Retail Data Analytics

Data analytics for the retail industry is gaining momentum to stay abreast of the latest shopping trends by unearthing, interpreting and taking actions on meaningful data insights. Customer analytics plays a key role here to analyze various retail data points such as in-store, online, social media, mobile and more. Retailers are using predictive analytics to understand customers better.

Sigmoid’s retail data analytics practices help retailers develop intelligent machine learning models for retail enterprises, as well as set up, improve and manage big data infrastructures. Data analytics in retail therefore enables accurate identification of products that customers are likely to buy.

Our Retail Data Analytics solution enables retailers to:

Integrate multiple and disparate sources of data
Derive insights from real-time customer analytics data
Productionize demand forecasting and other ML models
Manage data quality and consistency across sources

Providing End-to-End Data Solutions at each stage of the Retail Value Chain

Demand and Sales ForecastingReal Estate PlanningCompetitor AnalysisProduct Trends
Price Elasticity and OptimizationMarkdown OptimizationMarket Basket AnalysisCross Sell and Upsell AnalysisCannibalization Analysis
Supply Chain OptimizationSupplier AnalysisInventory Planning and OptimizationRoute OptimizationShipment and Delivery Optimization
Category and Shelf ManagementAssortment PlanningStore Profitability AnalysisWorkforce OptimizationTheft Identification and Reduction
Pricing AnalyticsCustomer SegmentationMarket Mix OptimizationMarketing Effectiveness
Channel AttributionCampaign Optimization
Loyalty Program ManagementCustomer InsightsCustomer Lifetime Value Analysis (CLTV)Personalized Recommendations
Customer Retention and ReactivationDelivery Optimization

Our Expertise

Tackle frequent retail customer challenges like improving conversion rates and lowering acquisition costs through robust analytics

Demand Forecasting

Make accurate decisions on your data with our forecasting and planning expertise for efficient business planning across teams

Personalized Recommendation

Leverage our ML capabilities to get the best out of your data and offer unique personalized service for your customers

Data Lake Creation

Create global storage repositories for all data types from multiple sources to effectively store, manage and analyze retail data

Productionize & Scale ML Models

Build & develop production grade scaling of ML models to generate faster, larger, more accurate actionable insights and business results

Cloud Migration

Improve your business agility and save on costs by architecting and seamlessly migrating to the right cloud infrastructure

Marketing Effectiveness

Engage more effectively with your customers through personalized marketing and in turn, optimize profits and improve long term sales

Customer Lifetime Value

Explore ways to increase the value of your existing customers and drive growth for better overall customer experience

Customer Segmentation

Identify and understand the different behaviors and interests of the user and target them with relevant marketing content

Success Stories

Customer Analytics and Data Warehousing

Processed 250+ TB of customer and POS data, generating insights within seconds through effective data management.

Personalized Recommendation System

Used Reinforcement Learning techniques to create personalized strategies that boosted the firm’s profitability
by 8%.