Effectively managing the order-to-cash (O2C) cycle while improving the maturity of your loss prevention strategy.

Using predictive techniques to proactively detect instances of fraud.

Controlling inventory shrink while providing customers a safe and satisfying shopping experience.

Managing innovation and continuing to explore opportunities to apply technological advancements to prevent inventory loss and theft.

Implementing AI solutions raises privacy concerns and ethical questions about surveillance and consumer rights, leading to issues with legal compliance.

AI can generate false positives, which can lead to customer inconvenience and mistrust.

Significant investment required for advanced AI systems can be a major barrier, particularly for medium and small enterprises.

Absence of specialized skills to implement and manage AI systems.

Resistance to change, lack of buy-in from stakeholders, and cultural barriers.

AI can not only help get a handle on losses by enabling immediate response to incidents as they happen, but also take a more proactive, preventive approach.

Info-Tech will provide:

• A comprehensive understanding of the benefits of applying AI-enabled technologies for loss prevention.
• A tool to help you assess the maturity of your current loss prevention strategy and identify focus areas for improvement.

The Kroger Company operates supermarkets and department stores throughout the US. Kroger is headquartered in Cincinnati, Ohio with a revenue of $100+ billion from over 2,500 stores.

In their quest to provide their customers with a quick, easy, and convenient experience in-store, Kroger has been expanding its use of self-service checkouts (SCOs) throughout the US.

With the increase of self-service checkouts, Kroger noticed an increase in losses due to missed scans and product switching. To address losses from these actions, Kroger decided to turn to AI.

Kroger chose Everseen's Visual AI platform that uses high resolution cameras, computer vision, and AI developed on Nvidia's Accelerated Computing Platform. The Everseen solution can intelligently intervene when problems occur at the SCOs.

Everseen's AI runs on Lenovo's Edge AI servers. Video footage from SCOs is analyzed in real time to identify when a customer has not scanned a product or moved the barcode from a cheaper to a more expensive product.

The system will flag these problems and prompt the customer while simultaneously informing a store associate on their mobile device so they can intervene and rescan the item.

With Everseen's AI solution, Kroger was able to flag and correct over 75% of checkout errors without involving a store associate. This resulted in a direct reduction in retail shrink.

Since this solution works with legacy equipment, Kroger was able to rapidly scale its initial deployment to over 1,700 stores.

Given the success of this platform, Kroger has decided to employ other AI-enabled technology such as front-door face watching technology, camera monitored back-door delivery areas, and license plate recognition in their parking lots.

Wayfair Inc. is an e-commerce company that sells home goods online in many major international markets. Wayfair is headquartered in Boston, Massachusetts and operates a complex international logistics and infrastructure network to fulfill orders from over 20,000 global suppliers.

The vast selection that Wayfair offers has resulted in many years of hypergrowth for the company. They have a large internal fraud team that manually reviews up to 10% of all orders placed on the site.

Wayfair soon found it inefficient to keep expanding this team to keep pace with the growth of order volumes.

Wayfair chose to partner with Riskified to start by reviewing their declined orders. Wayfair was impressed with Riskified and soon expanded their partnership to use AI and manage fraud for all their US orders.

Riskified's solution uses AI for analysis of comprehensive data including device data, behavioral insights, past chargebacks, e-commerce activity, and known fraud patterns.

AI then draws insights from historical transactions and takes decisions in near real time. Data is used to continuously train Riskified's decision models to improve their chances of identifying false declines.

With Riskified's solution, Wayfair was able to reduce their cost of fraud by over 50%.

When Wayfair saw an unprecedented increase in order volume during the pandemic, Riskified was able to help them reduce their chargeback rate by 50% to 60%.

Riskified's solution was also able to reduce false-positive callbacks by over four times, thus continuing to maintain Wayfair's objective of 0% friction due to fraud reviews.

Neiman Marcus is a privately owned luxury goods retailer headquartered in the US. Neiman Marcus has 36 location across the US and brings in revenue exceeding $5 billion annually.

Neiman Marcus had a team managing pricing functions that had to manually manage markdowns across tens of thousands of SKUs. The team had to manually scrape competitor websites for pricing intelligence on each individual item. This process was too slow, costly, and inefficient.

Neiman Marcus started looking for an effective competitive pricing tool to replace their outdated pricing practices.

Neiman Marcus chose to partner with Centric Market Intelligence for their user-friendly and capable pricing system.

Neiman Marcus first tested the system with a few categories and a couple of competitors. They leveraged Centric's Product Matching module which helps compare the SKUs that Neiman Marcus carries with products from their competitors and execute like-for-like price matching and discounting. The tool was able to analyze trends to ensure that Neiman Marcus was doing assortment the right way, resulting in more buying conversion.

Given the Centric platform's user-friendliness, its use was expanded by Neiman Marcus to cover all of their categories and competitors.

Neiman Marcus experienced several benefits by using Centric Market Intelligence:

• They achieved a more efficient and streamlined process for competitive pricing analysis.
• Centric allowed for more accurate and timely decision making regarding pricing strategies.
• It facilitated a deeper understanding of the competitive landscape, aiding in smarter pricing decisions.
• Neiman Marcus was able to respond more dynamically to market changes and competitor pricing strategies.

The Colruyt Group is a privately owned chain of stores that includes supermarkets, organic groceries, online shops, bakeries, toy stores, gas stations, and apparel stores. The brand is headquartered in Belgium and brings in over EUR$10 billion in revenue annually.

Colruyt faced challenges in speeding up checkout times, especially for products like fruits and vegetables that do not have barcodes.

The manual process of typing codes for these products at the checkout was time-consuming and could lead to confusion, queues, and delays.

Colruyt collaborated with Robovision to develop an AI-based system involving a "deep learning" smart camera installed above the checkout scales.

This camera automatically recognizes different kinds of fruits and vegetables when customers place them on the scale. The system proposes the right label to the customer, who then confirms the selection on a tablet.

Robovision's technology was a significant step in digital advancement for Colruyt, making the checkout process more efficient and reducing the workload for sales employees.

The AI technology provided by Robovision proved to be highly effective.

Robovision's solution could successfully identify over 97% of the products correctly. This not only sped up the checkout process, but also enhanced customer experience at the checkout counter.

The technology continually improves with each interaction, resulting in faster, more accurate product recognition and quicker checkouts for customers over time.

Canadian Tire is a well-known Canadian retail company specializing in automotive, hardware, sports, leisure, and housewares sales. Canadian Tire is headquartered in Toronto, operates over 2,000 stores across eight different brands, and brings in over Can$17 billion in revenue annually.

Canadian Tire, particularly the Caledonia store, faced challenges with their traditional DVR security system. This included the difficult process of retrieving video footage for law enforcement and the inability to efficiently analyze customer behavior in the store due to limitations in existing technology.

Canadian Tire Caledonia opted for Solink's cloud-based video surveillance solution.

Solink provided a modern system that could integrate with Canadian Tire's existing hardware and provide more functionality:

• Solink was able to connect to cameras that belonged to three different generations.
• Solink was also able to provide Canadian Tire with a way to measure conversion rates.

The Caledonia store decided to upgrade their cameras to Hanwa's latest models to leverage the Solink platform's additional capabilities related to behavioral and conversion analytics.

By implementing Solink and upgrading their camera setup:

• Canadian Tire gained a more efficient and user-friendly surveillance system that made it easier and faster to access security footage, saving significantly in the process.
• Additionally, Solink's people-counting capability enabled Canadian Tire to better understand and improve customer conversions and sales.

The store could now accurately track the number of visitors and their purchasing behaviors. This led to more informed decisions regarding store layout, product selection, and customer service tactics, ultimately impacting the store's revenue positively.

Pres Les is a 50-year-old South African direct-to-consumer sales company that sells luxury bedding, home accessories, and cookware.

Pres Les embarked on a massive digital transformation initiative that included new service delivery tools, a new website, extensive cloud infrastructure, and other digital innovations.

As new digital systems came online, Pres Les had to deal with phishing attacks, ransomware, and other cyberattacks that could not be handled using native Microsoft 365 security capabilities.

Pres Les employees had to deal with a large volume of emails from customers, suppliers, and consultants. Some of this communication included proof-of-payments and other business-critical communication. Pres Les partnered with BDO and Ironscales to deploy a proof of concept (PoC) which was overwhelmingly successful.

Based on the success of the PoC, Pres Les decided to implement Ironscales' AI-enabled email filtering and advanced phishing detection capabilities.

After implementing Ironscales, Pres Les saw tremendous improvements. In a three-month period, Ironscales:

• Inspected over 400,000 emails.
• Identified and prevented over 451 incidents.
• Remediated over 1,000 emails.

Ironscales continuously runs in the background and blocklists suspicious emails, allowing users to safelist the correct ones if not identified by AI. Since deploying Ironscales, Pres Les' IT team is spending less time dealing with these attacks and instead are focusing on more productive activities.

• Minimal training in loss prevention
• Basic security measures without specialized roles

• Increased awareness regarding loss prevention methods
• Basic training programs available

• Roles with specific focus on loss prevention exist
• Staff receives ongoing training in loss prevention strategies

• Loss prevention integrated into various business functions
• Staff across departments are engaged in loss prevention

• Culture of loss prevention throughout the organization
• Highly trained staff, specialized roles in analysis and technology

• Ad hoc and reactive processes
• Limited standard procedures for handling theft or shrinkage

• Structured processes for handling incidents
• Regular security audits

• Systematic processes for loss prevention, driven by insights from data analysis

• Cross-functional processes established

• Proactive and predictive processes
• Continuous refinement based on real-time data

• Basic security equipment like locks and simple cameras

• Upgraded surveillance systems and anti-theft devices like EAS tags are implemented

• Introduction of data analytics tools for monitoring and reporting

• Implementation of advanced technologies like AI and ML for predictive analysis

• Cutting-edge technology like AI-driven surveillance, real-time analytics platforms, and sophisticated data integration tools

• Minimal collection and use of data

• Initial collection and review of theft and fraud data
• Limited analysis

• Regular analysis of theft and fraud data
• Use of data to identify patterns and inform loss prevention strategies

• Deep analysis of data for predictive insights
• Integration of data across different systems

• Real-time data monitoring and analysis
• Use of big data and predictive modeling

• Basic incident tracking, with no dedicated KPIs for loss prevention

• Tracking of basic KPIs like incident rates and training completion

• Dedicated KPIs including shrinkage rates and inventory accuracy

• Advanced KPIs measuring the effectiveness of loss prevention systems

• Comprehensive KPIs including response rates, AI effectiveness