Smart, efficient, anonymous People Counters & Analytics to the real world.
Our solution allows for easy deployment, capture, analysis, and reporting of the number people who enter a physical place. Optionally, we can also capture and report occupancy in real time.
We assist Retailers, Universities, Casinos, Places of Worship, Office Buildings, and other industries in analyzing and taking action on their people traffic trends.
We offer a special package for retailers to measure performance on traffic, including conversion rate and service levels. Our direct integrations make it easy to combine POS data with staff data. The Retail Equation simulator lets users run simulations to improve sales. It can also be used as a learning tool to understand how traffic, staffing, conversion rates, and quality service relate.
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Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.
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BestPlace
BestPlace is an innovative platform that utilizes AI-driven predictive geo-analysis to assist businesses in pinpointing the best locations, anticipating performance outcomes, and gaining insights into consumer behavior through extensive data evaluation. It amalgamates various data inputs, such as population density, movement trends, shopping habits, and geographic characteristics, to provide a detailed understanding of how individuals engage with physical environments. This tool empowers businesses to assess potential sites by estimating revenue, pedestrian traffic, and audience reach at a detailed level, enabling leaders to evaluate different locations and their commercial viability before making investment decisions. Employing machine learning algorithms, it examines over 60 factors, including access, infrastructure, and competitive landscape, to produce precise predictions and practical guidance. By converting intricate datasets into understandable insights, BestPlace supersedes traditional research approaches and spreadsheet analyses, ultimately streamlining the decision-making process for organizations. Moreover, its capabilities enhance strategic planning, ensuring companies can adapt to evolving market demands effectively.
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Pensa
Pensa identifies and alerts on stock shortages while also forecasting potential low inventory levels. The platform gathers actionable data in real-time, ensuring it is collected more quickly, often, and with greater precision, all at a reduced expense. It enables comparisons of a leading brand's shelf performance against its rivals regarding stockouts, shelf share, and other factors that could affect revenue. Gaining insights into how consumers or third-party pickers substitute your products during stockout scenarios is essential for fostering your incremental growth. By providing a comprehensive view of actual consumer choices among your brand and competitors, Pensa’s ongoing shelf signal offers invaluable insights at scale. Errors in POS and perpetual inventory data that feed into your demand forecasting models can create significant challenges further down the line. By integrating Pensa’s real-time shelf signal with historical indicators such as POS data, businesses can reveal the true demand levels, facilitating the correction of inventory discrepancies and enhancing the reliability of demand forecasts. This approach ultimately leads to more informed decision-making and improved operational efficiency.
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