
Percolata
All-in-one hardware and software solution that helps retailers predict in-store traffic and staff employees accordingly.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor investor investor investor investor investor | €0.0 | round |
investor investor investor investor investor investor | €0.0 | round | |
investor investor investor investor investor | €0.0 | round | |
investor | €0.0 | round | |
investor | €0.0 | round | |
investor | €0.0 | round | |
N/A | $9.6m | Early VC | |
Total Funding | 000k |

USD | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | - | (44 %) | - |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Percolata leverages machine learning to provide predictive analytics solutions that help organizations make smarter marketing and operations decisions. The company specializes in forecasting sales, takeout orders, in-store traffic, and occupancy on an hourly basis for each store. This enables businesses to optimize staffing and delivery levels precisely when customers need the most assistance. Percolata's proprietary deep learning technology allows marketers to optimize their marketing budgets to drive more sales to both physical and virtual stores. The company serves global clients, including retailers and restaurants, who benefit from increased revenue and higher ROI through optimized campaign mixes and staffing solutions. Percolata operates on a 'no upfront payment' model, offering a fully managed Forecast as a Service solution. Clients have reported a 10% to 22% increase in same-store sales and a 4x higher accuracy rate compared to existing competitors. The business model focuses on delivering value through data-driven insights, enhancing customer satisfaction, and boosting sales.
Keywords: predictive analytics, machine learning, sales forecasting, staffing optimization, marketing budget, deep learning, retail, restaurants, Forecast as a Service, customer satisfaction.