering team spent a lot of time and resources in creating these dashboards and the dashboards that were in use were not scalable. We learnt that companies wanted such a tool that business leaders could use to visualize the data regarding their on-ground operations instead of having to rely on answers to queries sent to the engineering teams.
"We were silently losing money on shipping but were not capturing that data because we lacked precise visibility into our true cost of shipping i.e. fuel adjustments and post-shipping accessorial charges. After Locale, we updated our shipping charges in realtime so we can maintain our margins and best serve our customers"– Praful Mathur, C0-founder, VNDR
While we were ready with all our answers to build our product, we now needed a team of engineers but were running out of our savings. We needed money and we needed to fundraise. The fundraise journey was a whole new ballgame in itself and deserves a chapter of its own. Here is a synopsis:
After a long, draining journey we were fortunate to have Vaibhav from Better Capital as our lead investor along with Pallav, Raveen and Steve as our angel investors.
Postponing the First Launch
While we started building our core team of engineers to start working on the product on one hand, we started working on positioning the product. Throughout pitching to customers, investors and advisors, we got asked to questions like– Why this focus on geo-location? Why a different product for location analysis? Are you building a BI for location data? Isn't this very core to companies?
Our challenge was that companies especially in the logistics or delivery sector hadn't seen a product like this. And some startups who were using open source tools knew the importance of something like this but asked us– "Why shouldn't we build this internally?"
So, in order to clear these doubts, we always knew the best way to go about it would be to let the product speak for itself. In other words, launch the product such that anyone from our target industries could get a feel of the product to comprehend the value. We assumed it would take us a month to build the end-to-end product along with real-time pipelines. And then, reality hit!
We seriously underestimated the line it would take for us to build the pipeline that can handle three different kinds of data: marketing data (user events), operations data (supply pings) along with order data (transactions) – all of this in real time and at scale!
Lap 2: Iterations. Iterations. Coming up with the v2
Fast forward, it took us roughly 3 months to build the first version of the working product. With this, Locale became a canvas for our users: they could create different metrics and consoles mixing and matching data across databases and get insights on their ground performance.
When we deployed the product for India's fastest growing scooter-sharing company, it was then it became clear to us that our users (city, ops and growth teams) did not understand what to search for and what to measure since there was no steel structure that guided them. (A part of this was of course the bad UX!).
We learnt that if we launch the product in this shape, people may still not get the value since we won't be there working closely with them to depict what all they can do with Locale. It was as if we had built a city but the visitors needed a tour guide to travel through the city and help them reach their destinations.
And with this, we extended our launch yet again and went back to the drawing board.
Side Note: Here's how they used our product to open their stations (hubs)
"Locale taught me that it doesn't matter who you are or where you come from, what matters is if we all are equally passionate for the problem. When you believe in a problem and are passionate about it, everything else takes a backseat."– Anubhav Pattnaik, Content Team, Locale
Shaping v2's Structure along with the Philosophy
What we did was pick up our target industries and wrote down the list of top decisions for them and map each of those decisions to metrics. For example, we ended up understanding the most important questions that a business team in a delivery company could ask were built around understanding demand-supply gaps, or where users drop off, or where they should shoot promotions.
The journey to overcome this challenge led to the birth of a set of analyses. Every analysis or screen of the product is composed of the top metrics that leads to a decision, thus making it very actionable for our end users.
While we got down to building this, we also started our cold outreach again and demoed this new product concept to our prospects and received tons of feedback. We used the top rejections we got and try to engineer a solution to combat that into the product.
I remember the days when I used to play around with QGIS and how complicated it felt. Building a geospatial platform for the web is hard and challenging because it demands to be accessible to cater for a wide range of user bases and devices. It's sure is difficult, but we proved it to be not impossible ✨– Musthaq Ahamad, UX Engineer, Locale
Lap 3: The Grand Launch of Locale
Now, after 15 months, 1000s of burning the midnight oil with a team of 7, we feel we are ready to present Locale to the world!
As a visitor, you can now log into the product, select your industry and your job roles and experience all that Locale has to offer– all the decisions and problems Locale can help you with its consoles and analyses.
We are extremely excited to welcome you, dear reader, to join us on this journey as we try to solve the mysteries of the geospatial world. We have one simple goal- to help you measure every location aspect of your business and make you operationally efficient.
We learnt countless priceless lessons while we were on this journey but if we just had one lesson to share with y'all it would be:
"Like Niel Gaiman said, Keep Making Good Art"– Rishabh