<aside> 👑 Airboxr’s fundamental idea is that business leaders in comparable companies tend to make similar decisions. While they rely on data for these decisions, they are not data analysts themselves. These decisions have been made by thousands of peers in the past, so there is no need for them to start from scratch.

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Product Video

https://youtu.be/JGiEMUvCiKI

Link to video: https://youtu.be/JGiEMUvCiKI

Who we are.

We are a team of second-time founders:

• Saptarshi launched India’s first online recommerce marketplace, ran big-data studies for F100 companies, and advised deep-tech startups on GTM and fundraising.

• Shubham designed data infrastructure for Bangladesh’s biggest online grocery delivery brand.

• Salima, our Head of Product Marketing built her own independent artist project to over 7,000 followers and 900k streams on Spotify. She’s also an ex-entrepreneur in the events and entertainment space, with extensive experience in community-building.

  

The problem.

Business leaders ****are tasked with making decisions driven by data. But they aren’t data analysts themselves. They depend on external tools, spreadsheets, and—as they grow in their careers—on data analysts. Within direct-to-consumer businesses, the problem is more pronounced by the fact that data is spread across multiple sources: sales channels (like Shopify, Woocommerce, and Amazon), ad channels (like Meta, Google, and TikTok), and email platforms etc. Worse, a large proportion of this audience often doesn’t even know what questions to ask to find the right answers.

This leads to:

• Manual data wrangling and busywork to collate data into spreadsheets.
• Repeating the process every week for weekly reviews.
• Decision fatigue within key decision-makers: they eventually don’t make a decision at all, or make a gut-based decision without depending on data.

How do we solve it?