Retail & Consumer Goods
Stay competitive in retail and consumer goods with AI
Elevate sales performance, optimize operations, and ensure customer delight with tailored AI products and solutions
Your growth partner in AI for retail and consumer goods
In the dynamic and fast-paced landscape of Retail and Consumer Goods, swift adaptation is key. Today’s consumers demand agility and personalization and businesses must evolve with these changing trends and expectations. Fusemachines offers over a decade of expertise in delivering AI-powered speed and customization to the industry. Collaborating with businesses at every stage of their AI journey, we provide tailored AI products and solutions to help retail and consumer goods companies tackle these challenges head-on.
Here’s why you should partner with us
10+ years of consistently delivering exceptional AI products and solutions in the retail & consumer goods Industry with an outstanding CSAT Score of 9+
Expert understanding of business challenges and evolving retail & consumer goods landscape
At the forefront of AI-assisted and innovative data engineering and application development
Our areas of expertise in retail and consumer goods
Personalized recommendations
Our AI-powered personalized recommendation systems help businesses shorten the purchase journey for customers through accurate matching, reduce checkout time and increase average basket size.
Fraud detection
We offer highly capable fraud detection solutions designed for retail & consumer goods businesses to handle today's evolving landscape of fraud tactics by alerting anomalies and threats in real-time.
Price optimization
We help companies optimize and offer the best prices with our highly reliable and accurate AI-driven competitive price intelligence solutions. Outperform your competitors at every turn.
Supply chain optimization
Optimize retail supply chains with our AI-driven solutions. Maximize efficiency, reduce complexity, and manage inventory for peak performance.
Customer analysis
Improve business operations, elevate your advertising campaigns, and drive profitability with our data-driven customer analytics solutions tailored for retail industry enterprises.
Demand forecasting
Leverage our AI-powered demand forecasting tools to anticipate consumer trends and optimize inventory levels. Meet your market demand efficiently, minimizing both stockouts and excess inventory.
Market basket analysis
Boost sales through our AI products & solutions for market basket analysis. Identify product affinities, optimize placements & increase cross-selling for an enhanced shopping experience.
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SCHEDULE A CALLOur AI engines expedite retail & consumer goods business value with industry-specific solutions
Answer GenTM
A GenAI based Answer Generation Engine from Documents
Fraud Detection AI EngineTM
Accelerate how you identify emerging fraud patterns and investigate them with AI
Forecast AI EngineTM
Advanced AI for Demand & Inventory Forecasting
Our retail and consumer goods case studies
Dive into our case studies, showcasing the powerful impact of innovative AI products and solutions in revolutionizing retail & consumer goods.
Precision and Efficiency in Resale Authentication with AI
A prominent luxury resale platform used AI to enhance accuracy and efficiency in authentication and valuation.
Problem/Requirement
- Difficulty extracting crucial information from different types of luxury bag images, impacting downstream analytics.
- Adapting to an expanding variety of bag models and variations posed a significant hurdle.
Solution
- Developed an advanced authentication pipeline using InceptionResNetV2, enhanced with data processing and a Fusion Model trained on an MLP network.
- The system focuses on key metrics such as sensitivity, specificity, and accuracy, and is continuously optimized through advanced image processing techniques, including orientation and anomaly detection.
- A feedback loop, incorporating user and real-world data, further refines the model.
Results
- Enhanced key-value extractions for precise information from diverse luxury bag images.
- Surpassed system limitations, fortifying authentication and valuation processes.
- Optimized operational efficiency, reducing processing time for a larger inventory.
AI-powered Forecasting Models for a Luxury Fashion Company
Built forecasting models at channel & allocation levels for an american multinational luxury fashion holding company.
Problem Statement
- Build a model to forecast 8 weeks of future sales for all products sold in North American outlet and retail channels.
- Determine the quantity of units to manufacture for each product, destined for either retail or outlet channels, to eliminate the risk of stock-outs or stock pileups.
Solution
- Developed ETL pipelines to amalgamate sales, product, and inventory data.
- Executed exploratory data analysis to pinpoint sales-related features.
- Selected Multi-Quantile Recurrent Neural Network (MQRNN) based on error analysis.
- Designed a dashboard to visualize and assess model forecasts against real data, enabling dynamic feature adjustment for forecast interpretation.
Results
- Achieved a 50% enhancement in evaluation metrics (MAE, MAPE) with MQRNN.
- Attained precision with under 50 units error in weekly sales.
- Observed a ~25% average reduction in stockout probability in store.
A prominent luxury resale platform used AI to enhance accuracy and efficiency in authentication and valuation.
Problem/Requirement
- Difficulty extracting crucial information from different types of luxury bag images, impacting downstream analytics.
- Adapting to an expanding variety of bag models and variations posed a significant hurdle.
Solution
- Developed an advanced authentication pipeline using InceptionResnetV2, enhanced with data processing and a Fusion Model trained on an MLP network.
- The system focuses on key metrics such as sensitivity, specificity, and accuracy, and is continuously optimized through advanced image processing techniques, including orientation and anomaly detection.
- A feedback loop, incorporating user and real-world data, further refines the model.
Results
- Enhanced key-value extractions for precise information from diverse luxury bag images.
- Surpassed system limitations, fortifying authentication and valuation processes.
- Optimized operational efficiency, reducing processing time for a larger inventory.
Built forecasting models at channel & allocation levels for an american multinational luxury fashion holding company.
Problem Statement
- Build a model to forecast 8 weeks of future sales for all products sold in North American outlet and retail channels.
- Determine the quantity of units to manufacture for each product, destined for either retail or outlet channels, to eliminate the risk of stock-outs or stock pileups.
Solution
- Developed ETL pipelines to amalgamate sales, product, and inventory data.
- Executed exploratory data analysis to pinpoint sales-related features.
- Selected Multi-Quantile Recurrent Neural Network (MQRNN) based on error analysis.
- Designed a dashboard to visualize and assess model forecasts against real data, enabling dynamic feature adjustment for forecast interpretation.
Results
- Achieved a 50% enhancement in evaluation metrics (MAE, MAPE) with MQRNN.
- Attained precision with under 50 units error in weekly sales.
- Observed a ~25% average reduction in stockout probability in store.
“Fuse’s ability to deliver consistently outstanding solutions and strategic counsel is on par with their commitment to nurturing AI and tech talent through global education initiatives. Their unique role as experts and educators motivates us to continue finding ways to work together.”
Bharat Krish
President, TIME Digital and CTO
FAQs
AI enhances personalized marketing and shopping experiences for companies by analyzing customer data, enabling targeted campaigns, providing personalized product recommendations, implementing dynamic pricing strategies, and fostering consistent cross-channel interactions. These capabilities contribute to a more tailored and engaging customer journey, ultimately driving satisfaction and loyalty.
AI is pivotal in elevating the customer experience, seamlessly integrating online and in-store improvements. Through personalized recommendations powered by customer data analysis, AI enriches the online shopping journey by tailoring product suggestions to individual preferences. Additionally, implementing chatbots and virtual assistants enhances customer support, providing instant assistance online and personalized guidance in-store, fostering a positive and engaging shopping environment.
AI's predictive analytics capabilities anticipate customer needs and preferences, enabling businesses to proactively cater to individual in-store and online requirements. Optimizing inventory management ensures product availability and reduces out-of-stock instances, contributing to a smoother customer experience. Streamlining checkout processes and employing dynamic pricing strategies further solidify AI's impact, creating a cohesive and satisfying customer journey that seamlessly transcends online and in-store interactions.
AI-driven data analytics revolutionizes our understanding of consumer behavior and market trends. Through advanced algorithms, businesses can sift through vast datasets to uncover nuanced patterns and correlations. This deeper insight allows for more informed decision-making, enabling companies to anticipate trends and tailor strategies for sustained success in the competitive market.
Real-time processing capabilities further enhance agility, ensuring businesses can adapt swiftly to evolving trends. By continuously analyzing data, AI-driven analytics not only provides insights into current consumer behavior but also positions companies to proactively anticipate future shifts. This dynamic approach gives businesses a competitive edge in navigating today's rapidly changing market environment.
AI technologies, such as chatbots, recommendation engines, and visual search, play pivotal roles in enhancing e-commerce platforms. AI-powered chatbots streamline customer interactions by providing instant support, answering queries, and guiding users through the online shopping process. They enhance customer engagement, offer personalized assistance, and contribute to a seamless shopping experience, increasing customer satisfaction and retention.
Recommendation engines analyze user behavior, purchase history, and preferences to suggest personalized product recommendations. This improves the overall user experience by making product discovery more relevant and boosts cross-selling and upselling opportunities, ultimately increasing sales and revenue for e-commerce platforms.
Visual search enables users to search for products using images rather than text. By understanding visual cues, e-commerce platforms can offer more accurate and relevant search results, enhancing the efficiency of product discovery. This feature is particularly beneficial for users who may struggle to articulate their search needs verbally or in text, providing a more intuitive and user-friendly experience.
Incorporating these AI technologies into e-commerce platforms optimizes operational efficiency and transforms how users interact with online stores, fostering a more personalized and engaging shopping journey.
AI solutions are revolutionizing supply chain management, inventory forecasting, and logistics, offering businesses the tools to optimize operations and enhance efficiency. These include:
- Demand Forecasting Systems: Leveraging AI algorithms to analyze historical data and market trends for accurate predictions.
- Inventory Management Solutions: Utilizing real-time data analytics to track stock levels and automate reorder processes.
- Predictive Analytics for Logistics: Optimizing routes, predicting shipping times, and identifying potential disruptions.
- Supply Chain Visibility Platforms: Offering real-time insights into the entire supply chain for proactive decision-making.
- AI-Powered Supplier Management: Assessing supplier performance, monitoring risks, and providing optimization recommendations.
- Warehouse Automation: Streamlining storage, picking, and packing processes for improved efficiency.
- Blockchain for Supply Chain Transparency: Enhancing transparency and traceability in transactions within the supply chain.
- AI-Based Route Optimization: Optimizing delivery routes considering factors like traffic and weather.
These AI-driven solutions empower businesses to create agile, transparent, and resilient supply chain networks, ultimately boosting customer satisfaction and reducing operational costs.
AI plays a crucial role in enhancing security and preventing online transaction fraud through anomaly detection, adaptive machine learning models, and behavioral biometrics. Real-time monitoring enables immediate identification and response to suspicious activities, while predictive analytics assesses historical data to anticipate potential fraud risks.
Utilizing advanced AI algorithms, our Fraud Detection Engine enhances online security through real-time monitoring, adaptive machine learning, and anomaly detection. Beyond transaction scrutiny, the solution incorporates behavioral biometrics, device fingerprinting, and predictive analytics for a comprehensive approach to fraud prevention. This proactive defense ensures a secure online environment, prioritizing swift intervention and reinforcing trust in every transaction.
AI plays a pivotal role in automating operational processes, significantly enhancing efficiency, and driving cost reduction through:
- Task Streamlining: By handling repetitive tasks, AI allows human resources to focus on more complex and strategic activities, optimizing workforce productivity.
- Informed Decision-Making: AI algorithms analyze data to inform decision-making, reducing errors and improving the overall quality of operational outcomes.
- Predictive Maintenance: Monitoring equipment and systems, AI predicts potential issues, enabling proactive maintenance to avoid downtime and reduce costly disruptions.
- Workflow Automation: Implementing end-to-end workflow automation, AI minimizes manual interventions, accelerates process completion, and contributes to increased operational efficiency and substantial cost savings.
AI significantly contributes to product development by deeply understanding consumer needs and preferences. Leveraging advanced analytics and machine learning, AI processes vast amounts of data to unveil valuable insights into customer behaviors, preferences, and market trends. By analyzing social media interactions, customer reviews, and historical purchase data, businesses gain a nuanced understanding of what consumers truly value, enabling them to tailor products to meet specific demands and stay ahead in the competitive landscape.
AI enhances the product development lifecycle by facilitating predictive modeling and iterative testing. It enables businesses to forecast potential market success, optimize features, and identify areas for improvement. Through sentiment analysis and real-time data processing, AI ensures that products align with evolving consumer expectations, ultimately leading to more successful consumer-centric product development strategies.
AI promotes sustainability in retail by reducing waste and improving energy efficiency. Through advanced demand forecasting, inventory management, and smart energy systems, AI optimizes stock levels and adjusts lighting and climate based on real-time data, minimizing waste and energy consumption. It also extends sustainability efforts to the supply chain, manufacturing processes, and marketing, fostering intentional consumer choices and encouraging eco-friendly practices.
AI is a key driver in transforming retail and CPG operations towards a more environmentally conscious and sustainable future.
AI offers significant advantages in the highly competitive retail and consumer goods landscape. Personalized recommendations, driven by AI recommendation engines, cater to individual preferences, fostering customer loyalty. Predictive analytics enables retailers to stay ahead of market trends, optimize inventory, and make data-driven decisions, enhancing operational efficiency.
Implementing AI in supply chain optimization, customer segmentation, and dynamic pricing allows for streamlined operations and targeted strategies, giving businesses a competitive edge. Chatbots and virtual assistants improve customer interactions, while AI-driven fraud detection safeguards against potential threats. Embracing image recognition, visual search, and customer analytics further elevates the retail experience, ensuring companies stay at the forefront of innovation and customer satisfaction, ultimately securing a competitive position in the dynamic retail landscape.
