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Identifying Segmentation Criteria for Customer Segmentation in the Aftermarket Industry

Customer segmentation is a crucial strategy in the aftermarket industry, where businesses provide support, maintenance, and replacement parts for equipment and machinery that customers have already purchased. Effectively segmenting customers based on their installed base data allows companies to offer more customer-aligned aftermarket services, optimize inventory management, and enhance customer satisfaction. Identifying the right segmentation criteria is important because it forms the basis for a successful customer segmentation strategy.

The criteria you choose should facilitate a deeper understanding of your customers, enable differentiation of their characteristics, and guide the development of customized aftermarket solutions. This, in turn, can lead to improved customer retention, increased sales of replacement parts, and more efficient resource allocation. Here are some criteria that we have observed and implemented for some of the leading OEMs:

Type of Equipment

Segmenting customers based on the type of equipment they have in their installed base is a foundational criterion in the aftermarket industry. Different types of machinery may have different replacement part needs and maintenance schedules. For example, a company specializing in industrial pumps might create segments for customers with centrifugal pumps and those with positive displacement pumps.

Industry or Application

The industry or application in which customers use their equipment plays a significant role in segmentation. Different industries have specific aftermarket requirements. For instance, a company supplying agricultural machinery might segment customers into farming, forestry, and construction sectors or a Food packaging company might segment customers into more specific Food sub verticals like Meat, Dairy, etc.

Equipment Age and Usage

Equipment age and usage are crucial criteria in the aftermarket. Older equipment may require more frequent replacement parts and maintenance, while heavily used equipment may experience replacements at a faster rate. Segmenting based on age and usage patterns helps specific service and replacement part offerings accordingly. For Example, You can create a segment of customers based on the current duty cycles of machines and compare among themselves by creating a few benchmarks which can further help in calculating the right potential for that low-buying customer in comparison to the most buying customers in the same segment.

Geographic Location

Geographic segmentation remains relevant in the aftermarket industry, especially when local conditions, climate, and environmental factors impact equipment wear. Customers in different regions may have varying needs for maintenance and replacement parts. For instance, HVAC companies may segment customers based on regional climate differences.

Maintenance and Service History

Segmenting based on maintenance and service history allows businesses to identify customers who have consistently engaged with their aftermarket services versus those who have had occasional interactions. This can influence service contract offerings and customer engagement strategies.

Purchase History

Analyzing a customer’s purchase history of replacement parts and aftermarket services can provide insights into their buying behavior. This information can be used to create segments like loyal customers, occasional purchasers, or those who have not engaged with aftermarket offerings.

Data-Driven Approach to Identifying Segmentation Criteria for Customer Segmentation in the Aftermarket Industry

To effectively identify segmentation criteria in the aftermarket industry, a data-driven approach is essential

  1. Data Collection and Integration

    Gather data from various sources within your organization, such as sales records, customer databases, maintenance logs, and equipment databases. Ensure data accuracy and completeness.

  2. Exploratory Data Analysis (EDA)

    Conduct EDA to understand patterns and trends within the installed base data. EDA can help identify potential segmentation criteria.

  3. Statistical Techniques

    Utilize statistical techniques like cluster analysis, regression analysis, or machine learning algorithms to uncover meaningful customer segments. These methods can identify hidden patterns and relationships within the data.

  4. Validation

    Validate the identified criteria by assessing their relevance and potential for actionable insights. Ensure that each criterion results in distinct and meaningful customer segments.

  5. Continuous Monitoring and Adaptation

    Aftermarket customer segmentation is an ongoing process. As customer needs evolve and equipment conditions change, regularly revisit your segmentation criteria and adjust them as needed.

Identifying segmentation criteria is important in creating effective customer segments based on installed base data in the aftermarket industry. By carefully selecting criteria that align with your business goals and customer base, you can develop strategies that cater to the unique needs of each segment. This, in turn, can lead to improved customer satisfaction and increased sales of aftermarket products and services. Remember that customer segmentation in the aftermarket is not static, it should evolve alongside your business and customer base to remain effective over time. This article was crafted and published on LinkedIn by Sahil Monga.

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