Pygmalios Analytics

Pygmalios Analytics

Financials

Estimates*

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Revenues, earnings & profits over time
EUR2017201820192020202120222023
Revenues<1m<1m<1m1.1m1.3m<1m<1m
% growth349 %304 %41 %9 %16 %(36 %)-
EBITDA(<1m)(<1m)(<1m)(<1m)(<1m)(<1m)-
% EBITDA margin(330 %)(57 %)(19 %)(20 %)-(4 %)-
Profit(<1m)(<1m)(<1m)(<1m)(<1m)(<1m)-
% profit margin(364 %)(73 %)(30 %)(31 %)(13 %)(32 %)-
R&D budget<1m<1m<1m<1m---
R&D % of revenue57 %56 %70 %64 %---

Source: Dealroom estimates

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DateInvestorsAmountRound
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Seed
Total Funding-

Recent News about Pygmalios Analytics

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Pygmalios is a real-time in-store analytics platform designed to provide actionable business insights for the retail sector. The company specializes in tracking and analyzing customer behavior within physical retail environments, offering detailed data on footfall, demographics, and queue analytics. Pygmalios serves a wide range of retail clients, from small boutique stores to large chain retailers, helping them optimize their operations and improve customer experiences.

Operating in the retail analytics market, Pygmalios employs a subscription-based business model. Retailers subscribe to the platform to gain access to various analytics modules that provide insights into customer behavior, store performance, and marketing effectiveness. The company generates revenue through these subscriptions, which are tiered based on the level of service and data access required by the client.

Pygmalios' platform integrates seamlessly with existing Point of Sale (POS) systems, enabling retailers to correlate sales data with in-store customer behavior. This integration allows for a comprehensive understanding of how marketing campaigns, store layouts, and staff performance impact sales and customer loyalty. By leveraging advanced analytics, retailers can make data-driven decisions to enhance customer satisfaction and increase sales.

Keywords: in-store analytics, customer behavior, footfall tracking, demographics analysis, queue management, retail optimization, POS integration, marketing effectiveness, customer loyalty, data-driven insights.

Tech stack

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