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The future of retail: Video data analytics and AI applications

The global retail industry is experiencing a significant transformation, fueled by advancements in Artificial Intelligence (AI), particularly through customer behavior recognition via video data analytics. This capability enables retailers to better understand consumer needs, optimize shopping experiences, and enhance operational efficiency. In this article, we will explore how behavior recognition through video analytics has revolutionized the retail sector, the challenges it presents, and solutions from BPO.MP to overcome these issues.

Applications of behavior recognition and benefits for retail

Retail businesses heavily depend on efficient customer service operations and optimized marketing strategies. Both physical and online stores are now leveraging automated data analysis tools to predict customer demands in real time, based on shopping history and responses to marketing campaigns. This allows businesses to precisely address customer needs, enhance shopping experiences, and make more informed business decisions, such as inventory management and marketing planning.

Behavior recognition via automated systems, especially video analytics, brings numerous advantages to retail businesses. This technology helps retailers:

Analyze in-store shopping behavior

AI-powered video analytics can track customers’ movement paths in stores, identify areas where they linger the most, and analyze product interactions. For instance, Walmart’s AI Retail Lab project utilized AI to monitor and analyze customer behavior in their stores. The system combined data from cameras and sensors to track in-store activities, from inventory levels to customer foot traffic. All collected data was sent to a central data hub for analysis, enabling decision-making to improve customer experiences, enhance customer understanding, and boost store revenue.

>> You might be interested in: The Future of Artificial Intelligence: Data Shaping the Digital World

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Walmart’s AI Retail Lab project utilized AI to monitor and analyze customer behavior in their stores. (Source: Walmart)

Enhance store design layout

Insights from behavior recognition systems provide detailed information about traffic flow and popular areas in the store. Retailers can redesign and rearrange their stores to optimize space and increase product accessibility, ultimately boosting sales. For example, by monitoring real-time customer flow, store managers can adjust the opening of checkout counters or customer service desks to reduce congestion and shorten waiting times in the customer journey.

Improve security and manage shrinkage

AI video applications not only enhance customer experience but also improve store security. According to the National Retail Federation (NRF), shrinkage accounted for approximately $112 billion in losses in 2022, with theft being a major contributor. AI-powered video systems can detect suspicious behaviors, such as loitering in certain areas, and alert security teams to mitigate risks promptly. Currently, over 50% of retailers are using AI video systems to minimize such risks.

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According to NRF, shrinkage accounted for approximately $112 billion in losses in 2022, with theft being a major contributor.

Optimize inventory and sales

Retailers can analyze inventory levels at displays through video data analytics from cameras. This helps identify which products sell well and which receive less attention, enabling informed decisions about restocking or repositioning items. For instance, moving slower-selling products to eye-level shelves or high-traffic areas can attract attention and boost sales.

Challenges and solutions from BPO.MP in retail video data analytics

Despite the vast potential of video data analytics in retail, its implementation presents several challenges. However, with effective solutions, businesses can overcome these obstacles to optimize operations and enhance customer experiences.

Ensuring data quality and diversity

To ensure accurate processing and analysis, video data must be collected from various angles and of high quality. Blurry, noisy, or poorly lit footage can confuse systems and reduce the accuracy of behavior recognition models.

After collection, data must be cleaned to remove noisy, blurry, or incomplete frames. At BPO.MP, we utilize advanced technologies to process and standardize data, ensuring the highest input quality for AI models. Additionally, our premium data labeling processes, combined with a team of experts, minimize errors and accelerate data processing, even for large-scale projects.

>> See more: Data Annotation: A Breakthrough in E-Commerce

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Blurry, noisy, or poorly lit footage can confuse systems and reduce the accuracy of behavior recognition models.

Real-time processing

In the retail sector, quick decision-making is essential for competitiveness. However, processing large volumes of data in real time requires robust hardware and software systems. These limitations can cause delays in data analysis, affecting model performance.

Data privacy and security

With stringent regulations like GDPR (Europe) and CCPA (US), collecting and using video data must adhere to high security standards. Businesses face not only legal risks but also the challenge of protecting customer privacy and building trust.

BPO.MP employs ISO 27001-certified security protocols to help businesses meet strict privacy requirements while protecting sensitive data comprehensively. By combining advanced technology and a skilled team, our solutions enable businesses to optimize video data for improved analysis and performance in retail.

To fully leverage the potential of video data, businesses must invest in modern technologies and comprehensive data processing workflows. With extensive experience in BPO and AI research, we are ready to assist businesses in collecting and processing video data, creating highly effective and secure AI solutions. Let BPO.MP help shape the future of retail with you!

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BPO.MP COMPANY LIMITED

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