Customer Loyalty Analysis for a Leading Pharma Player in Europe

Oct 22, 2021

What you’ll find in this case study:

  • Pharmaceutical Industry Overview
  • About the Client
  • The Business Challenge
  • The Customer Loyalty Analysis Solution
  • The Customer Loyalty Analysis Business Impact
  • Customer Loyalty Analysis Predictive Insights

Highlights of the Customer Loyalty Analysis Case Study

ClientA Europe-based pharmaceutical company
Business ChallengeImprove customer loyalty and maintain a long-term customer relationship
Solution ImpactIdentified metrics most important for establishing long-term customer loyalty; created loyalty segments to better market offerings to customers

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Pharmaceutical Industry Overview

The global pharma industry is witnessing immense growth due to the presence of numerous competitors who are involved in the production, development, and marketing of medications. With the majority of revenues coming from the United States and Europe, the pharma industry is witnessing a high demand for pharmaceuticals such as pain drugs, antihypertensives, and antidiabetics. In the pharma industry, the growing demand among the customers is further triggering the need for research and development in the segment. Although the pharma industry is witnessing relentless demand among the end-user segments, certain factors are responsible for the hindrance of the market’s growth. These factors include:

  • Rising customer expectations: In recent years, with the shift toward a consumption-driven economy, countries across the globe are imposing cost constraints on healthcare service providers. Moreover, with the customers becoming more informed than ever before, they are looking for clinically and economically better alternatives as compared to the existing alternatives.[spacer height=”20px”]
  • Policy reforms: Today, any changes in the healthcare regulations significantly affects the pharma industry. Leading policy reforms are in place to ensure the quality, safety, and efficacy of therapeutic drugs to target audiences. Moreover, overseas manufacturers are expected to operate to the general standards to meet the licensing requirements of the specific region.

To address such issues and meet the relentless demands of the target audience in the pharma industry, leading organizations are utilizing customer loyalty analysis. Customer loyalty analysis ensures better visibility into the customer’s tastes and preferences and offers better satisfaction to the customers.

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About the Client

The client is a leading pharma manufacturer in Europe.

The Business Challenge

The client wanted to improve customer loyalty and maintain a long-term customer relationship with the pharmacies and hospitals that they were selling to. Also, the rising costs and increased complexity of the pharmaceutical network combined with the emergence of local players had put the client under enormous pressure to maintain their existing market share. Limited customer orientation of marketing, sales, and after-sales channels resulted in the lack of understanding of products and services required by each account. Moreover, due to multiple information systems capturing information about their marketing, sales, and customer data, the organization had a splintered view of their customers across different customer contact points.

After hearing about Quantzig from another industry veteran, the client decided to connect with our experts to understand what they can achieve with us.

To address the customer’s requirements and enhance loyalty, the client needed a holistic data management and analytics solution to integrate the data spread across multiple soiled systems and analyze it to achieve the following objectives:

  • 360-degree view of the accounts, account structure, and decision-makers
  • Value of customer segments
  • Offer account-specific products and services
  • Achieve better customer loyalty and centricity

The Customer Loyalty Analysis Solution

To understand the relative preferences of the customers, the customer loyalty experts at Quantzig:

  • Finalized business scope and consumption use cases after multiple client meetings
  • Multi-source data integration at various levels (account, channel, product, and DMA) to create a single analyzable data set
  • Data cleansing and business rule application to create final data set for analysis
  • Developed clustering and multivariate regression-based models to provide insights for improving customer loyalty and sales
  • Simulations to analyze the probability of winning a bid based on account-specific parameters
  • Designed self-generating decision boards in tableau to analyze:
    • Customers across different segments
    • Account penetration and marketing response index
    • Price sensitivity and simulations

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The Customer Loyalty Analysis Business Impact

The customer loyalty analysis engagement offered by Quantzig:

  • Provided a 360-degree view of the account, sales, and marketing information for the client to have complete information on account structure, product penetration, marketing response, and sales
  • Segmented the accounts into four different segments – Bronze, Silver, Gold, and Platinum based on length of the relationship, revenue generated, the volume of sales, and the number of products purchased
  • Prioritized key decision-makers and offered differentiated services to Gold and Platinum accounts
  • Identified metrics that were most important to establish long-term customer loyalty based on the contractual agreements using multivariate regression models
  • Understood the tenure of relationship, repeat business, products availed, prices quoted, promotions, and the discounts applied
  • Provided recommendations on an ideal range of parameters based on the account segment

Customer Loyalty Analysis Predictive Insights

  • Created price elasticity models for multiple products being sold to the individual accounts to recommend prices that would improve the volume of sales as well as maintain profit margins
  • Allowed the client to adjust prices and discounts for wholesale contracts so as to negotiate based on real-time information
  • Identified variables that significantly affect the deal win as well as losses to improve sales pipeline velocity by ensuring that the clients’ sales activities were focused on value-adding tasks that maximized the probability of sale
  • Created a Deal/Win-loss simulator to provide real-time insights to the client by ensuring that for each individual account and their sales activities (sales representative, number of face-to-face meetings, samples provided, and calls made) were optimized and the chance of success was maximized

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