Using geo-demographic classifications for Customer Insight

www.worcestershire.gov.uk

Using geo-demographic classifications for Customer Insight

Andrew RuddResearch Manager

Miranda WebbResearch Officer

Worcestershire County CouncilResearch and Intelligence Unit


Contents

• Research and Intelligence Unit• About Worcestershire• What is Customer Insight?• Worcestershire Hub• Key Findings and Results• Practical Applications• Conclusion


Worcestershire's Research and Intelligence Unit• Market Research (inc Customer Insight)• Housing• Economy• Performance Monitoring• Supporting People• Community Safety • Population/Demographics• Partnership work e.g. JSNA


About Worcestershire

4

Worcestershire:

•Population: 556,548 (ONS 2009)

•Ageing population: 19% of population 65+ years

•4% population claiming Job Seekers Allowance July 2010

•71% of the population live in large towns or cities


About Worcestershire

5

Worcestershire:

Supergroup

Total Population

(2001 Census)

% of Worcestershire

Blue Collar Communities 84,251 15.5City Living 8,542 1.6Countryside 127,562 23.5Prospering Suburbs 165,838 30.6Constrained by Circumstance 50,178 9.3Typical Traits 100,207 18.5Multicultural 5,529 1.0Grand Total 542,107 100.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Blue Collar Communities

City Living Countryside Prospering Suburbs

Constrained by

Circumstance

Typical Traits Multicultural%

of P

opul

ation

(Ce

nsus

200

1)

OAC Supergroup

Worcestershires Population by OAC %

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Blue Collar Communities

City Living Countryside Prospering Suburbs

Constrained by

Circumstance

Typical Traits Multicultural

% o

f Pop

ulati

on (

Cens

us 2

001)

OAC Supergroup

Worcestershire Population by OAC %


What is Customer Insight?• Improve outcomes and services based on understanding of

customers:• needs• wants• expectations• behaviours• experiences

• Starts with knowing and understanding what customers want

• Ends with improved satisfaction with your organisation, and services being delivered in a more efficient way

6


Meet our customers

7[Slideshow Title - edit in Headers & Footers]

Person X Partner

2 little X’s

Person X:

•Skilled manual worker•Lives in a house with a mortgage•Sends children to local school•Makes use of the local library•Drives a family car


Our customers needs

8

Person X Needs…•To pay Council Tax

•Refuse and waste collected

•Information about school term times

•Advice about claiming benefits

•Information about library renewals

•Roads in good condition

Person X Partner

2 little X’s


Our customers preferences

9

Person X is likely to….

•Shop at Morrisons

•Read the Express or Mail

•Like to use email or phone channels

Person X Partner

2 little X’s


What our customers think


Person X thinks that…..

Most important•Employment prospects•Low crime

Most needs improving•Activities for children•Refuse and waste collection

Satisfaction with Local Govt•Neither satisfied nor dissatisfied

Person X Partner

2 little X’s


Meet our customers


Person Y Person Y:

•Retired

•Lives in the countryside

•Rents house from social landlord

•Does not drive

•Occasionally uses the local library


Our customers needs

12

Person Y needs…

•Information about local services

•Timetables for public transport

•Council Tax relief

•Library access

•Application form for Concessionary Fares

•Advice about Blue Badges

Person Y


Our customers preferences


Person Y is likely to…

•Shop in Co-op or Asda

•Attend social clubs

•Prefer ‘to talk to someone’ when contacting a service

Person Y


What our customers think


Person Y thinks that…

Most important•Access to services•Low crime

Most needs improving•Local transport•Refuse and waste collection

Satisfaction with Local Govt•Fairly satisfied

Person Y


Our services


Who uses our libraries?


Configuring our service

• 600 calls about library opening times per quarter• Many library users would prefer electronic

communication• Make information available via website and

email• Promote through material in libraries and during

telephone and face-to-face contact• Reduces time spent by Customer Service

Assistants

16


Savings

17

8.2

4.63.2

0.40123456789

Face to Face Post Phone Self Serve via website

App

roxi

mat

e Co

st (£

)

Channel

Cost to Serve by Channel

Costs from SOCITM and ESD toolkit


We have lots of different customers

18


...and provide lots of different services


Refuse and Waste

Highways

Benefits

Concessionary Fares

Blue Badge

Council Tax

Housing

Social Services

Environmental Health

Street Scene

Car Parking

Education

Registration Services

Parks and Open Spaces

Development Control


Match service configuration...with customer needs...and preferences...to get improved satisfaction



Why are we doing this?

• Economic situation• Reduced public-sector funding

• Do more with fewer resources• Make better use of data

• Improve service delivery/customer satisfaction

• Councillor engagement • Keep Elected Members informed about their local

communities


Worcestershire Hub

• WCC Customer Relationship Management system (OneServe) • Partnership between WCC and Local Authorities

• Information about service use by individuals

• Information about method of contact

• Location given by customer postcode

• Allows analysis of service use using geo-demographic tools e.g. ACORN, OAC

• We use both in this presentation

22


Key Findings, Quarter One, 2010

• After cleaning, files contained:

• 38,860 Unique Customers

• 53,238 Unique Incidents

• Average of 1.3 Incidents per Customer

• Approximately 20% more incidents than in Q4 2009


Results, Q1 2010


Service use, Q1 2010

25


Service use, Q1 2010

26


27

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% o

f Con

tact

Acorn Category

Origin of Contact by Acorn

Internet

Letter

E-mail

Personal Visit

Phone


28

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% o

f Con

tact

OAC Supergroup

Origin of Contact by OAC

Internet

Letter

E-mail

Personal Visit

Phone


Channel preferences

• Email/Website: Urban Prosperity, Wealthy Achievers, Comfortably Off

• Letter/Post: Hard Pressed, Moderate Means, Comfortably Off

• Personal Visit: Hard Pressed, Moderate Means• Phone: Hard Pressed and Comfortably Off, Moderate

Means• Text: Hard-Pressed, Moderate Means, Urban

Prosperity

29


Application: Promoting self-service• Changing the ways people contact the council

• Use channels customers most receptive to

• e.g. Libraries• 4,500 telephone and face-to-face enquiries per month• Many customers would use electronic channels• Alternative channels promoted during contact and

promotional material

• Savings• Self serve is a lower cost channel – where appropriate• Will not be suitable for all services

30


Application: Service Improvement• Missed Bins

• Identify where refuse collections are missed most often • Customers least likely to be satisfied with service

• Analysis:• Incidents mapped• Highlighted areas with recurring requests• Identified any special circumstances (i.e. snow)• Target focused areas for service improvement

• Savings• Fewer repeat journeys to collect ‘missed’ refuse• Fewer customers reporting missed bins



© Crown copyright. All rights reserved. Worcestershire County Council 100015914. For reference purposes only. No further copies may be made.

Selected Postcode:


Application: Informing Councillors • Electoral Division information

• Inform Councillors about needs of their communities• Councillors able to represent communities more effectively• Updated quarterly

• Area Profiles

• Postcode maps

• Savings• Councillors more proactive in resolving community issues• Fewer contacts from customers

34


35




Conclusions• Understanding customers allows better targeting of

resources, thereby reducing costs of service delivery = efficiency savings

• Geo-demographic tools help develop this understanding

• Can lead to improved satisfaction amongst customers• Demonstrates effective use of existing data• Relies on good quality location data and effective

partnership working• Many potential applications


Contact details

Andrew RuddResearch Manager

[email protected]

Miranda WebbResearch Officer

[email protected] 822026

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Using geo-demographic classifications for Customer Insight

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