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Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
Views of commercial users
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Views of commercial users

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  • 1. Views of Commercial Users Barry Leventhal MRS Census & Geodemographics Group ONS Summer Workshop 24th July 2013
  • 2. Agenda • Introduction – the MRS CGG • How will commercial users be analysing the 2011 Census data? • What kinds of analysis should ONS be producing? • Conclusions 2
  • 3. The MRS Census & Geodemographics Group (CGG) • An advisory board of The Market Research Society • CGG represents the interests of researchers in census and population statistics • Formed in 1989 – has helped to shape the last three censuses, and is now looking beyond 2011 • 20 members from market research agencies, census distributors, targeting consultancies and other commercial users • Websites: – www.mrs.org.uk – www.geodemographics.org.uk – Linkedin Group: MRS Census and Geodemographics Group Network
  • 4. How will commercial users be analysing 2011 Census data? • Continuous use of census data throughout the commercial sector • Applications in research & marketing include: – Geodemographics – Targeting local markets – Targeting customers – Designing market & social research surveys Unashamed plug: CGG Seminar Wednesday 6th November on early use of Census and other open data - further details on MRS website
  • 5. Geodemographics Applications Developed by value added resellers such as...
  • 6. Geodemographic Analysis • Geodemographic classifications, e.g. ACORN, MOSAIC – Applying cluster analysis to small area data • Profiling catchment areas (and customers) – Comparing profiles of target area vs. national profile • Estimating Retail potential – Applying market research estimates to area profiles • Input to further products & services, e.g. site location analysis – regression and gravity models • And other applications of geographical information
  • 7. Targeting Local Markets • Retailers use census data to help make multi-million pound investment decisions, e.g. – Where should new stores be opened? – Which existing outlets should be closed, refurbished or rebranded? – What range of products and services to offer, to meet local needs? – Which local media to employ? – newspapers, posters, radio, leaflets? • Census analysis includes: – Measuring size of catchment area population – Profiling catchment area population by demographics, such as age, social grade, ethnicity, religion, and by geodemographics – Estimating market size - by applying market purchasing rates to catchment area profile
  • 8. Example: Growth in Sainsbury’s store network since release of 2001 Census data March 2003 March 2010 Sainsburys Stores Main Stores Convenience Stores Between 2003 and 2011, Sainsbury’s opened over 450 new stores and extended over 100
  • 9. Targeting Customers • All types of companies with domestic customers use geodemographics as an input to targeting, e.g. – Which customers to target for cross-sell or up-sell? – Which customers are likely to churn? – Which customers should be sent catalogues? – Where to place advertising for gaining new customers? • Geodemographic analysis includes: – Profiling target groups of customers, e.g. churners vs. non-churners – Building and deploying propensity models – Analysing media profiles
  • 10. Designing market & social research surveys • Market researchers use the Census to design, control and enhance sample surveys: – Sample design & execution – Custom analysis, e.g. using Census Microdata – Profiling research data by geodemographics, e.g. products and media – Modelling/integrating Census data with research and customer data
  • 11. Sample Design & Execution • A unique benefit of the Census is availability of demographic information at small area level • Allows analysis/understanding of areas before researching them • Researchers use census data for: – Profiling areas and planning fieldwork – Estimating penetration rates – Stratifying samples – Setting quota targets – Survey weighting
  • 12. Social Grade Approximation for the Census • “ABC1” Social Grade used to be a key omission from the Census for market researchers and other commercial users • Government classifications such as NS-SEC have not been adequate substitutes • MRS CGG has developed a model to derive approximate Social Grade based on Census variables • Model was first built for 2001 Census, redeveloped for 2011 • Social Grade model was implemented by ONS as derived variable • Tables on Approximated Social Grade are included in Census outputs from Release 2 onwards
  • 13. 2011 Social Grade Approximation was built and tested on market research data 13 • Original and Approximation profiles match well for all markets examined • Similar targeting decisions would be made using Approximated Social Grade Source: National Readership Survey
  • 14. Example Results – Approximated Social Grade for Inner London Boroughs 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AB C1 C2 DE 2011 Census: Approximated social grade for local authorities in England and Wales Base: All household reference persons aged 16 to 64 in households Source: Office for National Statistics
  • 15. Integration of Census data with other sources Census small area statistics Census microdata Market Research survey data Customer database information Insights • The value of Census data increases if it can be integrated with other sources • For example, new insights can be created by integrating...
  • 16. Example - Generating small area estimates of demand for “eating out” Market research measurement of eating-out markets Census small area statistics Model demand by demographics Census microdata: estimate counts required for models demand estimates for all areas This method was applied to estimate and map the demand for 7 eating-out markets, at small area level
  • 17. What kinds of Census analysis should ONS be producing? • Data mining – Squeeze out every last drop of value from the Census • Things that users cannot easily do – e.g. Applying user-generated models to Census database • More data visualisation
  • 18. My personal wishlist (1) Modelling further variables onto the Census e.g. Income estimates • Build a model to estimate an individual’s income, on a suitable survey, using demographics available in Census, e.g. age, occupation, region, hours worked • Apply model algorithm to Census database – generate income estimates for individuals and households • Summarise income results down to OA level – Average income levels – Distributions and cross-tabs by income ranges • Benefits: – Approximated income variable, as if collected on Census – Can then examine relationships with other variables • Other census users will require different modelled variables...
  • 19. My personal wishlist (2) Household Segmentation • Develop a household segmentation using either market research data or Census Microdata • Apply segmentation algorithm to Census database • Produce outputs down to OA level – Number of households belonging to each household • Make segmentation algorithm available to users – for application to their own surveys and data sources • Benefits: – Strengthens link between research data and Census – More accurate method of demand estimation than using geodemographics
  • 20. My personal wishlist (3) Profile and model Internet Completion • 16% of census forms were completed online – distribution seems to follow a geographical pattern • Profile Internet vs. non-Internet forms by all standard demographics – develop description of online completers • Build model to predict propensity of online completion • Apply model to other ONS and external surveys • Benefit: – Enables surveys to be targeted or stratified by likelihood of online completion
  • 21. More data visualisation, e.g... • Recent release of postcode-level Census headcounts enables dot mapping within OA’s • Example shows Oxford postcodes coloured by population size • Dot maps would be useful method for visualising population dispersion • See also US Census Dotmap Source: http://opendatareview.wordpress.com
  • 22. Conclusions • Commercial users are continuously analysing Census to underpin research and support investment decisions • ONS should focus on the kinds of analyses that users cannot easily do for themselves, including data mining on the Census database and applying user-generated analytical models • Squeeze out every last drop of value from the Census!
  • 23. Thank you! Dr Barry Leventhal BarryAnalytics Ltd www.barryanalytics.com barry@barryanalytics.com Tel: 020 8905 2634

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