The advent of ecommerce, competition from global players and changing customer demographics have forced traditional brick and mortar stores to reinvent themselves. NeenOpal's retail analytics capabilities are helping some of the major retailers across different formats,to derive actionable insights by leveraging the power of data and overcome their challenges.
Convenience stores that deliver a memorable in-store experience to their customers - be it in terms of higher engagement levels, product availability at all times or reduced waiting time at POS , stand to earn higher customer loyalty and higher sales.
NeenOpal's suite of solution for convenience stores help store managers adopt a data driven approach to select the product assortment for each store. Drive impulse sales and improve Average Transaction Value through Market basket analysis. Implement a differential pricing strategy that helps capture the customers willingness to pay through Dynamic Pricing models.
Our solutions are delivered via a software-as-a-service(SaaS) model that helps us deliver immediate results and a quick ROI to our customers.
Catchment Area Analytics: Competition Geo-Platform
Dynamic Pricing and Promotions
Supermarkets around the world are leveraging predictive analytics to find answers to some of their most pressing business challenges.
Supermarket solutions by NeenOpal can help supermarkets identify and retain high value customers, increase in-store engagement levels, enhance personalization of offers at individual customer level, optimize product assortment, estimate demand and optimize inventory levels, etc., helping them to differentiate from the competiton.
Customer Portfolio Analytics
Loss Prevention Analytics
Demand Planning and Sales Forecasting
Health and Beauty Retailers
Our customer analytical models help predict and minimize customer churn. Association mining models provide concrete action points for product placement in shelves to drive impulse sales and improve Average Transaction Value.
Improve demand forecasting by integrating effect of seasonality and contextual parameters. Direct impact on bottom-line through end to end inventory optimization. Proactively identify aged and soon to be expired medicines to minimize losses.
Drug Inventory Management
Sales Forecasting Using Neural Networks
POS Transaction Analytics
Fashion and Footwear
Crunching key store metrics such as footfalls, ATV help segregate and identify the performance of each department. For example, how effective was the marketing department in driving consumers to the store? Markdown management minimizes end of season left over inventory to improve revenues by over 10%. Return analytics help identify and address the root cause of product returns.
Customer Returns Analytics
Fashion Product Development Analytics
Intelligent Markdown Management & Fast Fashion Sales Forecasting
Virtual Reality and Augmented Reality Analytics
Fast Fashion Retail Distribution Analytics - Inventory Management
Fashion Color Trend Forecasting
Implement assortment optimization tools to select the right product mix for each region. Determine the correct levels of replenishment and allocation between warehouses and stores for optimizing network and maximizing profitability.
Key-Value Item Analytics
Footfall Counter Analytics
Customer Portfolio Analytics
Digital Marketing & Social Media Analytics
Use analytics to minimize losses due to expiry of products while avoiding stock outs. Optimize promotions and improve customer loyalty by implementing recommendations of RFM modelling.
Perishable Product Analytics
Hyper Localized Assortment Analytics
By using insights based on predictive analytics, restaurants can discover the root causes and factors that drive revenue, prescribe actionable recommendations to change business operations and strategies to optimize profitability. Restaurants drive performance by applying insights from advanced analytics in the following ways:
Analytics-driven Menu Engineering can help restaurants maximize profits and improve their customer satisfaction levels.
Increase Customer Engagement
Restaurants can segment their customers to create personalized promotions resulting in increased profitability & enhanced customer engagement levels.
Restaurants optimally staff their stores to meet forecasted customers' demand at different time periods & measure staff performance on key KPIs
Analytics can help improve the speed of service, reduce food wastage by better forecasting product usage and adjusting purchasing and inventory accordingly.
Time of Day/Day of Week Analysis
Cannibalization effects of new products or promotions can be detected by drilling down into different time segments rather than using only averages.
Social Media Listening:
Restaurants can gauge their social media sentiments and quickly figure out the areas where they should improve to attract customers making the comments.
Picking up Store Location:
Big data analytics is helping retailers to fine-tune how they to pick up a store location with the ultimate goal of driving more traffic and boosting sales.
Incorporate latest trends from social media in product design and assortment. Identify slow moving products and minimize losses, on account of leftover inventory, through promotions and offers.
Dynamic Pricing Modelling
Promotion Response Forecasting
Location Based Analytics
Product Trends Platform - Text Mining & Social Media Analytics
Large Organizations as well as Small & Medium Enterprises across Asia and Europe