Customer Segmentation
Customer segmentation is the division of a customer base into groups (segments) that are as homogeneous as possible, sharing similar characteristics, needs or value to the company. The goal is to align sales, marketing and service to each segment in a targeted rather than uniform way.
Customer segmentation is the systematic division of a customer base into clearly delineated groups that are as internally homogeneous as possible – the segments. Customers within a segment resemble one another in selected characteristics (such as revenue, industry, region, buying behavior or needs), while the segments differ markedly from each other. The goal is to address each segment in a targeted and economically sensible way, rather than treating all customers alike. This lets sales resources, marketing budgets, terms and service levels be deployed where they yield the greatest return.
Segmentation is both an analytical and a steering instrument. Analytically, it reveals which customer groups carry the revenue and the contribution margin, where growth lies and which customers cost more than they bring in. As a steering instrument, it provides the basis for differentiated servicing models: A-customers receive personal support from the field sales team, while smaller customers are served via self-service or standardized campaigns. Segmentation is thus the bridge between mere customer data maintenance and value-oriented market cultivation.
At a glance
- Division of the customer base into homogeneous groups with similar characteristics
- Criteria include revenue/value, region, industry, buying behavior, needs
- Goal: differentiated rather than uniform engagement in sales, marketing, service
- Classics: ABC analysis by customer value, RFM analysis by buying behavior
- Operationally usable in the ERP via customer attributes, price lists and reports
How customer segmentation works
It starts with choosing the segmentation criteria. This depends on which decisions the company wants to make – value-based criteria suit servicing intensity, while behavior- or needs-oriented characteristics suit marketing campaigns. Customers are then assigned to segments based on existing data, usually with clear thresholds (such as annual revenue above a limit) or with scoring models. The segments must meet three requirements: they should be internally similar, clearly distinguishable from one another, and large enough to justify their own handling.
For segmentation to hold up, it must work with reliable data and be updated regularly. Customer value and buying behavior change; an assignment set once will grow stale. In practice, segments are therefore recalculated periodically or – with a good data foundation – updated automatically in the system. The prerequisite is a clean, duplicate-free customer base, since duplicate or incomplete records distort every analysis.
Segmentation criteria at a glance
Four groups of criteria are common. Demographic or firmographic characteristics describe who the customer is: for private customers age, gender or region, for business customers industry, company size or legal form. Geographic criteria break down by country, sales territory or postal code. Behavioral criteria rely on actual conduct – purchase frequency, basket size, channels used, return rate. Psychographic or needs-based criteria, finally, concern motives, price sensitivity or service expectations. In practice, several criteria are combined.
ABC and RFM analysis as standard methods
Two methods dominate in trade. ABC analysis divides customers by their value contribution into A- (few, high-revenue), B- and C-customers – the basis for tiered servicing and terms. RFM analysis (Recency, Frequency, Monetary) rates customers by how recent their last purchase was, their purchase frequency and their revenue, and is particularly suited to e-commerce and CRM campaigns, for example to identify customers who can be reactivated or are at risk of churning.
Why customer segmentation matters
Resources are limited, but customers are unequally valuable: in many companies a small share of customers generates the bulk of the contribution margin, while numerous small customers cause high servicing effort. Without segmentation, both groups receive the same attention – valuable customers are underserved, unprofitable ones overserved. Segmentation corrects this misallocation by aligning servicing intensity, discounts and channels with customer value.
The benefit shows across the entire market cultivation. Sales prioritizes appointments and follow-ups by segment; marketing targets campaigns precisely at the right groups and reduces wastage; purchasing and assortment planning recognize which target groups carry which products. Pricing and terms policy also becomes transparent when discount tiers and price lists are tied to segments. Overall, profitability and customer loyalty rise because offers become more relevant.
Customer segmentation in the ERP system
An ERP or merchandise management system supplies the data foundation and the operational levers for segmentation. The relevant raw data – revenues, order history, payment behavior, regions, industries – arises anyway in day-to-day business and is available in the customer master or in the transaction data. Via customer groups, attribute fields or tags, each customer can be assigned to one or more segments without having to offload data into a separate table.
The decisive advantage of segmentation in the ERP is its direct effectiveness: a segment is not merely a reporting filter but steers real processes. Customer groups carry segment-specific price lists and discount tiers, shipping and payment terms or approval limits. Reports and dashboards show revenue and contribution margin per segment, and exports for marketing or a connected CRM can be filtered by segment. Where the ERP includes a CRM module, sales control and segmentation mesh seamlessly.
Static assignment vs. dynamic segments
A distinction is made between fixed and rule-based segments. With static assignment, a customer is manually assigned to a group and stays there until someone changes the assignment – simple, but maintenance-intensive and quickly outdated. Dynamic segments, by contrast, define a rule (e.g. "annual revenue > €50,000 and at least 4 orders") by which the system keeps membership continuously up to date. Dynamic segments are more precise and low-maintenance, but require well-maintained, current data and sufficient reporting functions.
Distinction: customer segmentation vs. target group and customer base
Customer segmentation, target group and customer base are often confused, yet denote different things. The customer base is the pure data foundation of all existing customers; segmentation is the analytical structure that orders this pool into groups. No reliable segmentation without a well-maintained customer base – segmentation refines the existing data but does not replace it.
The target group, in turn, is usually future- and market-oriented: it describes ideal-typical, often yet-to-be-won customers for a product or campaign and also encompasses prospects outside one's own pool. Segmentation, by contrast, typically refers to real existing customers with an available history. Related is ABC analysis, which as a concrete method produces a value-based segmentation – it is a tool of segmentation, not its opposite.
Practice and DACH specifics
For the German-speaking region, two points are especially relevant. First, data protection: segmentation attributes about natural persons are personal data and are subject to the GDPR. Profiling in particular and behavior-based segments for marketing purposes require a legal basis, purpose limitation and – for electronic advertising – consent under the UWG (Act Against Unfair Competition). Business customer data is less sensitive, yet the same framework applies to contact persons.
Second, data quality as a success factor: segmentation is only as good as the underlying data set. Duplicates, outdated revenues or missing industry information lead to wrong assignments and thus to poor decisions on terms and servicing. A regularly maintained, duplicate-free customer base and clearly documented segment rules are therefore prerequisites for segmentation to be trusted in daily operations and actually used for steering.
Example
Example: segmentation at a B2B wholesaler
A wholesaler of electrical installation materials served around 2,000 commercial customers with a uniform field sales and discount model. An analysis in the ERP showed that about 15 percent of customers generated over 70 percent of the contribution margin, while a large share of small customers with frequent small orders and high servicing effort was barely profitable.
Based on an ABC analysis by contribution margin, the company set up three segments and stored them as customer groups in the merchandise management system. A-customers receive dedicated contacts in field sales and individual terms; B-customers are served via inside sales and targeted campaigns; C-customers were redirected to an online shop with a standard price list and minimum order value. Because the segments take effect directly in the ERP via price lists and discount tiers, the rules apply automatically at every order entry. Result: field sales concentrates on high-value customers, servicing costs for small customers fell markedly, and the contribution margin rose without additional sales staff.
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