Customer Segmentation: A Smarter Supply Chain Strategy to Streamline Operations & Boost Profits

June 5, 2024 · 14 minutes
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Here’s a simple yet illustrative example:

Sara’s Sweets is a fictional bakery that collaborates with local cafes and also handles custom online orders directly from consumers. 

Online customers frequently demand highly customized products such as tailor-made cakes, detailing every aspect of their order. These requests are irregular but tend to spike during special occasions like weddings and the holiday season. 

On the flip side, cafes place consistent, daily orders for standard baked goods.

Now, imagine if Sara’s applied the same supply chain strategy to both of these types of customers and channels.

As you might expect, it would lead to numerous inefficiencies, jeopardize profits, and in a worst-case scenario, could even result in the business shutting down due to a completely collapsed supply chain.

The need for customer segmentation in Sara’s situation is clear, but what about your business? 

Are you effectively segmenting your customer demand to ensure the highest satisfaction and maximize profits? 

With a variety of SKUs, locations, and customer types, do you have the capability to uncover these insights and respond in a timely manner?

If your answer to one or both of the above is a no, this blog is for you. 

You’ll learn:

  • What customer segmentation in supply chain is
  • How to develop a customer demand segmentation strategy
  • Examples of successful customer demand segmentation
  • Insights into how ThroughPut AI can help you with customer segmentation

What is Customer Segmentation?

Gartner defines Supply Chain Segmentation as: “Designing and operating distinctly different end-to-end value chains (from customers to suppliers) optimized by a combination of unique customer value, product attribute, manufacturing and supply capabilities, and business value considerations. 

In essence, supply chain segmentation is the dynamic alignment of customer channel demands and supply response capabilities optimized for net profitability across each segment.

Customer segmentation, a form of supply chain segmentation, refers to the process of dividing customers into groups based on specific criteria such as demand patterns, service needs, product preferences, geographical locations, and profitability. This strategic approach allows businesses to tailor their supply chain operations, such as production, inventory management, and distribution strategies, to meet the distinct needs and expectations of different customer segments more effectively.

What Are the Benefits of Customer Segmentation in Supply Chain?

Benefits of Customer Segmentation in Supply Chain

Customer segmentation offers numerous benefits, including the ability to prioritize profitable customers and products, optimize inventory management, and more. 

Here’s a detailed exploration of these advantages:

Prioritizing Profitable Customers and Products

Customer segmentation allows businesses to perform detailed analyses of demand to identify their most profitable customers and high-performing products. 

This enables prioritization of these customer groups and products, while also assessing the costs associated with meeting these demands. 

By focusing on customer satisfaction and product availability, companies can optimize revenue and efficiency, ensuring cost-effective operations. This targeted approach helps businesses allocate resources optimally and strategically, driving overall profitability and operational success.

Enhancing Resilience in Operations

Intelligent customer segmentation helps uncover relevant purchasing trends across various demographics, allowing businesses to develop stronger, more resilient marketing strategies based on real-time data tailored to specific customer groups. 

This targeted marketing approach enhances customer engagement and loyalty, ultimately boosting sales. 

It also enables businesses to understand customer behaviors and preferences to offer personalized experiences, increasing their competitiveness in the market.

Optimizing Inventory Management

Effective customer segmentation addresses two major business challenges: stock-outs and excess inventory. 

This method enables businesses to maintain accurate stock levels, freeing up working capital to speed up operations. Improved accuracy in stock levels reduces costs associated with overstocking or understocking and enhances customer satisfaction by consistently meeting demand. 

Optimized inventory management results in smoother operations and improved financial performance.

Leveraging Comprehensive Demand Views

Customer segmentation allows businesses to utilize detailed demand views across various variables. By accessing cross-sectional summary views, including Throughput, Lost Sales, OTIF (On-Time In-Full), and demand trends, decision-makers can gain a comprehensive understanding of their supply chain performance. 

These insights aid in making informed decisions and enhance strategic planning, ensuring efficient supply chain operations that effectively meet customer needs.

Types of Supply Chain Segmentation [& Why Choose Customer Segmentation]

Supply chain segmentation can significantly enhance the efficiency and responsiveness of businesses by tailoring operations to the specific needs of different market segments. 

Understanding the various types of supply chain segmentation is crucial for implementing the most effective strategy for your business. 

Here’s a breakdown of the different types and when to use them:

1. Product-based Segmentation

Product-based segmentation is used when a company offers products that differ significantly in terms of size, perishability, or value. 

This method helps in optimizing the manufacturing, storage, and distribution processes according to the specific requirements of each product category. 

It’s particularly useful for companies with extensive product lines that require different handling and shipping conditions.

Key aspects to consider in product segmentation are:

  • The number of products or SKUs
  • Pricing of these SKUs
  • High-margin versus low-margin products
  • High-volume versus low-volume products
  • Fast-moving versus slow-moving products
  • Lifecycle, like perishable versus non-perishable products
  • Low-quality versus high-quality products
2. Channel-based Segmentation

This type focuses on distinguishing supply chain operations based on the sales channel, such as online, retail, or wholesale. 

It’s best suited for businesses that sell through multiple platforms and need to optimize inventory and logistics differently for each channel to meet distinct channel demands efficiently.

While segmenting your supply chain based on the channels your business uses, remember to keep these points in mind:

  • Lead time requirements 
  • Direct–to-consumer versus business-to-business channels
  • Offline versus online sales
  • Multi-sources versus single-source channels
  • Your own distribution network versus third-party networks
3. Geographic Segmentation

Businesses operating in multiple geographic regions may use this segmentation to cater to regional differences in demand and supply chain capabilities. 

It allows for localization of supply chain activities to reduce transportation costs, improve delivery times, and comply with local regulations.

Considerations for geographic segmentation include 

  • Understanding local regulatory requirements
  • Regional demand variations
  • Transportation and logistics considerations
4. Service Level-based Segmentation

This segmentation is ideal for companies that offer different levels of service or delivery options to their customers. 

This segmentation helps in aligning supply chain resources, such as expedited shipping or premium handling, to meet varying service expectations.

The differentiation is done based on: 

  • Premium service vs. standard service
  • Same-day delivery vs. standard delivery
  • Customization requirements
5. Industry-based Segmentation

Industry-based segmentation is useful for companies that serve multiple industries with distinct regulatory requirements and operational needs. 

By segmenting the supply chain by industry, businesses can ensure compliance and optimize their operations for each industry’s specific challenges.

6. **Our Recommendation: Customer Segmentation

Customer demand-based segmentation focuses on aligning the supply chain with customers’ demand or purchase patterns. 

It is particularly valuable in the current times as companies experience fluctuating demand, enabling them to adjust production and inventory levels dynamically to prevent overstocking or stockouts.

Customer-based segmentation enables companies to allocate resources more efficiently by prioritizing high-demand products, profitable customer segments, and regions with strong sales potential. 

It also allows companies to adapt quickly to changing market conditions and customer preferences. By continuously monitoring demand trends and adjusting supply chain strategies accordingly, companies can stay agile and responsive in volatile or competitive markets.

You need to consider the following for segmentation:

  • The frequency and volume of purchases
  • High-value customers versus low-value customers
  • Regional differences
  • Big highly profitable customer groups versus small not-so-profitable customer groups

How to Implement a Customer Segmentation Strategy in Your Supply Chain?

You can follow the series of steps below for the implementation of customer segmentation.

1. Analyze Your Customer Base

Analyze historical and current sales data to differentiate customer segments based on multiple variables including volume and frequency of purchase, the margin of products purchased, lifecycle of the product, etc. 

We’d suggest using advanced algorithms to maintain real-time insights, ensuring that segmentation remains responsive to evolving market dynamics.

2. Segment Your Supply Chain

Once the customer analysis is completed, the next step is to segment your supply chain effectively. 

You can employ advanced analytics techniques such as clustering algorithms or machine learning models to group customers with similar characteristics together. 

By doing this, you can better tailor your supply chain strategies to meet the specific needs and preferences of each segment.

3. Develop Tailored Supply Chain Strategies

The next step is to customize your supply chain strategies by addressing the unique requirements of different customer segments. 

It may include streamlining the customer mix by prioritizing high-value customers and simplifying service for low-value or unprofitable ones. 

Additionally, consider implementing incentives like discounts or exclusive access to help reward loyal and high-value customers.

4. Monitor and Refine

Measuring outcomes against predefined key performance indicators (KPIs) enables businesses to evaluate the effectiveness of the segmentation strategy. 

Continuous monitoring of performance metrics like impact on profitability, reduction in wastage, better inventory control, etc. can help identify areas for improvement allowing for refinement of segmentation strategies to better align with evolving customer needs and market conditions.

Customer Segmentation Examples

Some of the top companies in the world today use customer segmentation strategies to optimize their business operations and drive better sales and profitability. 

Here are some examples.


The world’s largest e-commerce company uses a lean supply chain segmentation strategy for its high-volume, low-variety products like books, household items, electronic items, etc. 

The company uses its own and third-party automated warehouse to optimize inventory levels and drive an efficient distribution network. Rapid fulfillment is a strategy that Amazon introduced to the world, which has helped many e-commerce businesses focus on cost efficiency. 

Thanks to these strategies, the company can fulfill customer orders faster and minimize operational costs.


This is a typical case of an agile supply chain approach for Zara’s low-volume high-variety products. 

The fashion retailer has dedicated resources to focus on fast fashion. 

Thereby, the company can respond to changing fashion trends very quickly. 

Its strategy is to produce limited quantities but in a wider variety of styles. 

Zara has a flexible manufacturing system in place while at the ground level, its team works closely with designers to incorporate changes in demand. 

Its agile approach helps in the rapid restocking of stores while cutting down on overproduction. In this way, it can meet the fluctuating customer demands with the right type of products.


The company follows a hybrid supply chain segmentation strategy for its seasonal products like back-to-school supplies or festive decorations. During peak season, the company uses an agile methodology to meet customer demands and ramp up production and distribution, while during the off-season, it goes slow with a lean strategy. 

This helps the company maintain cost efficiency, control costs and be responsive to seasonal demand fluctuations.

ThroughPut AI for Customer Segmentation in the Supply Chain

Customer segmentation for enterprises and multi-scale businesses with a large number of products, locations and networks is not possible manually.

That’s where tools like ThroughPut AI with its multi-dimensional customer demand segmentation capabilities come into play.

ThroughPut’s AI-powered customer segmentation capabilities offer a more sophisticated, real-time, and comprehensive approach to supply chain segmentation compared to traditional methods.

 By leveraging advanced technologies and patented algorithms, ThroughPut AI enables businesses to gain deeper insights into customer behaviors, optimize their supply chain operations in real-time, and drive greater profitability and efficiency.

Let’s take a look into the key distinctions of ThroughPut AI’s capabilities in comparison to traditional segmentation techniques.

Key Distinctions of ThroughPut’s AI-Powered Customer Segmentation

1. Multidimensional Analysis vs. Single Variable Segmentation

Traditional segmentation methods often rely on a single variable such as sales volume or annual revenue to categorize customers.

This approach can be overly simplistic and may not capture the full complexity of customer behaviors and needs.

In contrast, ThroughPut’s AI-powered customer segmentation incorporates multiple dimensions of customer data including transactional data, behavioral patterns, and external market factors.

This allows for a more nuanced and comprehensive understanding of your customer segments.

2. Real-Time Data Integration vs. Periodic Updates

Traditional segmentation is typically performed on an annual or semi-annual basis which can result in outdated insights that fail to reflect current market conditions.

ThroughPut’s platform integrates with your real-time data from various sources, ensuring that segmentation is based on the most current information. This will enable you to respond more quickly to changes in customer behavior and market dynamics.

3. Predictive Analytics vs. Historical Analysis

While traditional methods often rely on historical data to inform customer segmentation, ThroughPut’s AI uses predictive analytics to forecast future customer behaviors and market trends.

This forward-looking approach will help anticipate changes in demand and adjust your supply chain operations proactively, reducing the risk of stockouts or overstocking.

4. Automated Insights and Recommendations vs. Manual Analysis

Traditional segmentation methods often require significant manual effort to analyze data and derive insights.

ThroughPut’s AI-driven platform automates this process, providing you with actionable insights and recommendations for optimizing your supply chain operations. This includes suggestions for inventory management, production planning, and logistics optimization, tailored to the specific needs of each customer segment.

5. Dynamic Order Prioritization vs. Static Segmentation

ThroughPut’s platform allows for dynamic order prioritization based on real-time data and multidimensional customer analysis.

You can see all your customers in a single, centralized location, broken down by service or commodity, and identify orders and customers that need to be prioritized.

This dynamic approach contrasts with the static nature of traditional segmentation, which may not account for shifts in customer behavior over time.

6. Holistic Customer Relationship Management vs. Isolated Metrics

Traditional customer segmentation methods may focus on isolated metrics such as sales volume or frequency of purchase without considering the broader context of customer relationships.

ThroughPut’s platform provides a holistic view of your customer relationships, highlighting segment shifts over time and connecting a customer’s current segment to their segment a quarter or a year prior.

This helps you to visualize whether a customer relationship is growing, stagnating, or declining, and identify new opportunities for growth.

7. Enhanced Customer Engagement and Supplier Alignment

ThroughPut emphasizes the importance of proactive engagement with your customers and alignment with suppliers.

This continuous engagement ensures that segmentation strategies remain effective and responsive to changing customer requirements. Traditional methods may not place as much emphasis on this ongoing collaboration, potentially leading to misalignment and missed opportunities.

Steps to Implement ThroughPut AI’s Capabilities for Customer Segmentation 

Step 1: Predict and resolve suboptimal forecasting

First and foremost, do away with traditional forecasting challenges by moving away from pure dependency on legacy systems & apply complete and accurate datasets to forecast demand.

Step 2: Analyze inventory accurately with relevant ABC/XYZ Segmentation

Easily plan volume/revenue per customer across your product mix with accurate customer demand-based segmentation according to industry and service line.

Step 3: Deploy targeted segmentation options based on relevant business characteristics

Easily understand, apply and act according to the sales channel, customer size or vertical, revenue source and deal size. 

Step 4: Simplify customer mix with cross-selling

Unlock opportunities to simplify customer mix to differentiate top performers and encourage customers to increase business and cut down on variance and waste. Use relevant What-if forecasts and prediction analysis to offer new rates, discounts and quotations.

Additional Features of ThroughPut AI’s Customer Segmentation Capabilities

Analyze Customer Segments – and their Growth

The ThroughPut AI platform illuminates shifts in customer segments over time, linking a customer’s current segment with their segment from a quarter and a year ago. It also highlights top customers in terms of sales. This enables businesses to:

  • Visualize whether customer relationships are growing, stagnating, or declining.
  • Identify fresh growth opportunities by understanding evolving customer dynamics.
Dynamic Order Prioritization to Accelerate Time to Value

With all customer data centralized and categorized by service or commodity, businesses can:

  • Identify orders and customers needing prioritization for efficient fulfillment.
  • Rank and segment customers using 360° scorecards, considering KPIs like order frequency, total sales volume, and purchase frequency.
  • Group customers into tiers and create customized promotions to encourage movement into higher tiers.
Maximize Customer Lifetime Value

The ThroughPut AI platform provides detailed insight into the values and timelines of each customer relationship, showcasing:

  • Multi-dimensional segmentation by demand, sales, and contribution margin.
  • Distribution by commodity, service, and location.
  • On-Time-In-Full (OTIF) delivery performance.
ThroughPut for Demand Segmentation

Case Study of Customer Segmentation in Supply Chain

In response to the challenges posed by the Coronavirus pandemic, ThroughPut AI collaborated with a European Retail Giant to transform their operations through customer demand segmentation, resulting in substantial annual savings of $20 million.

Challenge: With a specific emphasis on food warehouses, the client aimed to gain deeper insights into their supply chain dynamics and enhance the efficiency of fulfillment and shipping practices. 

The primary objective was to segment customer demand intricately and optimize replenishment and allocation strategies for individual SKUs.

Solution: ThroughPut AI was deployed to conduct a comprehensive analysis of customer demand. By leveraging advanced algorithms, the software identified and segmented demand patterns across various product categories and geographic regions. 

This enabled the client to tailor their replenishment and allocation strategies to meet the unique needs of different customer segments.

Competitive gains

  • Over 600x faster insights for improved supplier and demand lead times, defect rates and cycle times
  • Reduced lead time by over 30%

The impact

  • Up to 10% reduction in trucking costs
  • Up to 2X improvement inventory turns
  • Up to 1% increase in top-line revenue
  • Optimized 100,000 SKUs + years of siloed systems

How to Get Started: The ThroughPut Way

ThroughPut AI makes it easy to get started on customer segmentation in supply chain.

You can follow this three-step process for getting the right buy-in for this investment:

  • Find an executive sponsor, board member, or C-suite executive (operations and finance background preferred) who understands the importance of customer segmentation for the supply chain and the business
  • Start with a pilot first. Pick a distribution center or production line to provide material flow-related data.
  • No initial IT support required. Work with existing data and infrastructure to see initial ROI in less than 90 days.
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Anita Raj
Product Marketing Specialist