Geodemographic segmentation

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In marketing, geodemographic segmentation is a multivariate statistical classification technique for discovering whether the individuals of a population fall into different groups by making quantitative comparisons of multiple characteristics with the assumption that the differences within any group should be less than the differences between groups.

Contents

Principles

Geodemographic segmentation is based on two simple principles:

Clustering algorithms

The use of different algorithms leads to different results, but there is no single best approach for selecting the best algorithm, just as no algorithm offers any theoretical proof of its certainty. [1] One of the most frequently used techniques in geodemographic segmentation is the widely known k-means clustering algorithm. In fact most of the current commercial geodemographic systems are based on a k-means algorithm. Still, clustering techniques coming from artificial neural networks, genetic algorithms, or fuzzy logic are more efficient within large, multidimensional databases (Brimicombe 2007).

Neural networks can handle non-linear relationships, are robust to noise and exhibit a high degree of automation. They do not assume any hypotheses regarding the nature or distribution of the data and they provide valuable assistance in handling problems of a geographical nature that, to date, have been impossible to solve. One of the best known and most efficient neural network methods for achieving unsupervised clustering is the Self-Organizing Map (SOM). SOM has been proposed as an improvement over the k-means method, for it provides a more flexible approach to census data clustering. The SOM method has been recently used by Spielman and Thill (2008) to develop geodemographic clustering of a census dataset concerning New York City.

Another way of characterizing an individual polygon's similarity to all the regions is based on fuzzy logic. The basic concept of fuzzy clustering is that an object may belong to more than one cluster. In binary logic, the set is limited by the binary yes–no definition, meaning that an object either belongs or does not belong to a cluster. Fuzzy clustering allows a spatial unit to belong to more than one cluster with varying membership values. Most studies concerning geodemographic analysis and fuzzy logic employ the Fuzzy C-Means algorithm and the Gustafson-Kessel algorithm, [1] (Feng and Flowerdew 1999).

Systems

Famous geodemographic segmentation systems are Claritas Prizm (US), CanaCode Lifestyles (Canada), PSYTE HD (Canada), Tapestry (US), CAMEO (UK), ACORN (UK), and MOSAIC (UK). New systems targeting population subgroups are also emerging. For example, Segmentos examines the geodemographic lifestyles of Hispanics in the United States. Both MOSAIC and ACORN use Onomastics to infer the ethnicity from resident names. [2] [3]

CanaCode Lifestyle Clusters

CanaCode Lifestyle Clusters is developed by Manifold Data Mining and classifies Canadian postal codes into 18 distinct major lifestyle groups and 110 niche lifestyles. [4] It uses current-year statistics on over 10,000 variables ranging from demographics to socioeconomic factors to expenditures to lifestyle traits (e.g. consumer behaviors) including product usage, media usage, and psychographics.

PSYTE HD

PSYTE HD Canada [5] is a geodemographic market segmentation system that classifies Canadian postal codes and Dissemination Areas into 57 unique lifestyle groups and mutually exclusive neighborhood types. PSYTE HD Canada is built on the Canadian Census demographic and socioeconomic base in addition to various other third party data inputs combined in a state of the art cluster build environment. The resultant clusters represent the most accurate snapshots of Canadian neighborhoods available. PSYTE HD Canada is an effective tool for analyzing customer data and potential markets, gaining market intelligence and insight, and interpreting consumer behavior across the diverse Canadian marketplace.

CAMEO system

The CAMEO Classifications are a set of consumer classifications that are used internationally by organisations as part of their sales, marketing and network planning strategies.

CAMEO UK has been built at postcode, household and individual level and classifies over 50 million British consumers. It has been built to accurately segment the British market into 68 distinct neighbourhood types and 10 key marketing segments.

Internationally Global CAMEO is the largest consumer segmentation system in the world, covering 40 nations. There is also single global classification CAMEO International which segments across borders.

CAMEO was developed and is maintained by Callcredit Information Group.

Acorn system

A Classification Of Residential Neighborhoods (Acorn) is developed by CACI in London. It is the only geodemographic tool currently available that is built using current year data rather than 2011 Census information. Acorn helps to analyse and understand consumers in order to increase engagement with customers and service users to deliver strategies across all channels. Acorn segments all 1.9 million UK postcodes into 6 categories, 18 groups and 62 types.

MOSAIC system

Mosaic UK is Experian's people classification system. Originally created by Prof Richard Webber (visiting Professor of Geography at Kings College University, London) in association with Experian. The latest version of Mosaic was released in 2009. It classifies the UK population into 15 main socio-economic groups and, within this, 66 [6] different types.

Mosaic UK is part of a family of Mosaic classifications that covers 29 countries including most of Western Europe, the United States, Australia and the Far East.

Mosaic Global is Experian's global consumer classification tool. It is based on the simple proposition that the world's cities share common patterns of residential segregation. Mosaic Global is a consistent segmentation system that covers over 400 million of the world's households using local data from 29 countries. It has identified 10 types of residential neighbourhood that can be found in each of the countries.

geoSmart system

In Australia, geoSmart is a geodemographic segmentation system based on the principle that people with similar demographic profiles and lifestyles tend to live near each other. It is developed by an Australian supplier of geodemographic solutions, RDA Research.

geoSmart geodemographic segments are produced from the Australian Census (Australian Bureau of Statistics) demographic measures and modeled characteristics, and the system is updated for recent household growth. The clustering creates a single segment code that is represented by a descriptive statement or a thumbnail sketch.

In Australia, geoSmart is mainly used for database segmentation, customer acquisition, trade area profiling and letterbox targeting, although it can be used in a broad range of other applications.

The Output Area Classification

The Output Area Classification (OAC) is the UK Office for National Statistics' (ONS) free and open geodemographic segmentation based upon the UK Census of Population 2011. It classifies 41 census variables into a three-tier classification of 7, 21, and 52 groups.

The perceived advantages of OAC over other commercial classifications stem from the fact that the methodology is open and documented, and that the data is open and freely available to both the public and commercial organizations, subject to licensing conditions.

OAC has a wide variety of potential applications, from geographic analysis to social marketing and consumer profiling. The UK public sector is one of the main users of OAC.

ESRI Community Tapestry

This method classifies US neighborhoods into 67 market segments, based on socioeconomic and demographic factors, then consolidates these 67 segments into 14 types of LifeModes with names such as "High Society", "Senior Styles", and "Factories and Farms". [7] The smallest spatial granularity of data is produced at the level of the U.S. Census Block Group.

See also Market segmentation#Companies (proprietary segmentation databases)

Related Research Articles

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<span class="mw-page-title-main">Image segmentation</span> Partitioning a digital image into segments

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<span class="mw-page-title-main">Cluster analysis</span> Grouping a set of objects by similarity

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.

Mosaic is Experian's system for geodemographic classification of households. It applies the principles of geodemography to consumer household and individual data collated from a number of government and commercial sources. The statistical development of the system was led by professor Richard Webber in association with Experian in the 1980s, and it has been regularly refreshed and reclassified since then, each based on more recent data from national censuses and other sources. Since its initial development in the UK, the Mosaic brand name has also been used to market separate products which classify other national consumers including most of Western Europe, USA, selected Asian regions and Australia.

Geodemography is the study of people based on where they live; it links the sciences of demography, the study of human population dynamics, and geography, the study of the locational and spatial variation of both physical and human phenomena on Earth, along with sociology. It includes the application of geodemographic classifications for business, social research and public policy but has a parallel history in academic research seeking to understand the processes by which settlements evolve and neighborhoods are formed. Geodemographic systems estimate the most probable characteristics of people based on the pooled profile of all people living in a small area near a particular address.

Psychographics is defined as "market research or statistics classifying population groups according to psychological variables" The term psychographics is derived from the words “psychological” and “demographics” Two common approaches to psychographics include analysis of consumers' activities, interests, and opinions, and values and lifestyles (VALS).

Acorn (demographics) Geodemographic information system categorising some UK postcodes

Acorn, developed by CACI Limited in London, is a segmentation tool which categorises the United Kingdom’s population into demographic types. It has been built by analysing social factors and behaviour. Acorn segments households, postcodes and neighbourhoods into six categories, 18 groups and 62 types.

The target audience is the intended audience or readership of a publication, advertisement, or other message catered specifically to the previously intended audience. In marketing and advertising, the target audience is a particular group of consumer within the predetermined target market, identified as the targets or recipients for a particular advertisement or message.

The following outline is provided as an overview of and topical guide to marketing:

Technographic segmentation for marketing management is a market research analysis tool used to identify and profile the characteristics and behaviors of consumers through the process of market segmentation. Traditionally market researchers focused on various demographic, psychographic, and lifestyle schemes to categorize and describe homogeneous clusters of consumers that comprise possible target markets.

Micromarketing was first referred to in the UK marketing press in November 1988 in respect of the application of geodemographics to consumer marketing. The subject of micromarketing was developed further in an article in February 1990, which emphasised understanding markets at the local level, and also the personalisation of messages to individual consumers in the context direct marketing. Micromarketing has come to refer to marketing strategies which are variously customised to either local markets, to different market segments, or to the individual customer.

A target market, also known as serviceable obtainable market (SOM), is a group of customers within a business's serviceable available market at which a business aims its marketing efforts and resources. A target market is a subset of the total market for a product or service.

Claritas PRIZM Premier is a set of geo-demographic segments for the United States, developed by Claritas Inc., which was owned under The Nielsen Company umbrella from 2009 to 2016.

Firmographics are sets of characteristics to segment prospect organizations.

In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis.

In business intelligence, data classification is "the construction of some kind of a method for making judgments for a continuing sequence of cases, where each new case must be assigned to one of pre-defined classes."

Precision marketing is a marketing technique that suggests successful marketing is to retain, cross-sell, and upsell existing customers.

The fields of marketing and artificial intelligence converge in systems which assist in areas such as market forecasting, and automation of processes and decision making, along with increased efficiency of tasks which would usually be performed by humans. The science behind these systems can be explained through neural networks and expert systems, computer programs that process input and provide valuable output for marketers.

Psychographic segmentation has been used in marketing research as a form of market segmentation which divides consumers into sub-groups based on shared psychological characteristics, including subconscious or conscious beliefs, motivations, and priorities to explain and predict consumer behavior. Developed in the 1970s, it applies behavioral and social sciences to explore to understand consumers’ decision-making processes, consumer attitudes, values, personalities, lifestyles, and communication preferences. It complements demographic and socioeconomic segmentation, and enables marketers to target audiences with messaging to market brands, products or services. Some consider lifestyle segmentation to be interchangeable with psychographic segmentation, marketing experts argue that lifestyle relates specifically to overt behaviors while psychographics relate to consumers' cognitive style, which is based on their "patterns of thinking, feeling and perceiving".

Manifold Data Mining Inc. is a Canadian company specializing in consumer data products, analytics, and predictive modeling. As a data and analytical service provider in Canada, they have been providing businesses, charities, and governmental organizations with comprehensive data products since being founded in 2001. For each neighbourhood, they provide estimates of what products consumers buy, where and how often they shop, how much they spend, which media channels they use, their lifestyles, and their attitudes or psychographics.

References

  1. 1 2 Grekousis, George; Thomas, Hatzichristos (2012). "Comparison of two fuzzy algorithms in geodemographic segmentation analysis: The Fuzzy C-Means and Gustafson–Kessel methods". Applied Geography. 34: 125–136. doi:10.1016/j.apgeog.2011.11.004.
  2. ↑ "Using Intelligent Systems to infer ethnicity from names, Richard Webber, UCL 2006".
  3. ↑ "Onomastics for business: can discrimination help development? - Paris Innovation Review". www.paristechreview.com.
  4. ↑ "Consumer Lifestyle Clusters | Manifold Data Mining" . Retrieved 2020-11-12.
  5. ↑ Market segmentation system for Canada PSYTE HD Canada
  6. ↑ Experian. "Segmentation". www.segmentationportal.com.
  7. ↑ "Esri Data - Current Year Demographic & Business Data - Estimates & Projections". www.esri.com.
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