Data-E-Labs| Retail

Retail

Leverage advance analytics to get smarter retail operations

Retail sector is facing a need to establish new business strategies to stay competitive, The sector is growing with a decent pace but behind this explosive growth the profit margins get trimmed. Companies are constantly working on reducing their operating costs to maintain margins, but the bigger challenge is to retain and grow new age customers segment who are well informed, digital savvy and seek personalized experience. Major retailers operating globally are using advance analytics, and machine learning to survive and grow in hypercompetitive market environment

DATA-E-LABS EXPERTISE

We have a proven expertise in the retail sector and unmatched capability to analyze terabyte of data to be able to understand customer's preference, requirements more precisely. We are constantly monitoring industry changes and bringing in innovative ways of using analytics to support business that help companies to perform more efficiently and at lower cost.

More about Retail Analytics

Price Elasticity Analytics

Let our analytical process provide you an advanced view of the response of customer demand to price movements while concurrently synthesizing revenue growth and profit margins.

Product Mix Analysis

Use our analysis tools to select the optimum in-store product mix from multiple scenarios that also inform the impact on financial performance.

Assortment Planning

Make the best decision on the breadth of products to store, factoring in demand spikes and seasonality, without compromising on the depth of stock and supply chain capacity

Market Basket Analysis

Market basket analytics reveal associative customer behaviour that will help you connect linked products and revamp in-store locations.

Stock Optimization

Balance storage of large volumes of stock keeping units with supply schedules, demand fluctuations, store capacity and customer service goals.

Site Analytics

Weigh up demographics and profiles of potential customers, market potential, competition analysis, estimated revenues and site impact on existing store network while selecting a high potential site.

Layout Management

Draw on multiple mapping alternatives to optimize space utilization. Choose from a variety of floor plans – straight, geometric, angular, diagonal and mixed.

Profitability Analysis

Get inputs of where each rupee of store revenue comes from and where it goes. An analytical tool that encompasses rental, product mix, pricing, staff costs, per sq.ft. revenue/cost, and more

Stock Optimization

Slash your inventory holding costs by using demand forecasting, management of purchase order flows, just-in-time vendor supplies, inventory budgeting, inventory turnover computation, and the use of ‘what-if’ matrices

Market Mix Modeling

Evaluate your marketing return on investment through regression and econometric techniques that give you a clear picture of the impact of pricing, promotion and distribution to revenue

Customer Analytics

Harness business intelligence (BI) tools, loyalty program response data, customer’s order configuration, etc. to analyse customer behaviour and decide on product mix, promotion campaigns, pricing, and personalized offers

Promotion Effectiveness

High quality quantitative techniques for you to assess whether or not loyalty reward programs, price discounts, special offers, incentives and coupons, special packs, etc. are giving you results

Cross Channel Analytics

Capture data from social media, web, advertising campaigns, online click paths and customer behaviour to deliver customer-centric offers and marketing messages.

Media Analytics

Design your plans taking account of customer e-mails, social media posts, comments, shares, likes, tweets - both bouquets and brickbats.

Customer Conversion

Empirical measurement of customer conversion using data from video cameras /sensors correlated to point of sales data, web site clicks, measurement of the impact of in-store advertising campaigns on card swipes, etc.

Customer Experience

What it takes to create store recall and boost business.

Customer Segmentation

An algorithm that improves customer targeting by analyzing customer location, first purchase, purchase path, gender, age, income bracket and device used (iPhone, BlackBerry, etc.).

Cross Sell, Up Sell Modelling

Customer segmentation data is taken forward to strengthen customer engagements by using predictive analytic models to offer / recommend the ideal mix of products to customers. The model also allows you to up-sell products with higher margins

Customer Lifetime Value (CLV)

Build your acquisition campaign around analysis of correlation between cost of customer acquisition and forecast of lifetime revenue generation.

Customer Loyalty Analytics

Leverage customer purchase patterns. analyze behaviour of first time and repeat customers and build programs that will boost customer spends.

Retention Analytics

Design customer retention strategies using business intelligence (BI) tools to chart purchase frequency, average order value, acquisition source, time span between purchases.