Retail
Optimization
of inventory replenishment
in retail stores.
AI-driven virtual try-ons to enhance shopping with realistic virtual models.
Optimized customer experience through targeted product recommendations.
Sentiment analysis on reviews, ratings for informed decision-making.
Trends
30%
of global retailers will use AI to increase inventory visibility, reduce out-of-stock scenarios, and improve profitability by 2025
30%
cost reductions due to AI-powered supply chain optimization
75%
inventory reductions by AI powered route optimization, warehouse management, and supplier selection
2-5%
increase in retailer margins due to AI-enabled dynamically adjusted prices based on real-time demand, competitor pricing, and other factors
Use Cases
Demand Forecasting
Leverage AI to predict inventory needs across locations and time periods based on customer demand signals, ensuring product availability.
Personalized Recommendations
Use customer data to build AI systems that suggest relevant products to each shopper, increasing engagement and sales.
Conversational Commerce
Implement conversational agents to provide quick customer support, product information, and personalized interactions. Inventory Optimization: Employ AI to forecast demand fluctuations and optimize inventory levels, reducing costs.
Fraud Prevention
Build AI models to detect fraudulent transactions in real-time, minimizing losses.
Targeted Marketing
Apply AI to segment customers and deliver tailored promotions via preferred channels, improving campaign ROI.
Product Placement Optimization
Leverage computer vision and sensors to track customer in-store behavior including product interactions, shopping paths, and dwelling times.
Analyze this data using AI algorithms to gain insight into customer preferences for product categories, brands, shelf placement etc.
Continuously optimize planograms and product layouts within the store to match observed consumer preferences. Place products with higher affinity together to increase cross-selling potential.
Analyze this data using AI algorithms to gain insight into customer preferences for product categories, brands, shelf placement etc.
Continuously optimize planograms and product layouts within the store to match observed consumer preferences. Place products with higher affinity together to increase cross-selling potential.
Our Benefits
Increased Revenue
Personalized experiences drive higher conversion rates and customer lifetime value.
Operational Efficiency
Optimized demand forecasting and inventory management reduce waste and stockouts.
Customer Loyaltyg
Relevant recommendations and excellent service improve satisfaction and retention.
Risk Reduction
AI-enabled fraud prevention minimizes financial losses.
Strategic Insights
Customer and market intelligence inform planning and investments
Our Methodology
PLAN
Draft approach, methodologies and work plan to achieve set goals
DEVELOP
Custom built solutions to achieve set goal
IMPLEMENT
Deploy solutions to production
TRAIN USERS
Provide comprehensive training to end-users on utilizing AI/ML solutions effectively
PROBLEM STATEMENT
Initial discussions to understand the business pain points
MANAGE
Hypercare, measurement and A/B testing for ongoing improvement and refinement as required before transitioning into BAU
CONSULT
Narrow down pain points to tackle for optimum outcomes and define project goals