Market segmentation is the process of dividing a broad consumer or business market, normally consisting of existing and potential customers, into sub-groups of consumers (known as segments) based on some type of shared characteristics. In dividing or segmenting markets, researchers typically look for shared characteristics such as common needs, common interests, similar lifestyles or even similar demographic profiles. The overall aim of segmentation is to identify high yield segments – that is, those segments that are likely to be the most profitable or that have growth potential – so that these can be selected for special attention (i.e. become target markets).
Many different ways to segment a market have been identified. Business-to-business (B2B) sellers might segment the market into different types of businesses or countries. While business to consumer (B2C) sellers might segment the market into demographic segments, lifestyle segments, behavioral segments or any other meaningful segment.
Market segmentation assumes that different market segments require different marketing programs – that is, different offers, prices, promotion, distribution or some combination of marketing variables. Market segmentation is not only designed to identify the most profitable segments, but also to develop profiles of key segments in order to better understand their needs and purchase motivations. Insights from segmentation analysis are subsequently used to support marketing strategy development and planning. Many marketers use the S-T-P approach; Segmentation→ Targeting → Positioning to provide the framework for marketing planning objectives. That is, a market is segmented, one or more segments are selected for targeting, and products or services are positioned in a way that resonates with the selected target market or markets.
- 1 History
- 2 Criticisms of market segmentation
- 3 Market segmentation strategy
- 4 Segmentation, targeting, positioning
- 5 Identifying the market to be segmented
- 6 Bases for segmenting consumer markets
- 7 Selecting target markets
- 8 Developing the marketing program and positioning strategy
- 9 Bases for segmenting business markets
- 10 Use in customer retention
- 11 Segmentation: algorithms and approaches
- 12 Companies
- 13 See also
- 14 References
- Fragmentation (pre 1880s): The economy was characterised by small regional suppliers who sold goods on a local or regional basis
- Unification or Mass Marketing (1880s–1920s): As transportation systems improved, the economy became unified. Standardised, branded goods were distributed at a national level. Manufacturers tended to insist on strict standardisation in order to achieve scale economies with a view to penetrating markets in the early stages of a product's life cycle. e.g. the Model T Ford
- Segmentation (1920s–1980s): As market size increased, manufacturers were able to produce different models pitched at different quality points to meet the needs of various demographic and psychographic market segments. This is the era of market differentiation based on demographic, socio-economic and lifestyle factors.
- Hyper-segmentation (1980s+): a shift towards the definition of ever more narrow market segments. Technological advancements, especially in the area of digital communications, allow marketers to communicate with individual consumers or very small groups. This is sometimes known as one-to-one marketing.
Wendell R. Smith is generally credited with being the first to introduce the concept of market segmentation into the marketing literature in 1956 with the publication of his article, "Product Differentiation and Market Segmentation as Alternative Marketing Strategies."  Smith's article makes it clear that he had observed "many examples of segmentation" emerging and to a certain extent saw this as a natural force in the market that would "not be denied."  As Schwarzkopf points out, Smith was codifying implicit knowledge that had been used in advertising and brand management since the 1920s.
Contemporary market segmentation emerged in the twentieth century as marketers responded to two pressing issues. Demographic and purchasing data were available for groups but rarely for individuals and secondly, advertising and distribution channels were available for groups, but rarely for single consumers. Between 1902 and 1910, George B Waldron, working at Mahin's Advertising Agency in the United States used tax registers, city directories and census data to show advertisers the proportion of educated vs illiterate consumers and the earning capacity of different occupations etc. in a very early example of simple market segmentation. In 1924 Paul Cherington developed the 'ABCD' household typology; the first socio-demographic segmentation tool. With access to group level data only, brand marketers approached the task from a tactical viewpoint. Thus, segmentation was essentially a brand-driven process.
Until relatively recently, most segmentation approaches have retained this tactical perspective in that they address immediate short-term decisions; such as describing the current “market served” and are concerned with informing marketing mix decisions. However, with the advent of digital communications and mass data storage, it has been possible for marketers to conceive of segmenting at the level of the individual consumer. Extensive data is now available to support segmentation at very narrow groups or even for the single customer, allowing marketers to devise a customised offer with an individual price which can be disseminated via real-time communications.
Criticisms of market segmentation
The limitations of conventional segmentation have been well documented in the literature. Perennial criticisms include:
- that it is no better than mass marketing at building brands 
- that in competitive markets, segments rarely exhibit major differences in the way they use brands 
- that it fails to identify sufficiently narrow clusters 
- geographic/demographic segmentation is overly descriptive and lacks sufficient insights into the motivations necessary to drive communications strategy 
- difficulties with market dynamics, notably the instability of segments over time  and structural change which leads to segment creep and membership migration as individuals move from one segment to another 
Market segmentation has many critics. But in spite of its limitations, market segmentation remains one of the enduring concepts in marketing and continues to be widely used in practice. One American study, for example, suggested that almost 60 percent of senior executives had used market segmentation in the past two years.
Market segmentation strategy
A key consideration for marketers is whether to segment or not to segment. Depending on company philosophy, resources, product type or market characteristics, a businesses may develop an undifferentiated approach or differentiated approach. In an undifferentiated approach, the marketer ignores segmentation and develops a product that meets the needs of the largest number of buyers. In a differentiated approach the firm targets one or more market segments, and develops separate offers for each segment.
In consumer marketing, it is difficult to find examples of undifferentiated approaches. Even goods such as salt and sugar, which were once treated as commodities, are now highly differentiated. Consumers can purchase a variety of salt products; cooking salt, table salt, sea-salt, rock salt, kosher salt, mineral salt, herbal or vegetable salts, iodized salt, salt substitutes and many more.
|Number of segments||Segmentation strategy||Comments|
|Zero||Undifferentiated strategy||Mass marketing: no segmentation|
|One||Focus strategy||Niche marketing: focus efforts on a small, tightly defined target market|
|Two or more||Differentiated strategy||Multiple niches: focus efforts on 2 or more, tightly defined targets|
|Thousands||Hypersegmentation||One-to-one marketing: customise the offer for each individual customer|
A number of factors are likely to affect a company's segmentation strategy:
- Company resources: When resources are restricted, a concentrated strategy may be more effective.
- Product variability: For highly uniform products (such as sugar or steel) an undifferentiated marketing may be more appropriate. For products that can be differentiated, (such as cars) then either a differentiated or concentrated approach is indicated.
- Product life cycle: For new products, one version may be used at the launch stage, but this may be expanded to a more segmented approach over time. As more competitors enter the market, it may be necessary to differentiate.
- Market characteristics: When all buyers have similar tastes, or are unwilling to pay a premium for different quality, then undifferentiated marketing is indicated.
- Competitive activity: When competitors apply differentiated or concentrated market segmentation, using undifferentiated marketing may prove to be fatal. A company should consider whether it can use a different market segmentation approach.
Segmentation, targeting, positioning
The process of segmenting the market is deceptively simple. Seven basic steps describe the entire process including segmentation, targeting and positioning. In practice, however, the task can be very laborious since it involves poring over loads of data, and requires a great deal of skill in analysis, interpretation and some judgement. Although a great deal of analysis needs to be undertaken, and many decisions need to be made, marketers tend to use the so-called S-T-P process, that is Segmentation→ Targeting → Positioning, as a broad framework for simplifying the process. Segmentation comprises identifying the market to be segmented; identification, selection, and application of bases to be used in that segmentation; and development of profiles. Targeting comprises an evaluation of each segment's attractiveness and selection of the segments to be targeted. Positioning comprises identification of optimal position and development of the marketing program.
Identifying the market to be segmented
The market for a given product or service known as the market potential or the total addressable market (TAM). Given that this is the market to be segmented, the market analyst should begin by identifying the size of the potential market. For existing products and services, estimating the size and value of the market potential is relatively straight forward. However, estimating the market potential can be very challenging when a product or service is totally new to the market and no historical data on which to base forecasts exists.
A basic approach is to first assess the size of the broad population, then estimate the percentage likely to use the product or service and finally to estimate the revenue potential.
Another approach is to use historical analogy. For example, the manufacturer of HDTV might assume that the number of consumers willing to adopt high definition TV will be similar to the adoption rate for Color TV. To support this type of analysis, data for household penetration of TV, Radio, PCs and other communications technologies is readily available from government statistics departments. Finding useful analogies can be challenging because every market is unique. However, analogous product adoption and growth rates can provide the analyst with benchmark estimates, and can be used to cross validate other methods that might be used to forecast sales or market size.
N(t) – N(t−1) = [p + qN(t−1)/m] x [m – N(t−1)]
- N(t)= the number of adopters in the current time period, (t)
- N(t−1)= the number of adopters in the previous time period, (t-1)
- p = the coefficient of innovation
- q = the coefficient of imitation (the social contagion influence)
- m = an estimate of the number of eventual adopters
The major challenge with the Bass model is estimating the parameters for p and q. However, the Bass model has been so widely used in empirical studies that the values of p and q for more than 50 consumer and industrial categories have been determined and are widely published in tables. The average value for p is 0.037 and for q is 0.327.
Bases for segmenting consumer markets
A major step in the segmentation process is the selection of a suitable base. In this step, marketers are looking for a means of achieving internal homogeneity (similarity within the segments), and external heterogeneity (differences between segments). In other words, they are searching for a process that minimises differences between members of a segment and maximises differences between each segment. In addition, the segmentation approach must yield segments that are meaningful for the specific marketing problem or situation. For example, a person's hair colour may be a relevant base for a shampoo manufacturer, but it would not be relevant for a seller of financial services. Selecting the right base requires a good deal of thought and a basic understanding of the market to be segmented.
In reality, marketers can segment the market using any base or variable provided that it is identifiable, measurable, actionable and stable. For example, some fashion houses have segmented the market using women's dress size as a variable. However, the most common bases for segmenting consumer markets include: geographics, demographics, psychographics and behavior. Marketers normally select a single base for the segmentation analysis, although, some bases can be combined into a single segmentation with care. For example, geographics and demographics are often combined, but other bases are rarely combined. Given that psychographics includes demographic variables such as age, gender and income as well as attitudinal and behavioral variables, it makes little logical sense to combine psychographics with demographics or other bases. Any attempt to use combined bases needs careful consideration and a logical foundation.
|Segmentation base||Brief explanation of base (and example)||Typical segments|
|Demographic||Quantifiable population characteristics. (e.g. age, gender, income, education, socio-economic status, family size or situation).||e.g. Young, Upwardly-mobile, Prosperous, Professionals (YUPPY); Double Income No Kids (DINKS); Greying, Leisured And Moneyed (GLAMS); Empty- nester, Full-nester|
|Geographic||Physical location or region (e.g. country, state, region, city, suburb, postcode).||e.g. New Yorkers; Remote, outback Australians; Urbanites, Inner-city dwellers|
|Geo-demographic or geoclusters||Combination of geographic & demographic variables.||e.g. Rural farmers, Urban professionals, 'sea-changers', 'tree-changers'|
|Psychographics||Lifestyle, social or personality characteristics. (typically includes basic demographic descriptors)||e.g. Socially Aware; Traditionalists, Conservatives, Active 'club-going' young professionals|
|Behavioural||Purchasing, consumption or usage behaviour. (e.g. Needs-based, benefit-sought, usage occasion, purchase frequency, customer loyalty, buyer readiness).||e.g. Tech-savvy (aka tech-heads); Heavy users, Enthusiasts; Early adopters, Opinion Leaders, Luxury-seekers, Price-conscious, Quality-conscious, Time-poor|
Source: Based on Wikiversity, Marketing [E-Book], c. 2015
The following sections provide a detailed description of the most common forms of consumer market segmentation.
Geographic segmentation divides markets according to geographic criteria. In practice, markets can be segmented as broadly as continents and as narrowly as neighborhoods or postal codes. Typical geographic variables include:
- Country e.g. USA, UK, China, Japan, South Korea, Malaysia, Singapore, Australia, New Zealand
- Region e.g. North, North-west, Mid-west, South, Central
- Population density: e.g. central business district (CBD), urban, suburban, rural, regional
- City or town size: e.g. under 1,000; 1,000–5,000; 5,000–10,000 ... 1,000,000–3,000,000 and over 3,000,000
- Climatic zone: e.g. Mediterranean, Temperate, Sub-Tropical, Tropical, Polar,
The geo-cluster approach (also called geodemographic segmentation) combines demographic data with geographic data to create richer, more detailed profiles. Geo-cluster approaches are a consumer classification system designed market segmentation and consumer profiling purposes. They classify residential regions or postcodes on the basis of census and lifestyle characteristics obtained from a wide range of sources. This allows the segmentation of a population into smaller groups defined by individual characteristics such as demographic, socio-economic or other shared socio-demographic characteristics.
Geographic segmentation may be considered the first step in international marketing, where marketers must decide whether to adapt their existing products and marketing programs for the unique needs of distinct geographic markets. Tourism Marketing Boards often segment international visitors based on their country of origin.
A number of proprietary geo-demographic packages are available for commercial use. Geographic segmentation is widely used in direct marketing campaigns to identify areas which are potential candidates for personal selling, letter-box distribution or direct mail. Geo-cluster segmentation is widely used by Governments and public sector departments such as urban planning, health authorities, police, criminal justice departments, telecommunications and public utility organisations such as water boards.
Segmentation according to demography is based on consumer- demographic variables such as age, income, family size, socio-economic status, etc. Demographic segmentation assumes that consumers with similar demographic profiles will exhibit similar purchasing patterns, motivations, interests and lifestyles and that these characteristics will translate into similar product/brand preferences. In practice, demographic segmentation can potentially employ any variable that is used by the nation's census collectors. Typical demographic variables and their descriptors are as follows:
- Age: e.g. Under 5, 5–8 years, 9–12 years, 13–17 years, 18–24, 25–29, 30–39, 40–49, 50–59, 60+
- Gender: Male, Female
- Occupation: Professional, self-employed, semi-professional, clerical/ admin, sales, trades, mining, primary producer, student, home duties, unemployed, retired
- Social class (or socio-economic status): A, B, C, D, E, or I, II, III, IV or V (normally divided into quintiles)
- Marital Status: Single, married, divorced, widowed
- Family Life-stage: Young single; Young married with no children; Young family with children under 5 years; Older married with children; Older married with no children living at home, Older living alone
- Family size/ number of dependants: 0, 1–2, 3–4, 5+
- Income: Under $10,000; 10,000–20,000; 20,001–30,000; 30,001–40,000, 40,001–50,000 etc.
- Educational attainment: Primary school; Some secondary, Completed secondary, Some university, Degree; Post graduate or higher degree
- Home ownership: Renting, Own home with mortgage, Home owned outright
- Ethnicity: Asian, African, Aboriginal, Polynesian, Melanesian, Latin-American, African-American, American Indian etc.
- Religion: Catholic, Protestant, Muslim, Jewish, Buddhist, Hindu, Other
In practice, most demographic segmentation utilises a combination of demographic variables.
The use of multiple segmentation variables normally requires analysis of databases using sophisticated statistical techniques such as cluster analysis or principal components analysis. It should be noted that these types of analysis require very large sample sizes. However, data-collection is expensive for individual firms. For this reason, many companies purchase data from commercial market research firms, many of whom develop proprietary software to interrogate the data.
The labels applied to some of the more popular demographic segments began to enter the popular lexicon in the 1980s. The following popular terms can be found in any good dictionary of popular language:
- DINKS: Double (or dual) Income, No Kids. describes one member of a couple with above average household income and no dependent children, tend to exhibit discretionary expenditure on luxury goods and entertainment and dining out
- GLAMs: Greying, Leisured and Moneyed. Retired older persons, asset rich and high income. Tend to exhibit higher spending on recreation, travel and entertainment
- GUPPY: (aka GUPPIE) Gay, Upwardly Mobile, Prosperous, Professional; blend of gay and YUPPY (can also refer to the London-based equivalent of YUPPY)
- MUPPY: (aka MUPPIE) Mid-aged, Upwardly Mobile, Prosperous, Professional
- PREPPY: (American) Well educated, well-off, upper class young persons; a graduate of an expensive school. Often distinguished by a style of dress.
- SITKOM: Single Income, Two Kids, Oppressive Mortgage. Tend to have very little discretionary income, struggle to make ends meet
- TWEEN: (contraction of in-between). Young person who is approaching puberty, aged approximately 9–12 years; too old to be considered a child, but too young to be a teenager.
- WASP: (American) White, Anglo-Saxon Protestant. Tend to be high-status and influential white Americans of English Protestant ancestry.
- YUPPY: (aka YUPPIE) Young, Urban/ Upwardly-mobile, Prosperous, Professional. Tend to be well-educated, career-minded, ambitious, affluent and free spenders.
Psychographic segmentation, which is sometimes called lifestyle segmentation, is measured by studying the activities, interests, and opinions (AIOs) of customers. It considers how people spend their leisure, and which external influences they are most responsive to and influenced by. Psychographics is a very widely used basis for segmentation, because it enables marketers to identify tightly defined market segments and better understand consumer motivations for product or brand choice.
While many of these proprietary psychographic segmentation analyses are well-known, the majority of studies based on psychographics are custom designed. That is, the segments are developed for individual products at a specific time. One common thread among psychographic segmentation studies is that they use quirky names to describe the segments.
Behavioral segmentation divides consumers into groups according to their observed behaviors. Many marketers believe that behavioral variables are superior to demographics and geographics for building market segments. Typical behavioral variables and their descriptors include:
- Purchase/Usage Occasion: e.g. regular occasion, special occasion, festive occasion, gift-giving
- Benefit-Sought: e.g. economy, quality, service level, convenience, access
- User Status: e.g. First-time user, Regular user, Non-user
- Usage Rate/ Purchase Frequency: e.g. Light user, heavy user, moderate user
- Loyalty Status: e.g. Loyal, switcher, non-loyal, lapsed
- Buyer Readiness: e.g. Unaware, aware, intention to buy
- Attitude to Product or Service: e.g. Enthusiast, Indifferent, Hostile; Price Conscious, Quality Conscious
- Adopter Status: e.g. Early adopter, late adopter, laggard
Note that these descriptors are merely commonly used examples. Marketers customize the variable and descriptors for both local conditions and for specific applications. For example, in the health industry, planners often segment broad markets according to 'health consciousness' and identify low, moderate and highly health conscious segments. This is an applied example of behavioral segmentation, using attitude to product or service as a key descriptor or variable which has been customised for the specific application.
Purchase/ usage occasion
Purchase or usage occasion segmentation focuses on analyzing occasions when consumers might purchase or consume a product. This approach customer-level and occasion-level segmentation models and provides an understanding of the individual customers’ needs, behavior and value under different occasions of usage and time. Unlike traditional segmentation models, this approach assigns more than one segment to each unique customer, depending on the current circumstances they are under.
Benefit sought (sometimes called needs-based segmentation) divides markets into distinct needs, perceived value, benefits sought or advantage that accrues from the purchase of a product or service. Marketers using benefit-sought segmentation might develop products with different quality levels, performance, customer service, special features or any other meaningful benefit and pitch different products at each of the segments identified. Benefit segmentation is one of the more commonly used approaches to segmentation and is widely used in many consumer markets including motor vehicles, fashion and clothing, furniture, consumer electronics and holiday-makers.
Loker and Purdue, for example, used benefit segmentation to segment the pleasure holiday travel market. The segments identified in this study were the naturalists, pure excitement seekers, escapists, 
Attitudinal segmentation provides insight into the mindset of customers, especially the attitudes and beliefs that drive consumer decision-making and behavior. An example of attitudinal segmentation comes from the UK's Department of Environment which segmented the British population into six segments, based on attitudes that drive behavior relating to environmental protection:
- Greens: Driven by the belief that protecting environment is critical; try to conserve whenever they can
- Conscious with a conscience: Aspire to be green; primarily concerned with wastage; lack awareness of other behaviors associated with broader environmental issues such as climate change
- Currently constrained: Aspire to be green but feel they cannot afford to purchase organic products; pragmatic realists
- Basic contributors: Sceptical about the need for behavior change; aspire to conform to social norms; lack awareness of social and environmental issues
- Long-term resistance: Have serious life priorities that take precedence before behavioral change is a consideration; their every day behaviors often have low impact on the environment but for other reasons than conservation
- Disinterested: View greenies as an eccentric minority; exhibit no interest in changing their behavior; may be aware of climate change but have not internalised it to the extent that it enters their decision-making process.
Other types of consumer segmentation
In addition to geographics, demographics, pyschographics and behavioral bases, marketers occasionally turn to other means of segmenting the market, or to develop segment profiles.
A generation is defined as "a cohort of people born within a similar span of time (15 years at the upper end) who share a comparable age and life stage and who were shaped by a particular span of time (events, trends and developments)." Generational segmentation refers to the process of dividing and analysing a population into cohorts based on their birth date. Generational segmentation assumes that people's values and attitudes are shaped by the key events that occurred during their lives and that these attitudes translate into product and brand preferences.
Demographers, studying population change, disagree about precise dates for each generation. Dating is normally achieved by identifying population peaks or troughs, which can occur at different times in each country. For example, in Australia the post-war population boom peaked in 1960, while the peak occurred somewhat later in the USA and Europe, with most estimates converging on 1964. Accordingly, Australian Boomers are normally defined as those born between 1945–1960; while American and European Boomers are normally defined as those born between 1945–64. Thus, the generational segments and their dates discussed here must be taken as approximations only.
The primary generational segments identified by marketers are:
- Builders: born 1920 to 1945
- Baby boomers: born about 1945–1965
- Generation X: born about 1966–1976
- Generation Y: also known as Millennials; born about 1977–1994
- Generation Z: also known as Centennials; born 1995–2015
|Millenials||Generation X||Baby Boomers|
|Technology use (24%)||Technology use (12%)||Work ethic (17%)|
|Music/ popular culture (11%)||Work ethic (11%)||Respectful (14%)|
|Liberal/ tolerant (7%)||Conservative/ traditional (7%)||Values/ morals (8%)|
|Smarter (6%)||Smarter (6%)||Smarter (5%)|
|Clothes (5%)||Respectful (5%)||n.a.|
Cultural segmentation is used to classify markets according to cultural origin. Culture is a major dimension of consumer behavior and can be used to enhance customer insight and as a component of predictive models. Cultural segmentation enables appropriate communications to be crafted to particular cultural communities. Cultural segmentation can be applied to existing customer data to measure market penetration in key cultural segments by product, brand, channel as well as traditional measures of recency, frequency and monetary value. These benchmarks form an important evidence-base to guide strategic direction and tactical campaign activity, allowing engagement trends to be monitored over time.
Cultural segmentation can also be mapped according to state, region, suburb and neighborhood. This provides a geographical market view of population proportions and may be of benefit in selecting appropriately located premises, determining territory boundaries and local marketing activities.
Census data is a valuable source of cultural data but cannot meaningfully be applied to individuals. Name analysis (onomastics) is the most reliable and efficient means of describing the cultural origin of individuals. The accuracy of using name analysis as a surrogate for cultural background in Australia is 80–85%, after allowing for female name changes due to marriage, social or political reasons or colonial influence. The extent of name data coverage means a user will code a minimum of 99 percent of individuals with their most likely ancestral origin.
Selecting target markets
Another major decision in developing the segmentation strategy is the selection of market segments that will become the focus of special attention (known as target markets). The marketer faces a number of important decisions:
- What criteria should be used to evaluate markets?
- How many markets to enter (one, two or more)?
- Which market segments are the most valuable?
When a marketer enters more than one market, the segments are often labelled the primary target market, secondary target market. The primary market is the target market selected as the main focus of marketing activities. The secondary target market is likely to be a segment that is not as large as the primary market, but has growth potential. Alternatively, the secondary target group might consist of a small number of purchasers that account for a relatively high proportion of sales volume perhaps due to purchase value or purchase frequency.
In terms of evaluating markets, three core considerations are essential:
- Segment size and growth
- Segment structural attractiveness
- Company objectives and resources.
Criteria for evaluating segment attractiveness
There are no formulas for evaluating the attractiveness of market segments and a good deal of judgement must be exercised. Nevertheless, a number of considerations can be used to assist in evaluating market segments for overall attractiveness. The following lists a series of questions that can be asked.
Segment size and growth
- How large is the market?
- Is the market segment substantial enough to be profitable? (Segment size can be measured in number of customers, but superior measures are likely to include sales value or volume)
- Is the market segment growing or contracting?
- What are the indications that growth will be sustained in the long term? Is any observed growth sustainable?
- Is the segment stable over time? (Segment must have sufficient time to reach desired performance level)
Segment structural attractiveness
- To what extent are competitors targeting this market segment?
- Do buyers have bargaining power in the market?
- Are substitute products available?
- Can we carve out a viable position to differentiate from any competitors?
- How responsive are members of the market segment to the marketing program?
- Is this market segment reachable and accessible? (i.e., with respect to distribution and promotion)
Company objectives and resources
- Is this market segment aligned with our company's operating philosophy?
- Do we have the resources necessary to enter this market segment?
- Do we have prior experience with this market segment or similar market segments?
- Do we have the skills and/or know-how to enter this market segment successfully?
Developing the marketing program and positioning strategy
When the segments have been determined and separate offers developed for each of the core segments, the marketer's next task is to design a marketing program (also known as the marketing mix) that will resonate with the target market or markets. Developing the marketing program requires a deep knowledge of key market segment's purchasing habits, their preferred retail outlet, their media habits and their price sensitivity. The marketing program for each brand or product should be based on the understanding of the target market (or target markets) revealed in the market profile.
Positioning is the final step in the S-T-P planning approach; Segmentation→ Targeting → Positioning; a core framework for developing marketing plans and setting objectives. Positioning refers to decisions about how to present the offer in a way that resonates with the target market. During the research and analysis that forms the central part of segmentation and targeting, the marketer will have gained insights into what motivates consumers to purchase a product or brand. These insights will form part of the positioning strategy.
According to advertising guru, David Ogilvy, "Positioning is the act of designing the company’s offering and image to occupy a distinctive place in the minds of the target market. The goal is to locate the brand in the minds of consumers to maximize the potential benefit to the firm. A good brand positioning helps guide marketing strategy by clarifying the brand’s essence, what goals it helps the consumer achieve, and how it does so in a unique way." 
The technique known as perceptual mapping is often used to understand consumers' mental representations of brands within a given category. Traditionally two variables (often, but not necessarily, price and quality) are used to construct the map. A sample of people in the target market are asked to explain where they would place various brands in terms of the selected variables. Results are averaged across all respondents, and results are plotted on a graph, as illustrated in the figure. The final map indicates how the average member of the population views the brand that make up a category and how each of the brands relates to other brands within the same category. While perceptual maps with two dimensions are common, multi-dimensional maps are also used.
There are a number of different approaches to positioning:
- Against a competitor
- Within a category
- According to product benefit
- According to product attribute
- For usage occasion
- Along price lines e.g. a luxury brand or premium brand
- For a user
- Cultural symbols e.g. Australia's Easter Bilby (as a culturally appropriate alternative to the Easter Bunny).
Bases for segmenting business markets
Segmenting business markets is more straightforward than segmenting consumer markets. Businesses may be segmented according to industry, business size, business location, turnover, number of employees, company technology, purchasing approach or any other relevant variables.
Firmographics (also known as emporographics or feature based segmentation) is the business community's answer to demographic segmentation. It is commonly used in business-to-business markets (it’s estimated that 81% of B2B marketers use this technique). Under this approach the target market is segmented based on features such as company size (either in terms of revenue or number of employees), industry sector or location (country and/or region).
In sales territory management, using more than one criterion to characterize the organization’s accounts,such as segmenting sales accounts by government, business, customer, etc. and account size or duration, in effort to increase time efficiency and sales volume.
Use in customer retention
The basic approach to retention-based segmentation is that a company tags each of its active customers on four axes:
- Risk of customer cancellation of company service
- One of the most common indicators of high-risk customers is a drop off in usage of the company's service. For example, in the credit card industry this could be signaled through a customer's decline in spending on his or her card.
- Risk of customer switching to a competitor
- Many times customers move purchase preferences to a competitor brand. This may happen for many reasons those of which can be more difficult to measure. It is many times beneficial for the former company to gain meaningful insights, through data analysis, as to why this change of preference has occurred. Such insights can lead to effective strategies for winning back the customer or on how not to lose the target customer in the first place.
- Customer retention worthiness
- This determination boils down to whether the post-retention profit generated from the customer is predicted to be greater than the cost incurred to retain the customer, and includes evaluation of customer lifecycles.
- Tactics to use for retention of customer
- This analysis of customer lifecycles is usually included in the growth plan of a business to determine which tactics to implement to retain or let go of customers. Tactics commonly used range from providing special customer discounts to sending customers communications that reinforce the value proposition of the given service.
Segmentation: algorithms and approaches
The choice of an appropriate statistical method for the segmentation, depends on a number of factors including, the broad approach (a-priori or post-hoc), the availability of data, time constraints, the marketer's skill level and resources.
A priori research occurs when "a theoretical framework is developed before the research is conducted". In other words, the marketer has an idea about whether to segment the market geographically, demographically, psychographically or behaviorally before undertaking any research. For example, a marketer might want to learn more about the motivations and demographics of light and moderate users in an effort to understand what tactics could be used to increase usage rates. In this case, the target variable is known – the marketer has already segmented using a behavioral variable – user status. The next step would be to collect and analyse attitudinal data for light and moderate users. Typical analysis includes simple cross-tabulations, frequency distributions and occasionally logistic regression or one of a a number of proprietary methods.
The main disadvantage of a-priori segmentation is that it does not explore other opportunities to identify market segments that could be more meaningful.
In contrast, post-hoc segmentation makes no assumptions about the optimal theoretical framework. Instead, the analyst's role is to determine the segments that are the most meaningful for a given marketing problem or situation. In this approach, the empirical data drives the segmentation selection. Analysts typically employ some type of clustering analysis or structural equation modeling to identify segments within the data. The figure alongside illustrates how segments might be formed using clustering, however note that this diagram only uses two variables, while in practice clustering employs a large number of variables. Post-hoc segmentation relies on access to rich data sets, usually with a very large number of cases.
Statistical techniques used in segmentation
Marketers often engage commercial research firms or consultancies to carry out segmentation analysis, especially if they lack the statistical skills to undertake the analysis. Some segmentation, especially post-hoc analysis, relies on sophisticated statistical analysis.
Common statistical approaches and techniques used in segmentation analysis include:
- Clustering algorithms  – overlapping, non-overlapping and fuzzy methods; e.g. K-means or other Cluster analysis
- Conjoint analysis
- Ensemble approaches – such as random forests
- Chi-square automatic interaction detection – a type of decision-tree
- Factor analysis or principal components analysis
- Logistic regression
- Multidimensional scaling and canonical analysis
- Mixture models – e.g., EM estimation algorithm, finite-mixture models for simple Latent Class Analysis 
- Model based segmentation using simultaneous and structural equation modeling e.g. LISREL
- Other algorithms such as artificial neural networks.
Data sources used for segmentation
- Customer transaction records e.g. sale value per transaction, purchase frequency
- Patron membership records e.g. active members, lapsed members, length of membership
- Customer relationship management (CRM) databases
- In-house surveys
- Customer self-completed questionnaires or feedback forms
- Proprietary surveys or tracking studies
- Proprietary databases/ software
- Omnibus surveys
- Government agencies and departments
- Government statistics
- Professional/ Industry associations/ Employer associations
- Census data
- Observed purchase behaviors
- Data-mining techniques
- Commissioned research
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