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The Need for Data Analytics in Retail
Factors contributing to growing demand
Acceptance of an Omni channel or multichannel retailing strategy.
Expanding need to improve end-user experience and capitalize on market dynamics.
Growing amount of data in the retail industry.
Optimizing inventory and ensuring on-shelf availability of products.
How you can use Analytics to optimise your retail business
Key Areas in Retail where Neostats’ Data Analytics can optimise the process
Solutions Offered
Promotional Campaign Overview
Enable businesses to come up with the right promotion strategy to improve awareness, footfall, revenue, reach and referrals.
- Overall Sales with and without promotion,
- Customer Footfall
- Average basket size with and without promotions
Department and Product Overview
Deep dive into department and product performance
- Store Health & Performance
- Which are the top and bottom selling categories during promotions ?
- Cross selling and upselling categories
- Internal Benchmarking
- Target vs Actuals
Smart Store Analysis
We further provide a store level analysis, which helps retailers to enable targeted promotions and increase sales.
- Impact of external factors on store performancÏ
- Store assortment
- Customer foot fall
Customer Analysis
Solution deep divers in to customer demographics to observe potential customer personas
- Which income group respond well to which category of promotions ?
- Target audience: Targeting the right customer segments for better promotion effectiveness
Customer Analytics
Neostats’ cutting edge customer analytics harness AI, machine learning, and deep data engineering to help retailers understand customer behavior at a granular level, enabling hyper-personalized experiences that drive engagement and loyalty.
- Behavioral Segmentation: Identify unique customer segments to deliver personalized offers and experiences.
- Churn Prediction: Proactively reduce churn by predicting which customers are likely to leave and why.
- Targeted Campaigns: Increase the effectiveness of marketing efforts with data-driven, highly targeted customer outreach.
Sales Analytics
Our sales analytics solutions deliver actionable insights through AI and predictive modeling, helping you improve forecasting, optimize pricing, and increase revenue growth while staying ahead of market trends.
- Sales Forecasting: Anticipate future demand patterns to streamline inventory and maximize sales.
- Price Optimization: Implement dynamic pricing models to react quickly to market shifts and consumer demand.
- Promotion Performance: Measure and refine promotional campaigns to maximize ROI and reduce wasted spend.
In Store Analysis
Neostats offers top of the line AI driven in- store analytics. By using sophisticated data modeling and real-time tracking, you can optimize store layouts, reduce operational bottlenecks, and create better shopping experiences that increase both footfall and conversion.
- Foot Traffic Analysis: Use data to analyze shopper movement and optimize store layouts for increased sales.
- Heatmaps & Dwell Time: Understand customer interaction with product displays to enhance in-store engagement.
- Checkout Optimization: Reduce wait times and enhance the checkout experience with predictive queue management.
Supply Chain Analytics
At Neostats, we use our advanced analytics solutions to enable retailers to gain real-time insights across the entire supply chain, improving forecasting accuracy, reducing stockouts, and optimizing overall efficiency. With data-driven decision-making, retailers can reduce costs and increase fulfillment speed.
- Inventory Planning: Leverage predictive analytics to manage stock levels efficiently and reduce excess inventory
- Demand Forecasting: Predict and prepare for changes in demand using AI-powered models
- Supplier Performance Monitoring: Track and improve supplier performance by analyzing lead times, quality, and delivery.