1/10 The Idea: It all started with a personal problem.
Working on projects involving geolocation previously, we had to build lots of internal tools.
We saw:
Companies collecting huge amt of lat/longs BUT
not having the right tools to use this data in operational decisions.
2/10 First round of validation: ~50 companies.
Found out that~
Internal tools were:
1. Needed eng bandwidth to update
2. Painful to maintain
3. Didn’t give localized, real-time insights
Business users keep waiting for dashboards for engg. sprints & metrics from analyst teams
3/10 Premise:
“Getting insights on ground operations for city/ ops teams should be as simple as getting insights on websites for marketers.”
To customize decisions based on how areas behave.
We packed our bags, quit jobs to move to a new city. @localeai was born in March’19.
4/10 MVP -> PoCs:
Rishabh hooked together our first MVP (a prototype in 3 days).
We demoed that to get some PoCs with top delivery startups in India.
Countless hrs. in their offices + 16 In-depth interviews gave us our:
1. Pain points
2. ICP
3. Solution
4. Positioning
5/10 Fundraising: With these answers, we needed to start building the product now.
For the product, we needed engineers
For engineers, we needed $$$
For $$$, we needed to raise
Fundraise is a complete sine wave on its own. We finally closed our pre-seed from Better Capital!
6/10: Now what?
We always wanted to be a product-led company:
Try Locale, get the feel, decide value.
We underestimated the complexity in building data pipelines at large scale, high freq & combining data from:
1. marketing events
2. supply pings
3. order transactions
7/10 Postponing 1st launch~
V1 ready after 4 months. But,
After deploying it for India’s largest micromobility co, users didn’t know
“which metrics to create” & “what to measure”.
Part of it was bad UX!
We realized we needed to make the process of getting insights simpler!
8/10 v2’s philosophy:
Help users make decisions by showing the right metrics.
We picked our target industries -> wrote top decisions -> mapped each decision to top metrics.
Different decisions required diff visualizations + diff metrics.
v2 was so actionable & insightful!
9/10 Validating v2:
I started our cold outreach & doing demos of v2 while the team got down to building!
Lockdown helped us do ~70 demos in 2.5 months.
We got lots of nice feedback & rejections.
Now, we’ve engineered some solutions into the product to combat those rejections
10/10 The Grand Launch: We are finally ready to present @localeai to the world.
Product launch is like a marriage proposal:
You want a positive response + you’re scared of failure + nervous about everything else.
Product’s not perfect but I’m proud of how it turned out🥺
