The goal of any entity dealing with technology is to create solutions that will make our lives easier by solving our problems and making things simpler and faster for us. The focus has always been to capture the incidents and draw insights or evidence from it. But if we can avoid these incidents from happening then our city will be a face haven. Predictive analytics implemented through video management systems can help us to foresee an incident before happening and avoid it.
So what is Predictive Analytics?
Predictive analytics is a form of analytics that uses both new and historical data to forecast future incidents, behavior of people, and trends. Predictive analytics is not a new concept but has been used by various organizations around the world. It has also been used by some retail stores to improve the customer experience by understanding their buying behavior. It gives you an advanced forecast into the future, helping you to stay ahead of the curve by identifying the needs of the customers.
How Predictive Analytics can help Retail?
Predictive analytics provides a competitive advantage by proactively informing about the potential events, outcomes and making a timely action plan before its occurrence. Predictive analytics can help retailers increase ROI through targeted marketing campaigns, personalized shopping experiences, smart inventory management, setting competitive pricing, and more. Without using predictive analytics and harnessing the sheer amount of data on offer, many companies would quickly become lost in the constant fluctuations within the market. Grow with your market and implement predictive analytics techniques today.
How to use predictive analytics in retail
Improving Security and Surveillance: Many stores have embraced video analytics to address their worrying problems of theft and fraud. Theft and fraud can be curbed with face recognition, where the VMS will pick up on people who have a past record of suspicious activities. So the store security is alerted and they can keep an eye on them or else escort them out of the store. Another way of countering theft is based on the study of patterns of suspicious activities through machine learning that have been recorded in the past. So any store using predictive analytics can get a forecast of such activities, helping them to avoid it.
Understanding Buying Behavior: Besides security and surveillance, predictive analytics can also help in terms of understanding buying behavior of customers. This can be done by taking advantage of metrics- the demography, age group of the customers visiting your store, average basket size, gender, time etc. Apart from that, the data generated by handheld barcode scanners or mobile applications that are used for smart check-out registers the buying patterns of the customers. You will be able to derive insights into what items are more likely to be bought at your store.
Through predictive analytics the store can push promotions of related products or other products that might be of interest to the customers. Using predictive analytics can also help you understand at what time slots your store is most likely to be busier, helping you to position your promotions accordingly and derive optimum utility out of it.
Optimizing promotion in real-time: Businesses can take advantage of predictive models that work to enable sellers to make better decisions in real time. This model is fed with a continuous stream of historical as well as real-time data. Insights based on information such as customer profile, visited channel, time of web session, cart abandonment, and price sensitivity can help retailers adjust promotions dynamically.
Personalization for customers: In the past, before data analytics became mainstream, the option of targeted offers was non-existent or was only for large swathes of customers having one or two common characteristics. But with the emergence of online shopping, and then data analytics, it is now possible to track behavior across channels, i.e., monitor a shopper who researches in the digital store and then goes ahead and purchases the item in the physical store.
Inventory and supply chain management: Predictive analytics helps answer questions such as what to store and when to discard. Stocking up slow-moving products and running out of popular ones are both major problems in the retail industry. Such insight provided by predictive analytics in the retail industry can optimize performance and reduce costs. Thus, predictive retail analytics removes this uncertainty, or any purchase simply based on a hunch.
Customer segmentation & customer journey: A customer’s journey is a map that tracks the buyer’s experience. It starts when the customer first contacts a brand and ends with a purchase order. The journey traces the process of engagement. In retail, predictive analytics does wonders in providing such useful insights.
Improving Customer’s Shopping Experience: Even when these two angles are being addressed, there is also a need to build a loyal customer base and provide a unique shopping experience so that the customer returns to the store. Many a times the wait-time while standing at a check-out counters can be frustrating. Queue management analytics can reduce wait-times by automatically opening other check-out stations by counting the people the number of people in the queue, thus saving the customer’s time. With people counting and also hot spot analysis, the store can optimize their workforce to cater to the aisles with high traffic.
Devices or applications for self-checkout can also improve customer experience. Through these devices you can also push promotions of the items they are more likely to buy based on the products they have bought in the past. Pop-ups for missed items can also assist the customer with his shopping. Through heat-mapping, the store authorities can find out how much time a customer has spent reading or watching the promotion and in that case send an attendee to assist them. This will also help the store to measure the performance of their promotional activities. This can also help in the launch of new products.
Predictive analytics can help businesses make progress incessantly towards the future and will help the retail stores stay ahead of the curve. If you are interested in exploring Video Analytics, know more about how Video Analytics can help in City Surveillance.