Mosaic Public Sector An introduction

Agenda Mosaic – very brief oversimplified history Data sources Mosaic Types and Groups Customer insight / Interactive Guide Profiling a customer file Mosaic Grand Index Targeting Case studies

Experian & Mosaic GUS mail order catalogue CCN (Credit Control Nottingham) Electoral Rolls / CCJ records etc. More data sources added and use extended beyond credit control to direct marketing Prof. Richard Webber (ex CACI) developed Mosaic in 1980 CCN acquired US credit records company Experian in 1996

What is Mosaic? Primarily a marketing segmentation and targeting tool that: –segments the UK adult population into a number of different ‘like minded’ groups –provides insight into how likely it is that certain attributes and values are held by each segment –informs decisions about how best to tailor and deliver messages to them –codes every postcode and residential address to facilitate targeting Micro Marketer GIS package optional –mapping / drive times etc.

Types of data in Mosaic Small area census and updates / PAF ‘Factual’ from ‘official’ sources –Electoral Rolls / CCJs / Council Tax / Property sales / Birth notifications / Company Directors / Health data etc. Transactional Data –Anonymised credit searches, activity & risk scores / motor vehicle & insurance databases / utility companies Modelled data –Age estimates / Mosaic origins

Age estimates Track people coming of voting age over time at same address Exempt from jury service Similar model to Mosaic Origins for predicting age group

Mosaic Origins Classifies people according to the part of the world from which their forebears are most likely to have originated. Every person is placed into one of 243 Origins Types, which may be grouped by type of name, religion, language or geography. Database contains 1.25m family names and >480k personal names

Mosaic Origins profile of East Shipley (Target) compared to the Yorkshire and Humber region (Base)

There is a large Pakistani community West of East Shipley

This shows the ethnic distribution without English, Irish and Celtic names

Target Group Index (TGI) Representative sample of around 25,000 British adults annually with the data released quarterly. Questions cover consumer attitudes, motivations, media habits and purchase behaviour. (Includes lifestyle questions) Single source survey - respondents fill out entire questionnaire covering all question areas so any variable can be cross-tabbed with any other variable Respondents coded by all major geodemographic systems including Mosaic, Acorn, Superprofiles etc. Some insight data included in Mosaic Used extensively by advertisers, media owners and agencies. e.g. Crosstab consumers of particular products or services with media consumption or TV viewing

Mosaic Data 440 Data Elements62% Experian Consumer Dynamic Database 38% Census CYE

Cluster analysis Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters

Mosaic variants MOSAIC UK Financial Grocery Automotive Public Sector Scotland Northern Ireland Global

Household level segmentation Public Sector specific 15 Groups, 69 Types, 146 Person types Accurate, contemporary and up to date Refreshed every six months Mosaic Public Sector

15 Mosaic Public Sector Groups GroupGroup Name A Residents of isolated rural communities B Residents of small and mid-sized towns with strong local roots C Wealthy people living in the most sought after neighbourhoods D Successful professionals living in suburban or semi-rural homes E Middle income families living in moderate suburban semis F Couples with young children in comfortable modern housing G Young, well-educated city dwellers H Couples and young singles in small modern starter homes I Lower income workers in urban terraces in often diverse areas J Owner occupiers in older-style housing in ex-industrial areas K Residents with sufficient incomes in right-to-buy social houses L Active elderly people living in pleasant retirement locations M Elderly people reliant on state support N Young people renting flats in high density social housing O Families in low-rise social housing with high levels of benefit need

69 Mosaic Public Sector Types

Mosaic Public Sector

Using Mosaic 1.Preparing postcode file for profiling Use comma separated text file Note: saving from Excel can generate spurious blank records that get reported as unmatched records Best to copy and paste to WordPad and shift/ctrl/end and remove any blank lines before saving

Profiling sample size 500 minimum for Group level 1,000 minimum for Type level A smaller sample size may be OK if profiling produces a small number of Groups or Types with high indices If no suitable sample available the Mosaic Grand Index may provide proxies

Need to consider the best base

Ward Profiles (Base Bradford District)

Ward Profiles (Base UK Households)

Ward Profiles (Base Bradford District)

Ward Profiles (Base UK Households)

Mosaic Grand Index

Mosaic ‘Targets’

Mosaic Directory CSV File – 210,741 rows All Bradford District residential addresses coded with Mosaic Type and Group 2 sets of Mosaic codes –household level –postcode level Link variable added to Gazetteer

Mosaic ‘Database’

Reaching target types Address / postcode will tell us where the target types are located Mosaic can inform channel choice and creative message

Communication Channels Example

Location Planning Plotting postcodes of ‘target’ Mosaic types can inform location planning, e.g. libraries, advice centres etc. Can also identify best place for mobile resources to visit

Children and Young People’s Services - Poverty in North Warwickshire County Council, CAB, Credit Union and others Branch Out Bus Benefit and free school meal data Mosaic to identify target households 97% satisfaction 88% would not have contacted Council or CAB Benefits, debt, redundancy etc

Case studies

Possible uses for Mosaic Benefit take-up –Profile claimants and design campaign to target dominant Mosaic types not claiming benefits to encourage them to apply Switch Council Tax payers to Direct Debit –Profile non-DD and target the types most likely to be receptive to paying by DD Council Tax arrears –Profile non-payers and target those most likely to have the ability to pay

Designing the creative message What are target types interested in? What’s their attitudes and opinions? What type of language is most suitable?

Stoke on Trent – Fly tipping Fly tipping a particular high cost problem By combining Mosaic data with the indices of deprivation and indicators of fly-tipping/street cleanliness, the Council identified specific areas where incidents were high and the make-up of the nearby population. One example showed Mosaic types 23 and 44 were likely to be responsible Both types have very little concern for the environment and are most receptive to marketing from television and tabloid newspapers, i.e. less receptive to local media Clearly this presented a challenge to the Council’s traditional methods of communication.

Stoke on Trent – Fly tipping However, Mosaic identified a similarity in both types in their use of local shops and bars, and that these locations should be targeted for marketing, e.g. leaflets and posters. Similarly, neither would be particularly responsive to messages that stressed the criminality of fly tipping, but given both types’ tendency to support pet charities, stressing the potential health hazard to animals from fly tipping would be likely to yield more results.