Today, a retailer needs to keep track of the rate of attrition in their customer base. Acquiring new customers is far more costly than retaining existing customer as retaining customers maintains volume and revenues at lower cost, increases customer lifetime value, and should create loyalty from limited experience and habit. Customer Churn analysis help organizations identify key factors driving churn and to design customer churn prevention and win back strategies to improve customer retention, loyalty and Life time value.
Every customer is different and so is their behaviour. To understand the vast and diverse universe of the customer base, we need to segment the customers based on their characteristics. These characteristics could be based on the requirements, preferences, lifestyles or life stages. Our segmentation approach is driven by the industry and the data. The data driven customer segment discovery allow us to understand the customers in the best possible manner.
Market Basket Analysis
Market Basket Analysis (MBA), also known as affinity analysis, is a data mining technique used to understand the purchase pattern of the shoppers. This analysis unveils the hidden association between the products or the product groups. This analysis is highly recommended for understanding cross-selling opportunities in the associated categories as well as up-selling opportunities within categories. Advanced Market Basket Analysis provides an excellent way to get to know the customer and understand the different behaviours.
High competition, consumer price sensitivity and pressure on margins are the key challenges that a retailer faces every day. Pricing optimization has been shown time after time to increase sales and margins; it is one of the most direct routes between analytics and the bottom line. It is designed to enable retailers to optimize base prices to achieve their sales, volume, profit and price image objectives for regular, everyday items. Rudder Analytics leverages point-of-sale information for seasonal and non-seasonal data to run probability and forecasting algorithms to create a set of demand curves for particular SKUs in particular stores or clusters. The demand curve identifies the products that are the most and least price-sensitive. Additional optimization routines leverage these demand curves to determine optimal recommended pricing.
Marketing Mix Modeling
Optimize your Marketing Mix. The old complaint that, “Half of the money I spend on advertising is wasted; the trouble is I don’t know which half” no longer has to be true. Through marketing mix modeling, we determine where and how much the retailers should spend their marketing resources. We use econometric models, along with the deep understanding of your market and industry, to measure the performance of your marketing mix. Our optimization techniques are flexible and are specific to the business challenge; hence maximize sales and produces highest return for your marketing investments.