Everything about Analytics Software
What is Analytics Software?
Data analytics has a long history and in the past it was significantly limited by data storage and processing speed. Nowadays those limitations are no longer applicable, as data analysis can be done with a help of complex machine and deep learning algorithms. These developments in AI are capable of handling large quantities of data in multiple passes. As the artificial intelligence technologies develop, augmenting data processing speed, this results in enhancement of standard descriptive predictive and prescriptive capabilities of data analytics.
Analytics is a process of data investigation that uses data and math in order to answer various mathematical questions, discover relationships, predict different outcomes and automate decision making processes. The whole analytics process can be described as finding meaningful patterns in data discovery as well as new information through the use of mathematics, statistics, machine learning and estimations. It also can be said that recent developments in technology have significantly enhanced the potential of data analytics. There is more data available that can be used to gain a better situational overview, cheaper and better storage facilities, faster and more efficient computation power as well as there are simply more algorithms that can be used to facilitate the application process of analytics within large data sets.
What is Analytics Software?
Analytics software is data processed by a computer program, and this data is used to draw conclusions about the information that has been processed. Analytics software in video, as the name implies, analyzes content from a camera’s video stream and detects, as well as processes, relevant actions. This generates real business value as it can deliver insightful information about customer frequencies, demographics, and behavior.
Why use video analytics software?
Video analytics software can perform several tasks, ranging from real-time analysis of video for immediate detection of events, to the analysis of pre-recorded video footage, for the purpose of extracting data from recorded events.
The demand for data analytics software is driven by the need for effectiveness in video monitoring. This is to say that organizations, in both security and business sectors, have found it more beneficial to rely on video analytics software to monitor camera feeds rather than human labor, as it is cost effective and less prone to errors. An organization can have dedicated and motivated personnel to monitor and process video streams, but studies have shown that humans find it difficult to execute monitoring tasks for more than 20 minutes. Automated video analysis offers an ever-vigilant alternative for these mundane monitoring tasks.
Another reason to use data analytics in video, also driven by demand, is the amount of insightful information organizations can obtain from the footage, whether it’s from a live feed or recorded. In retail for instance, insights gathered from video analytics can help businesses to optimized store performance and deliver an enhanced customer experience. This is because analytics can reveal vital information about a customer’s behavior. Video analytics can answer questions like “How many people visited my store today/this week/this month?” or “How many customers showed interest in the item on sale?”.
What can you do with data analytics software?
By applying data analytics to video feeds, businesses can optimize their operations, which can help increase profitability. Simply put, analytics in video equates to business intelligence, but what exactly is this intelligence? Here are a few things that video analytics software can do:
Popular in retail, analytics software can provide information about the number of visitors to a store at any given time or during a specified period. When combined with sales data, it can be used to calculate the store conversion rate, i.e. the percentage of visitors converted to buyers. The conversion rate is an indicator of high importance to retailers since it tells how well a store is performing. The total population count is usually achieved by installing cameras monitoring the entrance and exit of the store.
Hot zone and dwell time analysis:
Hot zone and dwell time analysis involves tracking where people go and stay within a store or shopping area. Hot zone refers to traffic activity and dwell time reveals where customers spend most of the time. This information enables store managers to optimize store layout for better product placement. In addition, this data can be used to evaluate or enhance the effectiveness of sale or advertising displays.
Customer behavior analysis:
In retail, video analytics can be used to understand how customers interact with products and how they make buying decisions. Businesses using digital signage as a medium for promotion can also analyze behavior and get an understanding of how the target audiences interacts with the content that is being advertised. This can be achieved through face analysis, which can provide insightful information such as age and gender, as well as detecting the emotion of the target audience.
Here are other articles that you might find interesting: