Sales & Marketing Analytics

Sales and Marketing Analytics uses the Marketing Mix Model, which is a statistical marketing method that attempts to determine the effectiveness of marketing campaigns and initiatives by taking apart data and attributing contributions to different marketing tactics and factors to better predict future success. It further allows organizations to understand consumer behavior with regard to exposure to different advertising methods and techniques.

The company can use Sales and Marketing Analytics to identify relevant macroeconomic indicators with statistical analysis, econometric time series modeling, and supervised machine learning. Building such ensembles and hybrid models also allows figuring out the factors affecting the business volume growth.

High inventory carrying costs as well as low inventory hurts the business. Advanced Analytics helps to identify inventory gaps by using Demand Forecasting for future periods and aggregation of predicted demand for each distribution center. It allows the company to streamline the production plan for each item and alter its business and marketing strategy to satisfy expected demand from its customer base. This further helps reduce risks and create an accurate budget that helps efficient financial decisions for improving profit margins, cash flow, and allocation of resources.

Advanced Analytics and Customer Journey mapping allow companies to view the sales process from the customer perspective to find out what they are doing well and how they can improve their sales model. Deriving an Analytics-driven journey map helps identify experience or service gaps in your buying process that you may not have noticed otherwise. For example, a missing instant chat feature on your website that helps resolve urgent customers' queries. You can easily plug this gap by adding a Chabot, a frequently asked questions (FAQ) section, or a knowledge base page.

While contemplating an ideal pricing strategy, it is imperative for businesses to determine how sensitive or ambivalent their target customers are to price changes. Intelligent and highly agile Pricing Analytics solutions enable you to accurately identify patterns and trends in customer behavior and track key pricing metrics to create the right pricing strategy that maximizes profit.

All industries, both B2B and B2C, can make efficient use of Pricing Analytics to create optimal pricing strategies and optimize their profitability and sales. The principal industries making use of Pricing Analytics are Retail and CPG, food and beverage, BFSI, Communication and Media, Automotive, Transportation and Logistics, Healthcare and Pharmaceutical, and Manufacturing.

Advanced Analytics and AI-driven recommendation engines provide businesses with a better-priced product and recommend a complementary product to the existing customers, respectively. Upsell/cross-sell techniques give businesses the power to leverage customer behavior to optimize customer service efforts. These techniques provide the customers with customized product suggestions, leading to improved customer lifetime value and revenues for businesses.

Customer Segmentation Analytics address critical business questions. Effective customer segmentation uncovers consumers' need states, mindsets, behaviors, demographics, and social profiles to identify their profit potential to tailor your marketing strategies to align with each segment at a micro level. Such Advanced Analytics solutions allow organizations to shift their approach from product-centric to customer-centric and improve the effectiveness of their marketing campaigns through a shaper understanding of their customer base.