Retails
AI Transformation in Retail
The retail industry is highly competitive with increasing pressure form online competitors. Leading retailers know that customer experience and streamlined operations are key to their success. Companies that are making extensive use of AI are reaping the benefits of increased customer satisfaction and loyalty while decreasing fraud and improving operations which adds to their bottom line. These companies are using AI for a number of scenarios including assortment optimization, product recommendations, fraud detection, customer retention, and optimized marketing. We are empowering leading retail companies to deliver AI solutions that are changing the industry.
The digital transformation of the retail industry has been going on for years. It has increased speed, efficiency, and accuracy across every branch of retail business, thanks in large part to advanced data and predictive analytics systems that are helping companies make data-driven business decisions.
None of those insights would be possible without the internet of things (IoT), and most importantly, artificial intelligence. AI in retail has empowered businesses with high-level data and information that is leveraged into improved retail operations and new business opportunities.
With AI- Retailers are getting smarter
Inventory Management
AI in retail is creating better demand forecasting. By mining insights from marketplace, consumer, and competitor data, AI business intelligence tools forecast industry shifts and make proactive changes to a company’s marketing, merchandising, and business strategies. This also impacts supply chain planning, as well as pricing and promotional planning.
Dynamic Outreach
Advanced CRM and marketing systems learn a consumer’s behaviors and preferences through repeated interactions to develop a detailed shopper profile and utilize this information to deliver proactive and personalized outbound marketing — tailored recommendations, rewards, or content.
Interactive Chat – Voicebots & Chatbots
Building interactive chat programs is a great way to utilize AI technologies while improving customer service and engagement in the retail industry. These bots use AI and machine learning to converse with customers, answer common questions, and direct them to helpful answers and outcomes. In turn, these bots collect valuable customer data that can be used to inform future business decisions.
Visual Curation
Algorithmic engines translate real-world browsing behaviors into digital retail opportunities by allowing customers to discover new or related products using image-based search and analysis — curating recommendations based on aesthetic and similarity.
Guided Discovery
As customers look to build confidence in a purchase decision, automated assistants can help narrow down the selection by recommending products based on shoppers’ needs, preferences, and fit.
Conversational Support
AI-supported conversational assistants use natural language processing to help shoppers effortlessly navigate questions, FAQs or troubleshooting and redirect to a human expert when necessary — improving the customer experience by offering on-demand, always-available support while streamlining staffing.
Personalization & Customer Insights
Intelligent retail spaces recognize shoppers and adapt in-store product displays, pricing, and service through biometric recognition to reflect customer profiles, loyalty accounts or unlocked rewards and promotions — creating a custom shopping experience for each visitor, at scale. Stores are also using AI and advanced algorithms to understand what a customer might be interested in based on things like demographic data, social media behavior, and purchase patterns. Using this data, they can further improve the shopping experience and personalized service, both online and in stores.
Emotional Response
By recognizing and interpreting facial, biometric, and audio cues, AI interfaces can identity shoppers’ in-the-moment emotions, reactions or mindset and deliver appropriate products, recommendations or support — ensuring that a retail engagement doesn’t miss its mark.
Customer Engagement
Using IoT-enabled technologies to interact with customers, retailers can gain valuable insights on consumer behavior preferences without ever directly interacting with them. Supported by the IoT Hub and machine learning, this tablet has leveraged consumer data and behavior trends, allowing companies to increase engagement and success with customers.
Operational Optimization
AI-supported logistics management systems adjust a retailer’s inventory, staffing, distribution, and delivery schemes in real-time to create the most efficient supply and fulfillment chains, while meeting customers’ expectations for high-quality, immediate access and support.
Responsive R&D
Deep learning algorithms collect and interpret customer feedback and sentiment, as well as purchasing data, to support next-generation product and service designs that better satisfy customer preferences or fulfill unmet needs in the marketplace.
How AI is transforming Retails
Demand Forecasting
Mining insights from marketplace, consumer, and competitor data, AI business intelligence tools forecast industry shifts and make proactive changes to a company’s marketing, merchandising, and business strategies.
Customized Selections
Taking customer service to the next level, many retailers are using AI to help them provide unique, personalized experiences for customers. Brands that create personalized experiences by integrating advanced digital technologies and proprietary data for customers are seeing revenue increase.
Create Exciting Experience
To drive continued interest, retailers need to differentiate their products and offer consumers compelling service and experiences. By integrating predictive analytics to gather more market insight, retailers can lead with innovation rather than react to change.
Create Insights from Disparate Data
Faced with an onslaught of information from all aspects of business from supply chain to stores to consumers, retailers need to filter through the noise to transform these disparate data sources into consumer-first strategies.
Synchronize Offline & Online Retail
Digital and physical shopping channels typically operate under a different set of initiatives and approaches but treating these channels as distinct business units adds friction for customers seeking a seamless shopping experience and leads to operational inefficiencies.
Empower Flexible Logistics Networks
In order to service a wider range of customer demands that are moving from mainstream to niche, retailers need to rethink their traditional supply chain in favor of adaptive and flexible ecosystems that can quickly respond to consumers’ shifting behaviors.
Artificial Intelligence Advanced Features
Cashier Free Stores
With automation system of stores which will result in reducing lines, lowering the number of human employees, and significant savings on operational expenses. AI has already introduced checkout-free stores. When you walk out of the shop with products, the retail store account will take money for your purchase. Store wants to make more shops driven by Artificial Intelligence where only limited human staff members are needed.
Price adjustments
Applications of AI for retail stores could help businesses set prices for their products, visualizing the likely outcomes of multiple pricing strategies. To be able to execute this, systems collect information about other products, promotional activities, sales figures, and additional data. Business leaders can present the best offers and get new customers and boost sales as a result. Artificial Intelligence for price optimization and stay flexible with the ability to adjust prices and promotions according to the information obtained.
Price predictions
Price forecasting is a prediction of the price of a product based on demand, seasonal trends, characteristics, the release date of new models of the same item, etc.. Just imagine an app or service that helps your customers know beforehand how the price for a certain product will change. With Artificial Intelligence, this is possible and it is very easy to implement. A Price prediction feature could help you build customer loyalty.
Supply chain management and logistics
AI in the retail supply chain can be used for restocking — calculating the demand for a particular product by taking into account a history of sales, location, weather, trends, promotions, and other parameters.
Machine Learning in retail: product categorization
Systems based on Machine Learning tag goods and sort them in different categories for customers who are seeking a particular type of product. Sellers can just upload the image of the products they want to sell and Machine Learning retail software with computer vision would recognize it, classify it, and even suggest a price.
Visual search
Visual Search systems powered by Artificial Intelligence allow customers to upload images and find similar products based on colors, shapes, and patterns.
Voice search
AI technology to provide customers with simple and quick voice search. Now customers can just ask AI for the desired item and its delivery status without typing anything. In fact, 27% of people worldwide use voice search on mobile, and 52% of them prefer it to mobile apps and websites for their convenience.
Virtual fitting rooms
Virtual fitting rooms are a great way for customers to save time and find the perfect outfit with all the elements perfectly matched — in a span of minutes! A virtual fitting kiosk can scan you in 20 seconds and measure 200,000 points of your body in this period. Companies and others can install these scanners in their stores and receive massive sales increases.
Customer satisfaction tracking
Artificial Intelligence is capable of detecting the mood of your customers during the shopping process. Mood tracking will definitely help build stronger relationships with customers.
Customer behavior prediction
Artificial Intelligence platforms enable business owners to make use of behavioral economics and build an individual approach to each customer. This Intelligent Incentive platform that analyzes each customer’s psychology and emotions to increase purchases. The algorithm processes the customer’s emotional responses and behavior during previous shopping experiences and tries to come up with optimal pricing offers for a particular visitor.
Artificial Intelligence is the future of Retail
Tailor retail efforts to specific customers
Optimize inventory and fulfillment for online or in-store shoppers
Tailor retail efforts to specific customers
Uncover precise consumer needs by tapping into where and at what price customers shop across all channels and devices. Rule-based systems can't handle the sheer number of products, customers and touch points in real time. But when driven by machine learning, your pricing, assortment and marketing are always on target down to the micromarket level.
Anticipate your customer’s next move
Optimize inventory and fulfillment for online or in-store shoppers
Tailor retail efforts to specific customers
For every customer, AI uses thousands of pieces of text and digital data to develop a next-best action and drive recommendation engines. And you can use this insight to predict future buying behaviors, shape demand and seize opportunities to maximize margins.
Optimize inventory and fulfillment for online or in-store shoppers
Optimize inventory and fulfillment for online or in-store shoppers
Optimize inventory and fulfillment for online or in-store shoppers
Planning and adjusting the movement of merchandise can be overwhelming. AI techniques can learn and correct supply chain issues while reducing the need for human intervention. And by adding in machine-to-machine IoT analytics and RFID data streams, you can achieve real-time inventory transparency.
Control fraud and shrinkage
Power the store of the future today with analytics at the edge
Optimize inventory and fulfillment for online or in-store shoppers
As the volume of digital transactions with customers and vendors continues to rise, analytic anomaly detection is the only way to keep an eye on what's happening. Deep learning algorithms can uncover and adapt to new fraud vectors, enabling you to address money laundering, vendor procurement fraud, cashier fraud and returns abuse.
Power the store of the future today with analytics at the edge
Power the store of the future today with analytics at the edge
Power the store of the future today with analytics at the edge
Your physical stores have untapped potential to connect with customers. Wi-Fi foot-traffic sensors, video cameras, electronic shelf labels, and warehouse and in-aisle robotics can transform how you use every square foot. Deep learning algorithms, computer vision technology and real-time decisioning enable you to bake the art and science of retail into the customer experience.
Reward Points
Power the store of the future today with analytics at the edge
Power the store of the future today with analytics at the edge
With AI, in the retailer's marketing toolkit, loyalty programs have proven themselves as one of the most effective tactics for increasing revenue and inspiring customer loyalty. As many as 84% of consumers say they’re more apt to stick with a brand that offers a loyalty program. And 66% of customers say the ability to earn rewards actually changes their spending behavior.
We know that it costs a lot less to sell to existing customers than acquire new ones—that’s why brands invest in loyalty and rewards programs.
While they can be so effective, customer loyalty programs are nothing new. Most fall into one of four categories: points, tiers, social media, and paid programs. That’s why some retailers are looking to shake things up and find innovative new ways to build rewards programs and inspire customer loyalty.
Cybersecurity, AI & Retail
Cybersecurity is a major concern for all companies and industries today, particularly those who manage sensitive customer information. Hardly a week goes by without a major breach making the news, and consumers are increasingly concerned about how their brands prepare for and manage these threats. Retailers can help protect their assets by understanding the threat landscape in their industry. Knowing what attackers are looking for and how or where they typically find vulnerabilities to exploit, can help companies stop attacks before they occur.
Digital transformation is dominating retailers’ attention — and their IT budgets. As a result, significant gaps in retail cybersecurity are left unfilled just as retail IT faces new challenges, from infrastructure moving to the cloud without clear security policies to an array of new threat vectors focused on personal customer information, ransomware and under-protected business-to-business connections.
Just as with line-of-business functions like merchandising and operations, retailers’ cybersecurity functions must undergo a digital transformation to become more holistic, proactive and nimble when protecting their businesses, partners and customers.
Retailers to focus on six control objectives:
- Build and maintain a secure network and systems
- Protect cardholder data
- Maintain a vulnerability management program
- Implement strong access control measures
- Regularly monitor and test networks
- Maintain an information security policy
Additionally, retailers are advised to migrate data to secure infrastructure and make sure POS systems are encrypted, train loss prevention specialists on how to identify cybersecurity attacks, make sure they are meeting all compliance mandates and monitor threats where the cybercriminals gather.
AI based Network Systems for Retails
In a retail store or a shopping mall, WiFi system transforms into an intelligent marketing system which enables a display of video advertisements on mobile phones, tablets or laptops of customers.
Having seen the video advertisement, the customers are delivered targeted video advertisements and special offers to maximize the effectiveness.
A customer can give consent to receive intermittently emails containing discounts, coupons and the offers of your partners for advertising purposes.
The system gathers data and surveys with feedback on customer satisfaction, complaints and comments that may be answered personally.
AI based Network Security
Personalized & Customized Development
Personalized & Customized Development
Personalized & Customized Development
Access Management
Personalized & Customized Development
Personalized & Customized Development
Content Filtering
Personalized & Customized Development
Vulnerabilty Assessment
Vulnerabilty Assessment
Virtual Private Network (VPN)
Vulnerabilty Assessment
Virtual Private Network (VPN)
Virtual Private Network (VPN)
Virtual Private Network (VPN)
User Management
Virtual Private Network (VPN)
Virtual Private Network (VPN)
Bandwidth Management
Bandwidth Management
Bandwidth Management
Load Balancing
Bandwidth Management
Bandwidth Management
Anti-Virus
Bandwidth Management
Intrusion Detection and Prevention System
Intrusion Detection and Prevention System
Intrusion Detection and Prevention System
Intrusion Detection and Prevention System
Anti-Spam
Intrusion Detection and Prevention System
Interface Management
Interface Management
Intrusion Detection and Prevention System
Interface Management
Managed AI Networks for Retails
