Sales Effectiveness

Data-driven decisions for a changing world.

Industry
Healthcare

Why xtLytics
The visualizations provided by xtLytics gave the organization ability to visually and analytically see which information should they pay attention to, quickly review their information assets to determine on what they should focus on. It enabled them in leveraging that information, making decisions and gaining insights in everything from prescription and profile data to sales force activity.

Key Benefits:

  • Increase market share
  • Better target and focused approach
  • Optimizing market and sales strategy
  • Improving customer satisfaction

Business Challenges

The biggest challenge for every pharmaceutical company lies in leveraging big data for equipping their sales representatives with focused information about sales by territory, potential leads and competitor products. The inability of organizations to utilize the data, leads to creation of unrealizable objectives for sales representatives that are less likely to contribute in the organization bottom line. At the same time inefficient data utilization leads to poor information provided to sales representatives, thus leaving them handicapped during their sales pitch. The above-mentioned challenges faced in utilizing Big Data for sales effectiveness cumulatively affect the pharmaceutical firms in the following ways:

  • Inability to increase market share
    Firms are unable to prioritize and tailor territory specific strategies for sales and marketing.
  • Reduced sales per sales person
    Inaccurate physician segmentation and targeting, leading to reduced success per lead.
  • Market Erosion
    Firms are unable to track exact competitor product growth and market share. Leading them to act at a slower rate for adapting their marketing and sales.

xtLytics™ offering

Our approach for data synthesis varies from basic reporting which is a must have, to advanced predictive and prescriptive analytics to generate powerful insights:

  1. Reporting — The most basic version of analytics solution that focuses on building data repositories and reporting the current situation using simple and uni – or bi-variate data. Typical examples in pharma include adverse event reporting and PPSA-based reporting.
  2. Descriptive Analytics — Generating  actionable   insights on the current situation using complex and multi-variate data Typical examples include marketing, Return on Investment (Rot) measurement, customer journey analysis, and customer satisfaction analysis.
  3. Predictive Analytics — leveraging structured and unstructured data from a variety of sources to predict the likely future outcomes of events. Typical Examples in pharma include customer lifetime value analysis, revenue forecasting based on health outcomes, and prediction of adverse event occurrence.
  4. Prescriptive analytics — Prescribing action items required to deal with predicted future events using data from variety of sources. Typical examples for this kind of analysis are EHR (Electronic Health Records) analysis for insights into early-stage drug development, marketing strategy planning, and guidance to medical practitioners.

WHAT OUR CUSTOMERS SAY ABOUT US

Our Clients are biggest supporters. Would you like to know what our clients think about us?
Take a look for yourself in the testimonials below.

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