When choosing a video surveillance solution, companies should consider what data is available to help make better business decisions. Data like where the bottlenecks are for your customers, how many customers overwhelm a point of sale, what timeframes cause the heaviest traffic in certain areas, or what safety risks increase with certain behaviors. All examples of data taken from video management systems.
Using AI, video management systems can recognize patterns that cause customer dissatisfaction and trigger corrective actions to resolve the issue. For example, if the customers are waiting in line too long to pay for goods, the abandoned cart rate increases significantly. By using AI to identify the conditions that lead to high abandon rates, you could trigger the deployment of additional cashiers during peak demand. Inversely, too many cashiers can lead to employee disengagement and they could be optimized to perform other duties at quiet times.
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The ability of a video management system to generate analytics on staff and customer behaviors will become a more significant differentiator between products in the marketplace as consumers of these products look to squeeze more value from their deployments than just security surveillance.