Prayas Analytics \USA

Prayas Analytics aimed to revolutionize the retail analytics space by providing in-depth insights into customer behavior through video analytics. By leveraging existing video surveillance infrastructure, the company promised retailers actionable data on customer foot traffic, dwell times, and interaction with products. Their value proposition centered around enhancing retail efficiency and optimizing store layouts to increase sales and customer satisfaction.

SECTOR Information Technology
PRODUCT TYPE AI
TOTAL CASH BURNED $120K
FOUNDING YEAR 2015
END YEAR 2018

Discover the reason behind the shutdown and the market before & today

Failure Analysis

Failure Analysis

Prayas Analytics succumbed to several strategic missteps. Firstly, their reliance on existing CCTV infrastructure meant varied video quality and hardware compatibility issues, which hindered...

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Market Analysis

Market Analysis

Today, the retail analytics sector is heavily influenced by AI and IoT convergence. Amazon's cashier-less stores set a new standard for data-driven retail experiences....

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Startup Learnings

Startup Learnings

Insight 1: The retail analytics market demands seamless integration with existing systems. Insight 2: Building a proprietary video processing engine is resource-intensive; leverage modern...

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Market Potential

Market Potential

The total addressable market for retail analytics remains significant as brick-and-mortar stores strive to compete with online retail giants. However, the market is now...

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Difficulty

Difficulty

The description indicates that Prayas Analytics is focused on providing services in the retail analytics space, suggesting they are still operating and active in...

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Scalability

Scalability

The scalability challenge for Prayas was twofold: handling large volumes of video data and ensuring real-time processing to provide timely insights. The unit economics...

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Rebuild & monetization strategy: Resurrect the company

Pivot Concept

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VisionCommerce would be an AI-first retail analytics platform leveraging cloud computing and edge AI to provide real-time customer insights without the need for extensive hardware overhauls. By using modern video analytics and machine learning, the platform could offer predictive analytics for inventory management and customer engagement strategies.

Suggested Technologies

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AWS RekognitionTensorFlowReact

Execution Plan

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Phase 1

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Step 1: AI-first prototype blueprint using existing video data to create a predictive analytics model.

Phase 2

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Step 2: Partner with a few retail chains to validate the hypothesis and refine data models.

Phase 3

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Step 3: Develop a scalable SaaS platform with a subscription-based pricing model.

Phase 4

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Step 4: Create a moat with proprietary AI models and integrations into major retail POS systems.

Monetization Strategy

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VisionCommerce would monetize through a tiered subscription model, offering different levels of data insights and analytics capabilities. Additional revenue streams could include consulting and integration services for enterprise clients, as well as premium features such as real-time alerts and predictive inventory suggestions.

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