The lack of real time data analytics and forecasts in venues creates disadvantages for both customers and businesses. Visitor experience and security needs remain unobserved and unaddressed, defying customer satisfaction and consequently reducing business profits.
To reverse this process and optimize both consumer and firm benefits, an AI density analysis solution incorporated with a visitor management system should be implemented. These capture critical information such as current and predicted venue footfall, duration of customer stays, busy and non-busy venue hours, and venue floor plans. The user interface is conveniently accessible on computers, tablets as well as smartphones.
The key purposes of this initiative are to help businesses predict space demand, analyze customer behavior to prioritize certain goods and services and optimize usage of space, resources and expenditure. The result is that on one hand customers enjoy a better experience through availability of products suited to their needs and the ability to choose appropriate times to visit depending on traffic, and on the other hand businesses improve and expand ROI.
We acknowledge from past observed data that this system plays different efficiency-driving roles in a variety of sectors such as commercial and residential buildings, security, shopping destinations, gym and leisure centers, retail and supermarkets, and entertainment. These statistics also tell us that a fit-to-purpose crowd management system such as ours increases business turnover by at least 20% over a period of about 4-6 months post implementation.
We see at least a 20% rise in the total revenue generation in typical ways explained earlier. This gives higher returns over an estimated period of 4-6 months of implementation.
An instance of where crowd managements system play a very crucial role is at fairs and exhibitions. Often, the lack of space at entrances disincentivizes visitations from customers. Problems with organization of seating space at showcasing areas, lack of crowd forecast availability for customers, security risks that come with large crowds and deficiencies in information on product preferences of consumers mean that both businesses and visitors endure losses.
By providing live and forecast trends at venues, density analyzers and visitor management systems resolve these issues, majorly cutting down costs to business and scaling-up customer satisfaction.
Our recognition of the importance that this edge system has for improving business hospitality and revenue yield through big data-based operations encourages us to facilitate its implementation.
