STRATEGIC ADVISORY SERVICES PROVIDER

BUSINESS PROBLEM

This Strategic Advisory Services Provider (SASP) engaged Scalesology to develop a targeted, data-driven marketing strategy for another organization. The organization aimed to expand its reach to small businesses across North America. To achieve this goal, it was crucial to analyze and understand the underlying buying patterns within their small business data.

SCALESOLOGY IN ACTION

The SASP provided Scalesology with raw customer system data to detect patterns and define customer segments. To enhance the quality of the customer segmentation exercise, this raw data was merged with multiple external data sources. The final dataset included:

1. Internal Marketing Data: Extracted from the organization’s CRM system.

2. Third-Party Data: Incorporating demographic and firmographic information.

The merged dataset was cleaned, transformed, normalized, and standardized to prepare it as input for clustering machine learning (ML) models. These ML models uncovered patterns within the data and segregated it into distinct segments for targeted marketing and internal business development.

Based on business requirements, the segmentation exercise was conducted in three iterations:

1. First Iteration: Using all customer data and engineered features (K-Prototype).

2. Second Iteration: Using all customer data without feature engineering (K-Prototype).

3. Third Iteration: Using only internal data (K-Modes with internal attributes).

Post-Clustering Analysis included:

1. Feature Importance Analysis: Conducted using LGBM Classifier and Shapley Values.

2. Cluster Analysis and Visualizations: Created using Power BI

RESULT

The clustering and feature importance analysis identified distinct market segments, enabling the marketing firm to develop targeted marketing strategies for each segment on behalf of the organization.

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SERVICE REFERENCES​

Data and Analytics

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