Leading CPG Manufacturer Achieved a 22% Increase in Conversions Using Big Data Analytics

Big data analytics

Leading CPG Manufacturer Achieved a 22% Increase in Conversions Using Big Data Analytics

Quantzig’s recent study on sales force effectiveness for a leading CPG manufacturer guarantees a double-digit increase in conversion rate and improves sales performance using big data analytics.

Big data and its effectiveness in the retail industry

Big data analytics help retailers make informed business decisions and effectively manage the sales force. These solutions help companies to manage the issue of the seasonality of the products and the demand for inbound shipments. Data analytics help CPG companies improve their network coverage strategy and ensure maximum reach and acceptance at minimum cost levels. The data collected analyze the potential of the sales force, build achievable territories, identify weaknesses, and set expectations. Big data analytics help retailers manage multiple sales channels and guarantee that their sales forces are well positioned to succeed by using data efficiently. The big data analytics solutions by Quantzig helps retailers manage their sales force and minimize time and cost of territory coverage. The study also develops strategies that help companies maximize sales force coverage to improve sales performance and long-term profitability.

Workforce optimization is the biggest challenge faced by several leading retailers in the market. Big data tools offer tactics that optimize marketing and merchandising process, thereby increasing the productivity of the sales force. These data tools are used to analyze the predicting trends, forecasting demand, and optimizing pricing policies. Moreover, the analytics streamlines data in an effective way that results in efficient decision making and changing operations to match the dynamic changes in the market.

Customer analytics

The biggest advantage of using big data in the retail sector is identifying and profiling potential customers. These solutions help organizations evaluate their customers’ interests, requirements, preferences, and spending capacity. This information is leveraged while designing sales and advertising campaigns resulting in the motivated sales force. Moreover, sales force uses this information to provide personalized services, offer exclusive and customized product offerings, and discounts, thereby increasing the brand loyalty and retention rate.

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Boosting social listening capabilities

Big data analytics facilitates the management and analysis of large amounts of unstructured data collated from social media channels such as Facebook, Instagram, Twitter, and LinkedIn. Social listening is essential to improve customer interactions, brand loyalty, boost revenue, and profit margins. This solution analyzes data from tools such as natural language processing (NLP) to understand the buying preference of the end-user. Additionally, companies can use this data to train a sales force to understand the target audience and boost the sales revenue.

Outcomes and solutions offered

The sales force optimization assessment for leading CPG manufacturer integrates multisource data to facilitate end-to-end visibility on each sales person’s journey. Some of the solutions offered are as follows:

  • Developed dashboard for real-time updates and insights on salesperson performance, operational metrics, target and achievement details, and new prospects
  • Delivered comprehensive information on a new number and location of cities to maximize territory potential and optimize transpiration costs
  • Resulted in around 11% reduction in miles per sales person
  • Provided insights on potential opportunities for territory optimization across all divisions and effectively apply best practices
  • Projected centralization of network optimization effort across all the divisions of the company and reduce 17% of transportation costs

The complete case study on big data analytics that improves sales performance for a leading CPG manufacturer is now available.

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