🦄 Unicorner Startup of the Week:

dataplor

✍️ Notes from the Editors

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Data is everything in making business decisions—but sometimes, the data you need isn’t at hand.

dataplor is uniquely leveraging AI to enrich location data, ultimately building one of the most robust location intelligence platforms out there. Hope you enjoy this week’s deep dive!

- Ethan and Arek 🦄

Leading provider of global location intelligence

dataplor is a global location intelligence provider serving businesses with location data to help them make data-driven decisions and extract insights. It leverages AI and ML technology to extract, ingest, and process geographically tagged information worldwide on consumer behaviors, brand sentiments, and more. dataplor combines this technological approach with over 100,000 human validators to ensure data is high quality and up-to-date. dataplor’s vast data allows businesses to understand their competitors, effectively scale into new markets, support investment decisions, and more.

🔗 Check it out: dataplor.com

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💰 Business Model

dataplor licenses its data to firms through an annual Data-as-a-Service (DaaS) subscription model. dataplor offers subscription plans with variable pricing based on the country, regional, or global scope of data access, along with the length of the often multiyear licensing deal. It primarily focuses on selling to Fortune 500 firms in the retail, mapping, logistics, restaurants, fintech, and packaged goods spaces.

📈 Traction and Fundraising

• Raised a $10.6 million Series A round, led by Spark Capital

• Amassed over 250 million points of interest across 200+ countries and territories

• Licenses location data to over 35 Fortune 500 brands, including American Express, PayPal, and Coca-Cola

• Averaging 2.5 times year-over-year revenue growth since 2020

👫 Founders

• Geoff Michener, CEO: Previously Contributing Writer @ Forbes, Consultant @ Acquisio, COO & Founder @ ProspectWise, Business Development Team Lead @ LivingSocial

📖 Founder Story

dataplor CEO Geoff Michener began his career working in the geospatial sector for the government but soon founded ProspectWise, a company providing data on small businesses in the U.S., which was acquired. After connecting with his mentor, Matt Graves, former head of DataAxle, Geoff realized that although there are around 450 million businesses globally, the vast majority of data is only available on U.S. and Canadian businesses due to poor global data quality. Leveraging his experience at ProspectWise, Michener set out to tackle this issue, building an MVP in Mexico, where he verified local business information directly with local workers. While his MVP quickly scaled into dataplor, his combination of human effort with technology was an ethos that remained in the company’s DNA.

🔮 Our Analysis

For businesses making decisions, data is gold—it allows them to more effectively call the right shots and mitigate the risks of incorrect choices. Location data, specifically, is even more valuable to firms, as it allows them to make location strategy decisions. For example, a firm can leverage dataplor’s point of interest data to understand the retail strategies of their competitors or uncover untapped markets, thereby allowing them to effectively make decisions to scale and grow revenue. Despite this thirst for data, it remains expensive for businesses to collect and process such vast amounts of data in-house, while a third party like dataplor can scale beyond these costs by selling to multiple enterprise customers through subscription plans at a significantly lower relative cost. With dataplor’s emphasis on consistently adding data to stay up-to-date, its subscription model is enticing for firms, who need real-time data for decisions.

Furthermore, with AI rapidly becoming a major force in driving business decisions, dataplor’s value proposition is stronger than ever: LLMs and other AI models require vast amounts of data to be trained on and dataplor stands to benefit by selling the underlying data that these increasingly popular technologies rely on. The rise of AI also democratizes the usefulness of data: using AI models, smaller firms can now cheaply extract business insights from data that would have historically required expensive human data science teams. With AI models only improving at extracting insights, demand for dataplor’s data will continue to rise, specifically for smaller businesses. Naturally, the usefulness of data—to both human business teams and AI models—relies on its quality, and dataplor sets itself apart from other vendors by ensuring data quality by combining technologically advanced data collection methods with human validators for quality control. In this rapidly evolving landscape where businesses of all sizes are digging for insights, dataplor is well-positioned to be the one selling shovels.

📚 Further reading

• For dataplor’s data intelligence tool, it’s all about location, location, location [TechCrunch]

• dataplor’s Blog [dataplor]

• How Wolt Strengthened Their Selection Insights with dataplor [dataplor]

Written by Rohan Desai

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