
Lebesgue
Lebesgue – Redefining online advertising performance with mathematical and statistical models..
Date | Investors | Amount | Round |
---|---|---|---|
N/A | €0.0 | round | |
* | $3.0m | Seed | |
Total Funding | 000k |
USD | 2021 | 2022 | 2023 |
---|---|---|---|
Revenues | 0000 | 0000 | 0000 |
% growth | - | 106 % | 18 % |
EBITDA | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Lebesgue.io is a cutting-edge company specializing in optimizing online advertising through advanced artificial intelligence (AI) and mathematical models. The company primarily serves businesses looking to enhance their online growth and advertising efficiency. Operating in the digital marketing and advertising sector, Lebesgue.io leverages its deep expertise in mathematics, statistics, and data science to provide actionable insights and strategies for improving customer lifetime value (LTV) and optimizing customer acquisition costs (CAC).
Lebesgue.io's business model revolves around offering enterprise-level services that include custom LTV models, churn prediction, and revenue forecasting using state-of-the-art neural networks. The company generates revenue by providing these specialized services to clients who seek to maximize their advertising budgets and achieve sustainable growth.
The team at Lebesgue.io includes former Google engineers and some of the best growth hackers in Europe, bringing over a decade of experience in leading tech teams and managing substantial advertising budgets on platforms like Facebook and Google. This extensive background allows them to understand the core mechanisms of online auctions and deliver personalized AI insights to improve advertising performance.
Keywords: AI models, online advertising, customer lifetime value, scalable growth, mathematical models, statistical analysis, churn prediction, revenue forecasting, digital marketing, customer acquisition cost.