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Retail Business Review | Friday, June 03, 2022
Retailers are boosting their demand planning capabilities to process more data or variables in the planning process at scale while based on human planners for qualitative input and exception management.
The retail industry has undergone significant transformation in the last decade as principal retail brands invested greatly in digital transformation underpinned by cloud computing advances and the widespread acceptance of e-commerce.
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We look at five rising yet important retail technology trends that retailers should assess in 2022.
1. Contactless Stores
Contactless stores indicate a suite of technologies and customer experiences that retail chains have implemented to reduce friction or delays experienced by customers at different touchpoints and minimize human contact in the buying experience.
2. Artificial Intelligence (AI) Enabled Security Cameras
AI cameras employ artificial intelligence to make sense of the videos being recorded. For example, they can be programmed to identify certain types of objects or human activity, movement, the expulsion of objects, read license plates or even identify faces.
AI-enabled security cameras can promote the effectiveness of remote video monitoring or surveillance.
Security operators monitoring the feeds can obtain real-time notifications when the camera detects any anomalies the AI program is trained for, enabling security teams to act before a crime is performed.
AI-enabled security camera systems provide a searchable footage library making it easy to swiftly find footage of bearing and doing away with the need to sift through hours of recorded footage during investigations.
Innovative AI-enabled security cameras have deep learning capability and can turn progressively better at recognizing patterns and detecting anomalies in recorded video.
3. Retail Video Analytics
Retail video analytics is a new category of retail applications that leverages computer vision and AI technologies to capture real-time information from security camera footage.
Most retail chains have established security cameras at all their stores. These security cameras record essential information that can be utilized to gain valuable operational insights regarding retail operations and customer action inside the store.
Data that can be grabbed with video analytics incorporate – customer movement or flow, customer engagement with products and shelves, the efficacy of the store layout, the influence of online promotions on foot traffic, customer service endure at the checkout, and compliance problems related to product display, spills, and cleanliness.
Technology implications of retail video analytics
Adopting a retail video analytics solution is not a complex initiative. Still, the real challenge is identifying the right metrics to track and being able to draw meaningful inferences. Here are the top considerations when adopting retail video analytics from a retail IT organization perspective.
•The primary sensor for collecting data from a video is the security camera. Security cameras are established with loss prevention as the main use case, and the installed cameras may not necessarily meet the data collecting requirements for a video analytics project. Camera enhancement and new installations may turn into a requirement.
• The ROI of a retail video analytics execution relies on the ability to fuse data from multiple data sources to recognize correlations and frame hypotheses regarding customer behavior. Solutions with documented API and integration capabilities should be favored.
• Video analytics solutions can trail customer movement, product interactions, and behavior inside the store. When utilized in conjunction with AI-enabled cameras with facial recognition capabilities, retailers can run the risk of violating customer privacy.
• Retail video analytics can be utilized by diverse departments or teams in a retail organization. Loss prevention, marketing, operations, compliance, legal, human resources, and merchandising teams have compelling use cases for reviewing customer and employee activities within the store. A powerful system to regulate access to video analytics data is an important requirement for IT teams.
4. Metaverse
Metaverse normally refers to the idea of a highly immersive virtual world where people get together to socialize, play, and work.
Metaverse is still an upcoming concept, with bits and pieces of the building blocks being gathered and considered work-in-progress.
5. Retail Demand Planning
Retail demand planning is the procedure of forecasting demand for products across all channels (in-store, e-commerce, BOPIS, ship from store), considering historical demand patterns, business decisions, and external factors such as competitor offer.
Demand planning aids retailers navigate complicated challenges across all aspects of retail operations.
• Streamlined store and distribution center replenishment
• Best workforce planning and optimization
• Optimized product advancement and discounts
• Optimized assortment planning
• Better space planning and enhancement
• Bettered budgeting and cash flow management
What are the key drivers for innovation in retail demand planning?
E-Commerce and new fulfillment channels are no longer observed as a differentiator as customers expect to find the products they wish no matter where and how they shop.
Retailers can only fulfill these expectations by upgrading to a data-driven, real-time demand planning approach. As a result, retailers are already boosting their demand planning capabilities to process more data or erratics in the planning process at scale while depending on human planners for qualitative input and exception management.
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