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🥺
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