In today’s climate, surveillance systems are a commonly used tool in retail facilities worldwide to support and aid security and safety measures. However, despite the pragmatic purpose they provide, there lies a large amount of under utilized data that can help retailers better understand consumer behavior and retail vendor performance. Without this data, retailers cannot improve business growth and make accurate decision making through informative measures.
Although there are a number of other technologies used to measure consumer activity, these methods rely solely on either specific data points, non-dynamic information, or manual processes that are time and resource consuming. As a consequence, these results do not showcase the “why” to a consumer’s behavior, nor do they provide a consolidated outlet for a seamless management experience.
Traditional, surveillance systems capture fairly useful information that is rarely filtered, processed and utilized. Although these systems are extremely useful, most facility owners do not realize that there is an extended capability they can provide. From improving customer experience, to measuring vendor performances, specific activity can be captured and analyze to help retailers increase revenue growth.
So, how can retail facilities capitalize on their previously existing surveillance system to achieve optimal growth? By integrating a state of the art AI Engine that uses trained algorithmic models to detect, identify and track a number of behavioral and performance-based metrics. With AI-based generated data, retailers will better understand the nature of retail environments in an automated and autonomous fashion. This allows facility owners to dive deeper into data related information, reveal what drives or depletes business growth, obtain direct feedback of sales or marketing strategy experiments, and identify market demands.
Furthermore, by integrating into other or existing technologies such as motion sensors, IoT devices and more, different sources of data can be extracted and consolidated into a central dashboard. This allows retailers to gain a richer insight into consumer and vendor related insights data.
Through a number of technology points integrated into an Artificial Intelligence engine, retailers can gather, filter, and process data to an analytics dashboard that simplifies information in a concise manner for informed decision making.
below we cover 4 data sets that can be reported in an automation fashion to provide efficient business outcomes:
Through AI recognition, you can track, analyze and better understand the correlation between demography and the specific behaviors that pertain to particular consumers. Whether you’re looking to single out a specific demography, or seek to understand the general overview of your consumers, confidently build and test new or existing strategies that apply to your consumer base accordingly.
An AI engine can identify and track:
Discover and pinpoint the density of where consumers frequent the most (or the least) through auto generated heat maps. Furthermore, through visual indicators of shopping flows and shopper counts, heat maps can be used to test the effectiveness of new layouts or the popularity of store locations to gauge retail space evaluations. Furthermore, through different data points such as time, year, demography and more, AI can also help assist in making future predictions in engagement, revenue and location of new or existing vendors.
Although entry points are typically facilitated by sensors, by also leveraging surveillance systems integrated with AI, we can timestamp and monitor consumers to not only track the amount of time spent within facilities or stores, but we can also discover what factors play into higher retention rates. Whether it’s a particular product or layout that captivates consumers to purchase or stay longer, indicators can be identified by AI to bring attention to probable correlations.
Better understand the effectiveness of advertising campaigns by monitoring how consumers interact with them. By leveraging AI and surveillance cameras, retail facilities can analyze advertisement interactions such as engagement rate, conversions, facial expressions and much more.
Although these are only just a few ways that data can be extracted and processed, there is much more information that an AI-based surveillance system can detect. Overall, it is important to note that AI should be leveraged as a powerful tool to automate data processing and quickly improve decision making.
If you would like to learn how our AI surveillance system can similarly benefit your retail business, or would simply like to understand how this solution can be leveraged in different industries, feel free to visit our AI Surveillance System or contact us to start a dialogue!
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