Watching customers closely to influence buying behaviour

February 13, 2014 | By RetailME Bureau

A customer drives into the parking lot of a hotel. The hotel staff is immediately notified of the arrival of this very important client. The hotel manager allocates staff to receive the guest and cater to his/her special requirements. The manager is fully aware of the customer’s name, contact details and dining and travel preferences, even before (s)he enters the hotel.

This scenario is the reality in the hospitality industry today, tested and perfected to improve customer service. Its technological base is the video camera system that permits high-speed gathering and processing of visual data – the very same cameranetwork installed for surveillance of the property.

From loss prevention to analysing store traffic patterns

Closed-circuit television (CCTV) camera systems have evolved into sophisticated and intelligent video management systems that do much more than just monitoring an area for loss prevention. A common, networked camera system can be used to detect theft, identify an important customer at different points of contact in and around a store, and perform several additional tasks such as people counting, queue management, heat mapping, facial and gender recognition.

That’s why the retail industry in the UAE is increasingly adopting these intelligent systems for surveillance, loss prevention, studying shopper behaviour, identifying important customers, and enhancing customer experience through real-time decision-making.

“Apart from surveillance of their stores, retailers can use this advanced technology to measure and study footfall, dwell time, customer traffic patterns and other parameters that can then form the basis of zoning, merchandising and optimization of their retail spaces,” observes Mahesh Asarpota, managing director of Magnus Technologies, a UAE-based system integrator offering intelligent video management systems in the UAE.



According to Asarpota, the numerous applications of video management systems hold many benefits for retailers, allowing them to collect, analyse and interpret in-store data to visualise and predict crucial shopping patterns, which in turn leads to improved sales. Brick-and-mortar stores can thus track and monitor customers in the manner online stores do, from the time they enter the store till the time they leave.

“Store owners or managers can analyse in-store shopping behaviour and customer browsing patterns in real time, allowing them to make prompt decisions to provide better sales assistance, improve merchandising and personalise advertising. For instance, during peak hours in hypermarkets, when queues build up at cash counters, CCTV cameras with video analytics software can alert store staff to open additional counters,” Asarpota points out.

“Retailers can also take advantage of the integrated people counting and heat mapping features of CCTV cameras to obtain useful visual tools for measuring customer traffic patterns inside their stores. Such heat maps can be generated for each aisle in the store to determine dwell time within a particular zone and the duration of time a customer engages with a product before deciding to buy it or not,” adds Asarpota.

Facial recognition – the beginning of things to come

Highly reliable, accurate and intelligent video technologies are being expanded to track the demographics of people entering a store through facial recognition. The most advanced facial recognition software available today can identify the age, gender, race and even mood of a shopper. Given below are examples of some of the innovative video analytics tools offered by manufacturers and software developers worldwide.
Japanese IT and network solutions provider NEC’s NeoFace facial recognition software solution, which helped Michigan State University researchers identify a suspect from footage of the Boston Marathon Bombing, is being offered to retailers to analyse customer faces to determine age, gender and shopping patterns. It has also been deployed at Universal Studios Japan to identify holders of annual passes to the theme park. The software uses a technology called ‘adaptive region mixed matching’, which divides the input image and the registered image into small segments and focuses on highly-similar segments of the face to provide a highly precise match. NEC is currentlytesting its products in high-end retail stores and hotels in the US and Europe to identify celebrities.

3VR, a US-based video intelligence solutions provider, is offering retailers the technology to obtain and analyse patterns of individual browsing and purchasing behaviour, including who is walking into the store, who is buying what in the store, how long the customer stays in the store, how long the customer waits in line before being helped, and how long the customer watches an item before making a move.

Italian mannequin manufacturer Almax has created the EyeSee Mannequin, which gathers details such as age, gender, race, number of people entering a store and time spent at a window display. A special camera installed inside the mannequin’s head analyses the facial features of people passing through the store front and provides statistical and contextual information useful for developing targeted marketing strategies. The embedded software can also provide other data such as the number of people passing in front of a window at specific times of the day.

Zoomkube, a US-based provider of interactive marketing display solutions, has introduced a facial recognition software with social media monitoring capabilities. Based on a consumer’s appearance and behaviour, this technology allows brands to serve realtime offers and content on a monitor in retail stores. Cameras capture an image of a consumer standing in front of a monitor and compares it with thousands of others in a database with the help of a third party facial recognition software, allowing the brand to determine gender, age and appearance and offer personalised offers and content based on the individual’s appearance and behaviour. For example, a person with curly hair standing in front of a digital kiosk would generate an advertisement of shampoo specific for curly hair.

Finnish company Uniqul has taken facial recognition applications to a new level by developing a face recognition payment system that enables customers to pay without having a wallet, card or mobile phone. According to the developers, the payment system reduces the transaction time from an average 30 seconds to less than 5 seconds. Uniqul works with existing payment solutions providers such as Visa, MasterCard, American Express, Diners club, PayPal and Square.

Last year, Russian retail technology company Synqera announced a joint pilot programme with retailer Ulybka Radugi, which owns and operates more than 280 retail cosmetics and household chemicals stores in Russia, to use facial recognition at the POS terminals in Ulybka stores. Synqera’s check-out technology captures ambient customer data including emotions, sex and age, and uses the data to personalise individual offers for customers. Synqera’s software syncs the physical profile of each customer facing the sensor-enabled checkout device, data from the loyalty card, and actual shopping basket data with the parameters of preliminary uploaded content. The software then creates rich visual images on the interactive customer display for each customer’s unique order, shopping tendencies and response rate in real time.

“Video management systems that provide demographic information can help retailers develop and modify their marketing strategies. For instance, a retailer targeting a certain age group to sell a particular brand may find its sales are coming from a different age group. Accordingly, that retailer can change its brand strategy to accommodate new customers,” concludes Asarpota.



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