Market segmentation is the activity 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 common characteristics such as shared 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, behavioural 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.
Definition and brief explanationEdit
Market segmentation is the process of dividing up mass markets into groups with similar needs and wants. The rationale for market segmentation is that in order to achieve competitive advantage and superior performance, firms should: "(1) identify segments of industry demand, (2) target specific segments of demand, and (3) develop specific 'marketing mixes' for each targeted market segment. " From an economic perspective, segmentation is built on the assumption that heterogeneity in demand allows for demand to be disaggregated into segments with distinct demand functions.
- 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 lifecycle. 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 (post-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.
The practice of market segmentation emerged well before marketers thought about it at a theoretical level. Archaeological evidence suggests that Bronze Age traders segmented trade routes according to geographical circuits. Other evidence suggests that the practice of modern market segmentation was developed incrementally from the 16th century onwards. Retailers, operating outside the major metropolitan cities, could not afford to serve one type of clientele exclusively, yet retailers needed to find ways to separate the wealthier clientele from the "riff raff". One simple technique was to have a window opening out onto the street from which customers could be served. This allowed the sale of goods to the common people, without encouraging them to come inside. Another solution, that came into vogue from the late sixteenth century, was to invite favored customers into a back-room of the store, where goods were permanently on display. Yet another technique that emerged around the same time was to hold a showcase of goods in the shopkeeper's private home for the benefit of wealthier clients. Samuel Pepys, for example, writing in 1660, describes being invited to the home of a retailer to view a wooden jack. The eighteenth-century English entrepreneurs, Josiah Wedgewood and Matthew Boulton, both staged expansive showcases of their wares in their private residences or in rented halls to which only the upper classes were invited while Wedgewood used a team of itinerant salesmen to sell wares to the masses.
Evidence of early marketing segmentation has also been noted elsewhere in Europe. A study of the German book trade found examples of both product differentiation and market segmentation in the 1820s. From the 1880s, German toy manufacturers were producing models of tin toys for specific geographic markets; London omnibuses and ambulances destined for the British market; French postal delivery vans for Continental Europe and American locomotives intended for sale in America. Such activities suggest that basic forms of market segmentation have been practised since the 17th century and possibly earlier.
Contemporary market segmentation emerged in the first decades of 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. By the 1930s, market researchers such as Ernest Dichter recognised that demographics alone were insufficient to explain different marketing behaviours and began exploring the use of lifestyles, attitudes, values, beliefs and culture to segment markets. With access to group level data only, brand marketers approached the task from a tactical viewpoint. Thus, segmentation was essentially a brand-driven process.
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 at least the 1920s.
Until relatively recently, most segmentation approaches have retained a 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. Some scholars have argued that the fragmentation of markets has rendered traditional approaches to market segmentation less useful.
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 strategyEdit
A key consideration for marketers is whether to segment or not to segment. Depending on company philosophy, resources, product type or market characteristics, a business 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, iodised salt, salt substitutes and many more. Sugar also comes in many different types - cane sugar, beet sugar, raw sugar, white refined sugar, brown sugar, caster sugar, sugar lumps, icing sugar (also known as milled sugar), sugar syrup, invert sugar and a plethora of sugar substitutes including smart sugar which is essentially a blend of pure sugar and a sugar substitute. Each of these product types is designed to meet the needs of specific market segments. Invert sugar and sugar syrups, for example, are marketed to food manufacturers where they are used in the production of conserves, chocolate, and baked goods. Sugars marketed to consumers appeal to different usage segments – refined sugar is primarily for use on the table, while caster sugar and icing sugar are primarily designed for use in home-baked goods.
|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, positioningEdit
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 voluminous data, and requires a great deal of skill in analysis, interpretation and some judgment. 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 the identification of optimal position and development of the marketing program.
Identifying the market to be segmentedEdit
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 straightforward. 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] × [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 marketsEdit
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 color 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, substantial, responsive, actionable and stable.
- Identifiability refers to the extent to which managers can identify or recognise distinct groups within the marketplace
- Substantiality refers to the extent to which a segment or group of customers represents a sufficient size to be profitable. This could mean sufficiently large in number of people or in purchasing power
- Accessibility refers to the extent to which marketers can reach the targeted segments with promotional or distribution efforts
- Responsiveness refers to the extent to which consumers in a defined segment will respond to marketing offers targeted at them
- Actionable – segments are said to be actionable when they provide guidance for marketing decisions.
For example, although dress size is not a standard base for segmenting a market, some fashion houses have successfully 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 behaviour. 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 behavioural 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|
|Contextual and situational||The same consumer changes in their attractiveness to marketers based on context and situation. This is particularly used in digital targeting via programmatic bidding approaches||e.g. Actively shopping, just entering into a life change event, being physically in a certain location or at a particular retailer which is known from GPS data via smartphones.|
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. Brazil, Canada, China, France, Germany, India, Italy, Japan, UK, US
- 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
- Socio-economic: 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. 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.
- DINK: 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
- GLAM: 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: 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; they are 'in between'.
- 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 psychometric or 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.
Behavioural segmentation divides consumers into groups according to their observed behaviours. Many marketers believe that behavioural variables are superior to demographics and geographics for building market segments and some analysts have suggested that behavioural segmentation is killing off demographics. Typical behavioural 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 customise 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 behavioural segmentation, using attitude to product or service as a key descriptor or variable which has been customised for the specific application.
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, behaviour 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 segmentation (sometimes called needs-based segmentation) was developed by Grey Advertising in the late 1960s. The benefits-sought by purchasers enables the market to be divided into segments with distinct needs, perceived value, benefits sought or advantage that accrues from the purchase of a product or service. Marketers using benefit 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 behaviour. 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 behaviour relating to environmental protection:
- Greens: Driven by the belief that protecting the 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 behaviours 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 behaviour 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 a behavioural change is a consideration; their everyday behaviours often have a low impact on the environment, but for other reasons than conservation
- Disinterested: View greenies as an eccentric minority; exhibit no interest in changing their behaviour; 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 segmentationEdit
In addition to geographics, demographics, psychographics and behavioural 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 analyzing 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 US 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
|Millennials||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%|
Cultural segmentation is used to classify markets according to cultural origin. Culture is a major dimension of consumer behaviour 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 be combined with other bases, especially geographics so that segments are 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.
Online customer segmentationEdit
Online market segmentation is similar to the traditional approaches in that the segments should be identifiable, substantial, accessible, stable, differentiable and actionable. Customer data stored in online data management systems such as a CRM or DMP enables the analysis and segmentation of consumers across a diverse set of attributes. Forsyth et al., in an article 'Internet research' grouped current active online consumers into six groups: Simplifiers, Surfers, Bargainers, Connectors, Routiners, and Sportsters. The segments differ regarding four customers' behaviours, namely:
- The amount of time they actively spend online,
- The number of pages and sites they access,
- The time they spend actively viewing each page,
- And the kinds of sites they visit.
For example, Simplifiers make over 50 percent of all online transactions. Their main characteristic is that they need easy (one-click) access to information and products as well as easy and quickly available service regarding products. Amazon.com is a good example of a company who created an online environment for Simplifiers. They also 'dislike unsolicited e-mail, uninviting chat rooms, pop-up windows intended to encourage impulse buys, and other features that complicate their on- and off-line experience'. Surfers like to spend a lot of time online, thus companies must have a variety of products to offer and constant update, Bargainers are looking for the best price, Connectors like to relate to others, Routiners want content and Sportsters like sport and entertainment sites.
Selecting target marketsEdit
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 labeled 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 attractivenessEdit
There are no formulas for evaluating the attractiveness of market segments and a good deal of judgment 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 growthEdit
- 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 attractivenessEdit
- 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 resourcesEdit
- 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 strategyEdit
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 maximise 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 makes 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 marketsEdit
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. The most widely used segmentation bases used in business to business markets are geographics, and firmographics.
The most-widely used bases for segmenting business markets are:
- Geographic segmentation occurs when a firm seeks to identify the most promising geographic markets to enter. Business can tap into business census type products published by Government departments to identify geographic regions that meet certain predefined criteria.
- 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 (an estimated 81% of B2B marketers use this technique). Under this approach the target market is segmented based on features such as company size, industry sector or location usage rate, purchase frequency, number of years in business, ownership factors and buying situation.
- Key firmographic variables: standard industry classification (SIC); company size (either in terms of revenue or number of employees), industry sector or location (country and/or region), usage rate, purchase frequency, number of years in business, ownership factors and buying situation
Use in customer retentionEdit
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.
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 approachesEdit
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 behaviourally 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 behavioural variable – user status. The next step would be to collect and analyze attitudinal data for light and moderate users. The typical analysis includes simple cross-tabulations, frequency distributions and occasionally logistic regression or one of 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 datasets, usually with a very large number of cases and uses sophisticated algorithms to identify segments.
Statistical techniques used in segmentationEdit
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
- Latent Class Analysis – a generic term for a class of methods that attempt to detect underlying clusters based on observed patterns of association
- Logistic regression
- Multidimensional scaling and canonical analysis
- Mixture models – e.g., EM estimation algorithm, finite-mixture models
- Model-based segmentation using simultaneous and structural equation modeling e.g. LISREL
- Other algorithms such as artificial neural networks.
Data sources used for segmentationEdit
- 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
- Commissioned research (where the business commissions a research study and maintains exclusive rights to the data; typically the most expensive means of data collection)
- Data-mining techniques
- Census data (population and business census)
- Observed purchase behaviours
- Government agencies and departments
- Government statistics and surveys (e.g. studies by departments of trade, industry, technology etc.)
- Omnibus surveys (a standard, regular survey with a basic set of questions about demographics and lifestyles where individual can add specific sets of questions about product preference or usage; generally lower cost than commissioned survey methods)
- Professional/Industry associations/Employer associations
- Proprietary surveys or tracking studies (also known as syndicated research; studies carried out by market research companies where business can purchase the right to access part of the data set)
- Proprietary databases/software
Companies (proprietary segmentation databases)Edit
- Acorn – geo-demographic segmentation
- Claritas Prizm – geo-demographic segmentation
- Experian – geo-demographic segmentation
- Mosaic – geo-demographic segmentation
- Roy Morgan Research Values Segments -psychographic/ psychometric
- VALS-psychographic/ psychometric
- Values Modes-psychographic/ psychometric
- Marketing § Market segmentation
- Market analysis § Market segmentation
- Attitudinal targeting
- Behavioural targeting
- Demographic profile
- Demographic targeting
- Geodemographic segmentation
- Mass marketing
- Niche market
- Positioning (marketing)
- Precision marketing
- Precision marketing
- Product differentiation
- Sagacity segmentation
- Segmenting and positioning
- Serviceable available market
- Target audience
- Targeted advertising
- Total addressable market
- Pride, W., Ferrell, O.C., Lukas, B.A., Schembri, S., Niininen, O. and Cassidy, R., Marketing Principles, 3rd Asia-Pacific ed, Cengage, 2018, p. 200
- Madhavaram, S., & Hunt, S. D., "The Service-dominant Logic and a Hierarchy of Operant Resources: Developing Masterful Operant Resources and Implications for Marketing Strategy, " Journal Of The Academy Of Marketing Science, Vol. 36, No. 1, 2008, pp 67-82.
- Dickson, Peter R.; Ginter, James L., "Market Segmentation, Product Differentiation, and Marketing Strategy, " Journal of Marketing, Vol. 51, No. 2, 1987, p. 1
- In his oft-cited work, New and Improved: The Story of Mass Marketing in America, Basic Books, N.Y. 1990 pp. 4–12, Richard Tedlow outlines first three stages: fragmentation, unification and segmentation. In a subsequent work, published three years later, Tedlow and his co-author thought that they had seen evidence of a new trend and added a fourth era, termed Hyper-segmentation (post 1980s); See Tedlow, R.A. and Jones, G., The Rise and Fall of Mass Marketing, Routledge, N.Y., 1993, Chapter 2
- Fullerton, R., "Segmentation in Practice: An Overview of the Eighteenth and Nineteenth Centuries," in Jones, D.G.B. and Tadajewski, M. (eds), The Routledge Companion to Marketing History, Oxon, Routledge, 2016, p. 94
- Alberti, M. E., "Trade and Weighing Systems in the Southern Aegean from the Early Bronze Age to the Iron Age: How Changing Circuits Influenced Glocal Measures," in Molloy, B. (ed.), Of Odysseys and Oddities: Scales and Modes of Interaction Between Prehistoric Aegean Societies and their Neighbours, [Sheffield Studies in Aegean Archaeology], Oxford, Oxbow, (E-Book), 2016
- Cox, N.C. and Dannehl, K., Perceptions of Retailing in Early Modern England, Aldershot, Hampshire, Ashgate, 2007, pp. 155–59
- McKendrick, N., Brewer, J. and Plumb, J.H., The Birth of a Consumer Society: The Commercialization of Eighteenth Century England, London, 1982.
- Fullerton, R.A., "Segmentation Strategies and Practices in the 19th-Century German Book Trade: A Case Study in the Development of a Major Marketing Technique", in Historical Perspectives in Consumer Research: National and International Perspectives, Jagdish N. Sheth and Chin Tiong Tan (eds), Singapore, Association for Consumer Research, pp 135-139
- Pressland, David, Book of Penny Toys, Pei International, 1991; Cross, G., Kids' Stuff: Toys and the Changing World of American Childhood, Harvard University Press, 2009, pp 95-96
- Jones, G.D.B. and Tadajewski, M. (eds), The Routledge Companion to Marketing History, Oxon, Routledge, 2016, p. 66
- Lockley, L.C., "Notes on the History of Marketing Research", Journal of Marketing, Vol. 14, No. 5, 1950, pp. 733–736
- Lockley, L.C., "Notes on the History of Marketing Research", Journal of Marketing, vol. 14, no. 5, 1950, p. 71
- Wilson B. S. and Levy, J., "A History of the Concept of Branding: Practice and Theory", Journal of Historical Research in Marketing, vol. 4, no. 3, 2012, pp. 347-368; DOI: 10.1108/17557501211252934
- Cano, C., "The Recent Evolution of Market Segmentation Concepts and Thoughts Primarily by Marketing Academics," in E. Shaw (ed) The Romance of Marketing History, Proceedings of the 11th Conference on Historical Analysis and Research in Marketing (CHARM), Boca Raton, FL, AHRIM, 2003.
- Smith, W.R., "Product Differentiation and Market Segmentation as Alternative Marketing Strategies," Journal of Marketing, Vol. 21, No. 1 , 1956, pp. 3–8 and reprinted in Marketing Management, vol. 4, no. 3, 1995, pp. 63–65
- Schwarzkopf, S., "Turning Trade Marks into Brands: How Advertising Agencies Created Brands in the Global Market Place, 1900–1930" CGR Working Paper, Queen Mary University, London, 18 August 2008
- Kara, A and Kaynak, E., "Markets of a Single Customer: Exploiting Conceptual Developments in Market Segmentation", European Journal of Marketing, vol. 31, no. 11/12, 1997, pp. 873–895, DOI: https://dx.doi.org/10.1108/03090569710190587
- Firat, A.F. and Shultz, C.J., "From Segmentation to Fragmentation: Markets and Marketing Strategy in the Postmodern Era," European Journal of Marketing, vol. 31 no. 3/4, 1997, pp 183-207
- Hoek, J., Gendall, P. and Esslemont, D., Market segmentation: A search for the Holy Grail?, Journal of Marketing Practice Applied Marketing Science, Vol. 2, no. 1, pp. 25–34, 1996
- Addison, T. and O'Donohue, M., "Understanding the Customer’s Relationship With a Brand: The Role of Market Segmentation in Building Stronger Brands," Market Research Society Conference, London, 2001, Online: http://www.warc.com/fulltext/MRS/49705.htm
- Kennedy, R. and Ehrenberg, A., "What’s in a brand?" Research, April, 2000, pp 30–32
- Bardakci, A. and Whitelock, L., "Mass-customisation in Marketing: The Consumer Perspective," Journal of Consumer Marketing' vol. 20, no.5, 2003, pp. 463–479.
- Smit, E. G. and Niejens, P. C., 2000. "Segmentation Based on Affinity for Advertising," Journal of Advertising Research, vol. 40, no. 4, 2000, pp. 35–43.
- Albaum, G. and Hawkins, D. I., "Geographic Mobility and Demographic and Socioeconomic Market Segmentation," Journal of the Academy of Marketing Science, vol. 11, no. 2. 1983, pp. 97–114.
- Blocker, C. P. and Flint, D. J., 2007. "Customer Segments as Moving Targets: Integrating Customer Value Dynamism into Segment Instability Logic," Industrial Market Management, vol. 36, no. 6., 2007, pp. 810–822.
- Board, T. "Ten Lessons Learned from Cybersegmentation," Technology & Communications practice for IIR – The Market Research Event IPSOS Insight. 2004 [On-line] http://www.ipsosinsight.com/pdf/IpsosInsight_PD_TenTips.pdf
- Yankelovich, D., Meer, D. "Rediscovering Market Segmentation", Harvard Business Review vol. 84. no 2, 2006, pp. 122–13
- Business Dictionary Online: http://www.businessdictionary.com/definition/undifferentiated-marketing.html
- Based on Weinstein, A., Market Segmentation Handbook: Strategic Targeting for Business and Technology Firms, 3rd ed., Haworth Press, Binghampton, N.Y., 2004, p. 12
- Marketing Insider, Market Targeting: Target Segments Effectively and Efficiently, https://marketing-insider.eu/marketing-explained/part-i-defining-marketing-and-the-marketing-process/market-targeting/
- Moutinho, L., "Segmentation, Targeting, Positioning and Strategic Marketing," Chapter 5 in Strategic Management in Tourism, Moutinho, L. (ed), CAB International, 2000, pp. 121–166.
- Lesser,B. and Vagianos,L. Computer Communications and the Mass Market in Canada, Institute for Research on Public Policy, 1985, p. 37.
- Mauboussin, M.J. and Callahan, D., Total Addressable Market: Methods to Estimate a Company's Potential Sales, [Occasional Paper], Credit-Suisse – Global Financial Strategies, 1 September 2015
- See for example, Lilien,G., Rangaswamy, A. and Van den Bulte, C., “Diffusion Models: Managerial Applications and Software,” ISBM Report 7, May 20, 1999.
- Sarin, S., Market Segmentation and Targeting, Wiley International Encyclopedia of Marketing, 2010
- Gavett, G., "What You Need to Know About Segmentation," Harvard Business Review, Online: July 09, 2014 https://hbr.org/2014/07/what-you-need-to-know-about-segmentation
- Wedel,M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, pp 4-5.
- In the early 1980s, Australian fashion designer, Maggie T, was the recipient of a Hoover Award for a segmentation study which showed that women with dress size 16+ underspent on clothes because they were unable to find suitable garments. This insight led to the establishment of 'plus-sized' fashion outlets. Case study reported in Australian Marketing Projects: the Hoover Award for Marketing, West Ryde, Australia, 1982
- Wedel,M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, pp 8-9
- 'What is geographic segmentation' Kotler, Philip, and Kevin Lane Keller. Marketing Management. Prentice Hall, 2006. ISBN 978-0-13-145757-7
- Doos, L. Uttley, J. and Onyia, I., "Mosaic segmentation, COPD and CHF multimorbidity and hospital admission costs: a clinical linkage study," Journal of Public Health, Vo. 36, no. 2, 2014, pp. 317–324
- Reid, Robert D.; Bojanic, David C. (2009). Hospitality Marketing Management (Fifth ed.). John Wiley and Sons. p. 139. ISBN 978-0-470-08858-6. Retrieved 2013-06-08.
- Baker,M., The Marketing Book, 5th ed, Oxford, Butterworth-Heinemann, 2003, p.709
- Sarin, S., Market Segmentation and Targeting, Wiley International Encyclopedia of Marketing, Vol. 1
- Sara C. Parks PhD & Frederick J. Demicco, "Age- and Gender-Based Market Segmentation: A Structural Understanding,"International Journal of Hospitality & Tourism Administration, Vol. 3, No. 1, 2002, DOI: https://dx.doi.org/10.1300/J149v03n01_01
- Tynan, A.N and Drayton, J., "Market segmentation," Journal of Marketing Management, Vol. 2, No. 3, 1987, DOI:https://dx.doi.org/10.1080/0267257X.1987.9964020
- Coleman, R., “The Continuing Significance of Social Class to Marketing.” Journal of Consumer Research, Vol. 10, 1983, pp 265-280
- Gilly, M.C. and Enis, B.M., "Recycling the Family Life Cycle: a Proposal For Redefinition", in Advances in Consumer Research, Vol. 09, Andrew Mitchell (ed.), Ann Abor, MI: Association for Consumer Research, pp 271-276, Direct URL:http://acrwebsite.org/volumes/6007/volumes/v09/NA-09
- Boushey, H., Finding Time, Boushey, 2016
- Courtwright, D.T., No Right Turn, Harvard University Press, 2010, p. 147
- Dension, D. and Hogg, R., (eds), A History of the English Language, Cambridge, Cambridge University Press, 2008, p. 270
- Thorne, T., Dictionary of Contemporary Slang, 4th ed, London, Bloomsbury, 2014,
- Burridge, K., Blooming English: Observations on the Roots, Cultivation and Hybrids of the English Language, Cambridge, Cambridge University Press, 2004, pp. 54–55
- "Market Segmentation and Targeting". Academic.brooklyn.cuny.edu. 2011. Archived from the original on 1 August 2014. Retrieved 15 July 2014.
- Wedel, M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, pp 10-15
- Philip Kotler and Gary Armstrong, Principles of Marketing, Pearson, 2014; 2012
- Burrows, D., "Is behavioural data killing off demographics?" Marketing Week,4 September 2015
- Kotler, P., Marketing Management: Planning, Analysis, Implementation and Control, 9th ed., Upper Saddle River, Pearson, 1991
- Clancy, K.J. and Roberts, M.L., "Towards an Optimal Market Target: A Strategy for Market Segmentation", Journal of Consumer Marketing, vol. 1, no. 1, pp 64-73
- Ahmad, R., "Benefit Segmentation: A potentially useful technique of segmenting and targeting older consumers," International Journal of Market Research, Vol. 45, No. 3, 2003
- Loker, L.E. and Perdue, R.R., "A Benefit–Based Segmentation," Journal of Travel Research, Vol. 31, No. 1, 1992, pp. 30–35
- Simkin, L., "Segmentation," in Baker, M.J. and Hart, S., The Marketing Book, 7th ed., Routledge, Oxon, UK, 2016, pp. 271–294
- McCrindle, M., Generations Defined [Booklet] n.d. circa 2010 Online: http://mccrindle.com.au/BlogRetrieve.aspx?PostID=146968&A=SearchResult&SearchID=9599835&ObjectID=146968&ObjectType=55
- Cran, C., The Art of Change Leadership: Driving Transformation In a Fast-Paced World, Wiley, Hoboken, N.J. 2016, pp. 174–75
- Salt, B., The Big Shift , South Yarra, Vic.: Hardie Grant Books, 2004 ISBN 978-1-74066-188-1
- U.S. Census Bureau, American Fact Finder: Age Groups and Sex, 2010
- McCrindle Research, Seriously Cool – Marketing & Communicating with Diverse Generations, Norwest Business Park, Australia, n.d. c. 2010
- Taylor, Paul; Gao, George (5 June 2014). "Generation X: America's neglected 'middle child'". Pew Research Center. Retrieved 24 July 2018.
- Ellson, T., Culture and Positioning as Determinants of Strategy: Personality and the Business Organization, Springer, 2004
- Gretchen Gavett, July 09/2014, What You Need to Know About Segmentation, Harvard Business Review, accessed online 3/04/2017: 
- "Management Tools - Customer Relationship Management". www.bain.com. Retrieved 23 November 2015.
- Forsyth, John E.; Lavoie, Johanne; McGuire, Tim. Segmenting the e-market. McKinsey Quarterly. 2000, Issue 4, p14-18. 5p.
- Marketing Insider, "Evaluating Market Segments", Online: http://targetmarketsegmentation.com/target-market/secondary-target-markets/
- Applbaum, K., The Marketing Era: From Professional Practice to Global Provisioning, Routledge, 2004, p. 33-35
- Ogilvy, David (1985). Ogilvy on advertising (First ed.). Vintage Books. ISBN 9780394729039.
- Based on Belch, G., Belch, M.A, Kerr, G. and Powell, I., Advertising and Promotion Management: An Integrated Marketing Communication Perspective, McGraw-Hill, Sydney, Australia, 2009, pp. 205–206
- Shapiro, B.P. and Bonoma, T.V., "How to Segment Industrial Markets," Harvard Business Review, May 1984, Online: https://hbr.org/1984/05/how-to-segment-industrial-markets
- Weinstein, A., Handbook of Market Segmentation: Strategic Targeting for Business and Technology Firms, 3rd ed., Routledge, 2013, Chapter 4
- "B2B Market Segmentation Research" (PDF). Circle Research. Circle Research. Retrieved 9 June 2015.
- Gupta, Sunil. Lehmann, Donald R. Managing Customers as Investments: The Strategic Value of Customers in the Long Run, pp. 70–77 (“Customer Retention” section). Upper Saddle River, NJ: Pearson Education/Wharton School Publishing, 2005. ISBN 0-13-142895-0
- Goldstein, Doug. “What is Customer Segmentation?” MindofMarketing.net, May 2007. New York, NY.
- Hunt, Shelby; Arnett, Dennis (16 June 2004). "Market Segmentation Strategy, Competitive Advantage, and Public Policy". 12 (1). Australasian Marketing Journal: 1–25. CiteSeerX 10.1.1.199.3118.
- Myers, J.H., Segmentation and Positioning for Strategic Marketing Decisions, American Marketing Association, 1996
- Market Research Association, Glossary of Terms, Online:http://www.marketingresearch.org/issues-policies/glossary
- Wedel, M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, pp 22-23.
- Constantin, C., "Post-hoc Segmentation using Marketing Research," Economics, Vol 12, no 3, 2012, pp. 39–48.
- Wedel, M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, pp 24-26.
- http://evgeniou,T., Cluster Analysis and Segmentation, Online: inseaddataanalytics.github.io/INSEADAnalytics/Report_s45.html [with worked example]
- Desarbo, W.S., Ramaswamy, V. and Cohen, S. H., "Market segmentation with choice-based conjoint analysis," Marketing Letters, vol. 6, no. 2 pp. 137–147.
- Perbert, F., Stenger, B. and Maki, A., "Random Forest Clustering and Application to Video Segmentation," [Research Paper], Toshiba Europe, 2009, Online: https://mi.eng.cam.ac.uk/~bdrs2/papers/perbet_bmvc09.pdf
- Dell Software, Statistics Textbook, Online: https://documents.software.dell.com/statistics/textbook/customer-segmentation
- Minhas, R.S. and Jacobs, E.M., "Benefit Segmentation by Factor Analysis: An improved method of targeting customers for financial services", International Journal of Bank Marketing, Vol. 14, no. 3, pp. 3–13.
- Wedel,M. and Kamakura, W.A., Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2010, p. 21.
- Burinskiene, M. and Rudzkiene, V., "Application of Logit Regression Models for the Identification of Market Segments", Journal of Business Economics and Management, vol. 8, no. 4, 2008, pp. 253–258.
- T.P. Beane and D.M. Ennis, "Market Segmentation: A Review", European Journal of Marketing, Vol. 21 no. 5, pp. 20–42.
- Green, P.E., Carmone, F.J. and Wachspress, D.P., Consumer Segmentation Via Latent Class Analysis,Journal of Consumer Research, December, 1976, pp. 170–174, DOI: https://dx.doi.org/10.1086/208664
- Swait, J., "A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data," Journal of Retailing and Consumer Services, Vol. 1, no. 2, 1994, pp. 77–89.
- Kelly E Fish, K.E., Barnes, J.H. and Aiken, M.W., "Artificial neural networks: A new methodology for industrial market segmentation," Industrial Marketing Management, Vol. 24, no. 5, 1995, pp. 431–438.
- US Government, Small Business Administration, Online: https://www.sba.gov/blogs/conducting-market-research-here-are-5-official-sources-free-data-can-help
- Marr, C., "Big Data: 33 Brilliant and Ad Free Data Sources for 2016," Forbes, 12 February 2016, Online: https://www.forbes.com/sites/bernardmarr/2016/02/12/big-data-35-brilliant-and-free-data-sources-for-2016/#7ef90b046796
- Wedel, M. and Wagner, A., Market Segmentation: Conceptual and Methodological Foundations, Kluwer Academic Publishers, 1998, See Chapter 14
- For an excellent discussion of ACORN, see Chris Fill, Marketing Communications: Framework, Theories and Application, London, Prentice Hall, 1995, p. 70 and P.R. Smith, Marketing Communications: An Integrated Approach, London, Kogan Page, 1996, p. 126; Stone et al, Fundamentals of Marketing, Routledge, 2007, Chapter 6; Wedel and Wagner, Market Segmentation: Conceptual and Methodological Foundations, pp 250-256; Baker, M., The Marketing Book, Oxford, UK, Butterworth-Heinemann, 2003, pp 258-263
- Weinstein & Cahill, Lifestyle Segmentation, 2006, Chapter 4
- Chitty et al, Integrated Marketing Communications, 3rd Asia-Pacific ed., Cengage, pp 83-89 and p. 95; Eunson, B., Communicating in the 21st Century, 2nd ed., Wiley,p. 8.8; Phillip Kotler et al, Marketing Pearson, Australia, 2013, pp 196-7
- Media related to Market segmentation at Wikimedia Commons