A manufacturing client sought to evaluate their channel partners to determine whether they needed more dedicated channel managers or could consolidate some channels. The goal was to optimize channel partner relationships and improve profitability.

We analyzed sales volume data from the client’s channel partners, spanning the past 4 years. The data included details on the volume of various products moved through each channel partner. To prepare the data:

• We standardized all product volumes into a comparable measure, enabling fair comparisons across different product categories.
• We engineered additional features to capture key metrics such as frequency, recency, and monetary value (FRM) for each channel partner.

We employed R and the K-means clustering technique to segment channel partners. This approach involved:

• Creating 30+ features that represented channel partner behavior, including FRM metrics.
• Clustering the data into 7 distinct segments, labeling them based on shared characteristics.
• Quantifying the lifetime value of channel partners to identify high-value partners and understand their distribution by region and product type.
• Identifying product preferences across segments to recommend targeted cross-selling strategies.

Using the insights from the segmentation analysis, we provided the following recommendations:

• Prioritize high-value channel partners by offering dedicated management support and tailored incentives.
• Consolidate or phase out unproductive channel partners.
• Develop targeted cross-selling strategies for products popular in specific segments.
• Implement a sales incentive program based on volume thresholds to drive performance across all channel partners.

The client implemented the recommendations, which led to the following outcomes:

• Transitioned away from underperforming channel partners.
• Launched a training program for emerging channel partners.
• Rolled out a sales incentive program that contributed to a 24% increase in gross profit in the subsequent year.