Video Surveillance Analytics: How AI Drives Greater Revenue

Every day, enterprise businesses generate massive amounts of visual data, all from their video surveillance systems. However, despite this constant stream of data, the vast majority of it goes unused. This leaves a wealth of valuable information untapped, information which can help unlock new operational advantages and drive greater revenue.

To optimize workflows through surveillance, organizations can leverage AI video analytics to uncover the hidden insights buried within these thousands of hours of video. AI cuts through system noise by automatically sifting millions of data points to pinpoint events and identify overall trends, helping guide business decisions that can be used to elevate operations. By shifting from reactive recording to proactive analysis, businesses can transform their video security systems into a powerful engine for business intelligence.

The Areas Impacting Business Operations

Enterprise businesses face a multitude of daily challenges that impact both the bottom line and customer experience. Without a way to automate video analysis, unidentified inefficiencies can continue to affect overall organizational performance. To enhance company-wide processes, it is essential to examine how manual workflows create friction within daily operations, particularly in three key areas: 

• Recurring manual walkthroughs which slow processes 
• Limited visibility into customer foot traffic 
• Extended, inefficient queue lines 

Manual Site Walkthroughs Creating Inefficiencies 

Manually auditing site conditions, whether that be ensuring marketing promotions are properly placed or compliance policies are followed, can easily take massive amounts of time away from teams. A regional manager might spend days traveling between various locations due to fragmented surveillance systems, or shift supervisors may need to dedicate hours each week walking the floor to ensure operational readiness.

This manual approach limits efficiency. Every minute a team member spends conducting an unnecessary routine audit is a minute diverted away from strategic tasks that drive results. Additionally, walkthroughs only provide a momentary snapshot of site conditions. As conditions change throughout the day, this periodic checking can result in inconsistent standards across different locations.

Lack of Foot Traffic Insights

Optimizing labor and operational resources is a critical part of driving greater revenue; unfortunately, without accurate data on customer volume and peak hours, this task becomes increasingly more difficult. Many businesses rely entirely on historical point-of-sale data to predict future staffing needs. However, this method of analysis can miss out on additional data points, such as the total number of people who entered the building, people who browsed but did not buy, or the exact times when foot traffic spiked before trailing off.

An absence of clear, continuous traffic data can lead to misaligned labor resources, often resulting in overstaffing or understaffing, which creates unnecessary labor expenses or places greater burden on leaner teams.

Long Wait Times in Queues and Drive-Thrus

Long lines and slow drive-thru service can have a negative impact on customer satisfaction, making it crucial for managers to identify bottlenecks before customers complain or leave the store. A lack of visibility into queue lengths and wait times make it difficult for staff to proactively adjust workflows. If managers are unaware of a growing line at a location, they cannot deploy additional resources in time to alleviate the pressure or to prepare for future instances.

The consequences of failing to manage these queues can be detrimental to long-term revenue, as it often leads to customers leaving the queue: one study found that thirty-five percent of consumers would abandon a brand after two bad experiences. This statistic highlights how little margin for error exists in modern retail and service environments.

To meet the challenges posed by manual walkthroughs, inefficient usage of company resources and labor, and long queue lines, organizations need intelligent solutions that can help automate workflows, identify trends, and improve response to operational issues.

How Intelligent AI Analytics Unlocks Operational Efficiency 

Advanced AI video analytics in a cloud video platform can turn security cameras into intelligent operational assistants. An AI cloud solution can automatically monitor specific zones and detect patterns so teams can elevate operations. 

Instead of relying on staff to manually monitor cameras or physically walk the floor, AI analytics do the heavy lifting, with key capabilities including: 

• AI-powered visual alerting 
• Traffic count analytics 
• Additional third-party analytics types 

Visual Check To Reduce Manual Walkthroughs 

With AI-powered visual alerting, businesses can automatically verify site conditions and operational readiness to surface trends, improve consistency, and focus resources where they will have the greatest business impact. These checks analyze camera feeds at scheduled intervals to ensure compliance with company policies.

For example, an automated visual check can confirm whether promotional signage was placed on time at specific locations or help monitor corridors to ensure emergency exits remain unblocked by boxes. By reducing manual walkthroughs, team members free up valuable time while ensuring incidents that require response are addressed quickly and accurately.

Traffic Count for Actionable Business Insights

Organizations can gain clear visibility into location occupancy for more effective resource usage with traffic count analytics. AI-driven traffic counting tracks the number of individuals entering and exiting specific locations, offering valuable data regarding occupancy.

This capability helps managers align labor costs with actual foot traffic and drive more profitable operations. Instead of guessing when peak hours will occur, managers can analyze historical traffic trends to build optimized schedules. Occupancy threshold alerts provide an additional tool for responding quickly during situations when an unexpected rush is occurring. If the number of people in a store exceeds a predetermined limit, the system will notify store managers. This helps businesses ensure service remains swift even during unpredicted spikes in occupancy.

Third-Party Video Analytics To Improve Speed-of-Service

A complete video surveillance solution should also be able to leverage third-party analytics, allowing enterprise businesses to integrate cutting-edge tools and leverage additional analytics types, such as: 

• Vehicle Journey Time Analytics: Tracking vehicle journey time is a highly valuable metric, especially for expansive properties or complex drive-thru layouts. By measuring how long it takes a vehicle to move from the entrance to the service window, operators can identify where delays are occurring and implement targeted workflow adjustments to clear the bottleneck. 
• Queue Length Detection: Queue length detection helps monitor customer lines, with alerts for proactive response to anomalies. If a checkout line exceeds a designated threshold, the system can notify managers. This allows for faster intervention before customer experience degrades. 
• Wait Time Tracking: Additional analytics types can enable viewing of customer wait time to improve speed-of-service. Tracking the exact duration a customer spends waiting provides measurable data to evaluate staff performance and test the effectiveness of new operational processes. 
• Unattended Customer Detection: Analytics-based alerting for unattended customers helps ensure patrons are helped in a timely manner. If a customer stands at a service desk or counter for a set period without an employee present, an alert is generated to send over a team member. 

An open platform architecture enables utilization of analytics-enabled cameras and edge devices to further improve customer experience and enhance operations. An open ecosystem also ensures businesses aren’t locked into a single vendor’s product, allowing deployment of the exact analytic tools required for unique business environments.

Supercharge Your Business Operations With Video Analytics Solutions

An open, AI-powered cloud video platform helps businesses take their operations to the next level. By leveraging an intelligent solution, organizations can automate walkthroughs and respond to key operational inefficiencies faster, whether that’s long queue lines or workflow anomalies, while also gaining insights into company resource usage and trends. 

OpenEye’s AI video analytics provide a powerful solution designed to help enterprise businesses turn video into actionable intelligence, all available in the OpenEye Web Services (OWS) platform. With OWS, businesses can leverage AI Visual Check to automate visual verification of site conditions, Traffic Count to unlock occupancy insights, and Operational Analytics in OWS (powered by Wobot.ai) for additional tracking of key metrics such as wait times or customer journey. The open platform also enables integration of third-party analytics and edge devices for greater access to video analytics. By bringing video data into an AI-driven platform, OpenEye empowers organizations to reduce manual inefficiencies, align labor resources with customer demand, and ensure brand standards are consistently met across every single location. 

Upgrade operations and elevate customer experience today by exploring how OpenEye’s AI-powered video analytics can transform your organization.

FAQs: Video Surveillance Analytics

What are video surveillance analytics?

Video surveillance analytics refer to intelligent software algorithms that automatically process and analyze digital video feeds. Instead of requiring a human to watch hours of footage, AI can detect specific objects, track movement patterns, and identify unique events. 

How does cloud video surveillance improve daily operations?

Cloud video surveillance improves operations by automating manual tasks and providing measurable data. This is accomplished through AI tool sets available in a cloud video platform, such as AI-powered visual alerting, which verifies site conditions and helps reduce manual walkthroughs. 

Can I use my existing cameras with advanced AI analytics?

Yes. Server-side analytics, such as OWS AI Analytics, allow businesses to use their existing cameras and still access video analytics, as the analytics processing is completed on the surveillance recorder. Additionally, an open platform architecture, like OpenEye Web Services, integrates with businesses’ existing analytics-enabled cameras and edge devices. 

How do traffic count analytics help with resource management?

Traffic count analytics provide a record of how many people enter and exit a facility during a determined time. By analyzing this data, management can predict peak operating hours and schedule a more exact number of staff needed to handle the rush. This eliminates the unnecessary costs of overstaffing and the team strain associated with understaffing. 

How do video surveillance analytics improve customer experience?

Video surveillance analytics can help businesses improve customer experience by alerting on unique operational situations, such as long wait times or if a customer is unattended at a service counter. Managers can use alerts to proactively respond to these situations, helping businesses streamline speed-of-service and build a more responsive and helpful atmosphere for customers. 

What industries use AI video analytics?

Many industries use AI video analytics to strengthen security and improve operations. These industries include Retail, Convenience Stores, Restaurants, Financial Institutions, Cannabis, Education, Manufacturing, Logistics, Multi-Family Property Management, and Commercial Real Estate.