Customer Segmentation in Rochdale Two examples of using Mosaic

1. Customer Segmentation in Rochdale Two examples of using Mosaic Matt France Policy & Research Team Rochdale Council

2. What is customer segmentation? • Customer segmentation is the segmentation of service users/residents into a number of groups, usually with the help of datasets such as Experian’s Mosaic, CACI’s Acorn or ONS’ Output Area Classification. • Customer segmentationhelps to understand different people and their varying needs so that services can be tailored and resources used to best effect. • It is best used in conjunction with local data and local knowledge, and as one tool in a range of customer insight techniques. It’s not the be-all and end-all of customer insight. • We have used segmentation for a number of projects in Rochdale, including using it to help increase the uptake of CTB/HB, and ensuring EY provision meets customer needs….

3. Example 1: Increasing take up of Council Tax and Housing Benefits

4. Overview of the CTB/HB project Aim: to learn about why some of our most deprived households have low take-up rates of council tax and/or housing benefit, and try to increase take up in households that are currently not claiming but are eligible. Method: a range of customer insight tools and techniques were used to form an understanding of current claimants. One of these methods was customer segmentation to find which segments that are eligible to claim are most likely to claim. We contacted these households with a survey asking why they didn’t claim and encouraged them to find out more about claiming. Findings: After contacting customers that fell into the chosen segment, most customers (60%) just did not realise they were eligible to claim and we found lots of confusion around the rules of claiming in a large proportion of the households. Outcomes: Of the households that were contacted and returned the survey, 58% went on to make a successful claim for council tax and/or housing benefit increasing the households available income.

5. Current Claimants Using our internal CTB/HB database (SHBE file) we mapped current claimants at a household level. Current claimants as expected showed strong links to areas of high deprivation. Using Mosaic Household data, segmentation was carried out on current claimants, highlighting the customer type that proportionally had the highest number of household claiming. This took us to type G42 - Families with school age children, living in large social housing estates.

6. Profile of Current Claimants Mosaic gave us key characteristics of type G42, a number of these characteristics made them more eligible for CTB and/or HB: • Type G42 households are on low incomes and are particularly dependant on councils for housing and for transport, the majority of them work in semi skilled, routine jobs which demand few qualifications and offer modest wages. Many of them are unemployed, sick or bringing up children on their own. • These households are very likely to be claiming housing and/or council tax benefit, and are the most likely to eligible if not currently claiming. • Type G42 often pay bills at the Post Office and they are unlikely to pay bills using direct debts. They are also unlikely to visit the local council website or call telephone advice lines, and prefer posters and direct mail to learn about products and services.

7. Contactingthe G42s The majority of type G42 who are not currently claiming CTB and/or HB are located within very close proximity of other G42 households that are claiming. A consultation exercise was carried out to find out why these household were not claiming. We sent out a postal survey (G42s preferred method of communication) to each G42 household in the borough that was not currently claiming CTB and/or HB (3,767 Households) 334 surveys were returned, of these 58% said the main reason for not claiming was due to not knowing they could claim and requested further information on how to claim.

8. Outcome of the CTB/HB project • Of the 334 households that requested more information, 194 (58%) went on to make a successful CTB and/or HB claim. Which meant those households had help to pay rent and/or the council tax bill, resulting in an increase in funds available to the household (to hopefully spend in the borough!) • Using Mosaic give us the opportunity to profile at household level, in the past the Revenues and Benefit service did borough wide mail shots at huge expense. Now they only target households that are likely to able to claim, both reducing costs and increasing customer satisfaction. • From the comments provided via the survey it became apparent that confusion exists around entitlement to claim if working or if you own your own home. Revenues and Benefit service now take this into account when providing information to customers. • Households that potentiality have eligibility to claim (based on customer type) are proactively targeted and provided with more information regarding the eligibility criteria, detailing when you can claim CTB and/or HB and explaining how working and owning their own home affects their eligibility.

9. Example 2: Improving our service offer to early years families

10. Overview of the Early Years project Aim: to learn about our most deprived families in ways that enable us to make changes to services which reflect their needs and behaviours, resulting in an increase in independent access to Children’s Centres. Method: a range of customer insight tools and techniques were used to form a thorough understanding of families with young children. One of these methods was customer segmentation. Findings: a range of findings emerged that enabled tailored intervention. These ranged from insights into the effect of lack of confidence and isolation, to the potential of user-led social media to improve communications. Outcomes: Implementation is in it’s early stages, however it is anticipated that the project will lead to a significant increase in attendance of some of our most deprived families - and subsequently to improved outcomes. Such an increase in attendance is estimated to deliver significant savings, both in the operational costs and in the longer term through preventative work.

11. Overview of the Early Years project Aim: to learn about our most deprived families in ways that enable us to make changes to services which reflect their needs and behaviours, resulting in an increase in independent access to Children’s Centres. Method: a range of customer insight tools and techniques were used to form a thorough understanding of families with young children. One of these methods was customer segmentation. Findings: a range of findings emerged that enabled tailored intervention. These ranged from insights into the effect of lack of confidence and isolation, to the potential of user-led social media to improve communications. Outcomes: Implementation is in it’s early stages, however it is anticipated that the project will lead to a significant increase in attendance of some of our most deprived families - and subsequently to improved outcomes. Such an increase in attendance is estimated to deliver significant savings, both in the operational costs and in the longer term through preventative work.

12. Rochdale Borough Mosaic Types • 87,900 households = 10 groups and 45 different types • Top ten most common types account for 49,000 households but only 56% all households • Large variation of groups/types in top ten • Customer needs, characteristics and deprivation levels vary massively even within top 10

13. Refining segments • Mosaic household level data was used to develop a bespoke segmentation. • The segmentation was based upon two household characteristics: deprivation and service need. • Five broad segments were created; a manageable number for strategic work. • Each broad segment is made up of a number of more detailed and specific types – these are still available to refer to when more detailed insight is required. • Segmentation available at household, postcode or LSOA level.

14. Segmentation in the EY project • Before embarking on primary research, customer segmentation was used to build up an initial picture of the families we wanted to learn more about. • Gave us insight into the potential issues families may be facing. • Enabled us to set up appropriate primary research by targeting the correct type of families.

15. D24: Low income families living in cramped Victorian terraced housing in inner city locations – 8,178 Households (9.3%) Type 1 GENERAL Index of Multiple Deprivation 2007: average level of deprivation for type TOP 6 Likely Service Use (ESD toolkit) • Council tax: individual account enquiries • Libraries: general infromation • Welfare rights - benefits - advice and assessment • Refuse: household waste collection • Housing: general information and advice • Transport: journey planning • Key locations: • North East Middleton • North Heywood • Central Rochdale • North Castleton KEY ISSUES • High • Above average • Average • Below Average • Low COMMS

16. Segmentation in the EY project • Connected segmentation data to administrative data. • Household level segmentation available from some providers (we used Mosaic). • Gave us a quantitative understanding of service use patterns. • Will help us measure change.

17. Segmentation in the EY project • Analysed the customer base of the Children’s Centres. • Helped us target a range of centres for further research. • Gave us insight into travel patterns

18. Outputs from segmentation • The segmentation approach along with wider customer insight methods is being rolled out to other areas of work, via the development of a CI strategy • it doesn’t always have to be accompanied by primary research, but we think it’s most robust when it is.

19. Outputs from segmentation • Developing a Greater Manchester wide approach.

20. Contribution of segmentation • Segmentation allowed us to target our primary research at key groups and ask more informed questions from the outset. • E.g. findings around isolation, transience and confidence. • Attaching administrative data to household level segmentation data allowed us to see the different patterns and outcomes of different segments. • This information enabled us to see if centres were attracting the most in-need families from their local communities. • Quantifying access by segments will allow us to evaluate the success of interventions aimed at increasing access in target groups. • Combining segmentation with primary research helped us to further refine segments for future work.

21. Segmentation Resources Resources • Cabinet Office guide to segmentation including how to do it, case studies and a toolkit: http://webarchive.nationalarchives.gov.uk/+/http://www.cabinetoffice.gov.uk/public_service_reform/innovation/segmentation.aspx • Output Area Classification (OAC) user group:http://areaclassification.org.uk/ • Experian Mosaic Public Sector: http://publicsector.experian.co.uk/Products/Mosaic%20Public%20Sector.aspx • CACI Acorn/InSite:http://www.caci.co.uk/CustomerTarget.aspx Contact *Research@rochdale.gov.uk • 01706 924302 • www.statsandmaps.org.uk