This case study demonstrates how a pharmaceutical company streamlined its customer profiling process for a successful product launch by automating data management, online profiling, real-time analytics, and deduplication, overcoming challenges like geographical complexity and manual data handling. The solution improved data accuracy, customer insights, and timeliness, while significantly reducing paperwork.

Measuring Lead Customer Potential for a Successful Product Launch in a Pharmaceutical Company

- [Business Context](#business-context)
- [Challenges in New Product ‘Go to Market’ Launch](#challenges-in-new-product-go-to-market-launch)
- [Our Solution](#our-solution)
- [Benefits from Our Solution](#benefits-from-our-solution)

Challenges in New Product ‘Go to Market’ Launch

A leading Pharma Company needed to identify and profile their prospective customers to determine their potential in the specified market space. This profiling would enable the creation of effective sales and marketing strategies for the “Go to Market” phase of their new product.

“A good effective product launch yields good revenue for the year.”

It is widely accepted that **“A good effective product launch yields good revenue for the year.”**

[Challenges in New Product ‘Go to Market’ Launch](#challenges-in-new-product-go-to-market-launch)

Accurate collection and detailed analysis of customer information is a critical step in any successful product launch. However, our client faced several challenges with their existing processes, which relied on manual Excel-based methods:

: Profiling had to cover a wide geographical market within a minimal time frame and limited resources, leading to handling huge volumes of data in Excel.

**Geographical Complexity**: Profiling had to cover a wide geographical market within a minimal time frame and limited resources, leading to handling huge volumes of data in Excel.

: Collecting and consolidating profiling data from the sales team on a day-to-day basis was a significant challenge.

**Data Consolidation Issues**: Collecting and consolidating profiling data from the sales team on a day-to-day basis was a significant challenge.

: Manual paperwork resulted in delays in communication and data processing.

**Communication Delays**: Manual paperwork resulted in delays in communication and data processing.

: Analyzing and segmenting profiled data was cumbersome, leading to difficulties in crafting specialty-based strategies.

**Limited Data Analysis**: Analyzing and segmenting profiled data was cumbersome, leading to difficulties in crafting specialty-based strategies.

: Handling varying analytics, particularly with partial or repeat profiling, was problematic.

**Inconsistent Analytics**: Handling varying analytics, particularly with partial or repeat profiling, was problematic.

: These bottlenecks often delayed product launches, which could adversely affect yearly sales targets.

**Impact on Timeliness**: These bottlenecks often delayed product launches, which could adversely affect yearly sales targets.

To address these challenges, we designed and implemented a robust, automated solution to streamline the profiling exercise. The key steps in the process were:

Centralized management of lead data, handling volumes of up to 1-2 lakh records.

**Lead Data Management**:
Centralized management of lead data, handling volumes of up to 1-2 lakh records.

Efficient organization and tracking of relationships with leads.

**Lead Relationship Management**:
Efficient organization and tracking of relationships with leads.

Enabling market-specific profiling of leads online.

**Online Profiling**:
Enabling market-specific profiling of leads online.

Providing real-time analytics readily accessible at users’ fingertips.

**Real-Time Analytics**:
Providing real-time analytics readily accessible at users’ fingertips.

Removing duplicate leads and logically combining profiling data for each unique lead.

**Deduplication**:
Removing duplicate leads and logically combining profiling data for each unique lead.

Applying statistical techniques to segment and target customers effectively.

**Statistical Analysis**:
Applying statistical techniques to segment and target customers effectively.

[Benefits from Our Solution](#benefits-from-our-solution)

The KEA-Lead Customer Profiling model provided a highly efficient profiling methodology and robust central customer database management system, delivering the following key benefits:

Relevant analytics for segmentation and targeting, aiding effective positioning of the new product launch.

**Strategic Insights**:
Relevant analytics for segmentation and targeting, aiding effective positioning of the new product launch.

Improved insights into customer-specific needs.

**Enhanced Customer Understanding**:
Improved insights into customer-specific needs.