Customer Insight Analysis

What do we know about our customers?Customer Insight Analysis

Voluntas Customer Conference 15th November 2012

Paul Ryall-FriendHead of Customer Experience

v 1.0

At a glance

• We are the largest social landlord in the Bath area providing 12,000 homes• We are a major local provider of older people's services• We provide homes and support services to general social housing residents, young people and teenage parents, older people in sheltered housing, homeless people, shared owners and leaseholders• We provide services to other housing associations• We let private market-rented properties• We have developed more than 1,700 homes since 2002 and are due to complete 1,473 homes by 2016• We have a foyer where, in addition to accommodation, we provide training for young people

Our priorities

We have set ourselves six priorities:

• Creating a renowned customer service culture• Owning great properties and places• Setting up an ethical care and support business• Working for happy, safe, popular neighbourhoods• Helping people who need work• Lobbying for positive social change

Who are we?

Customer Insight? - What we used to do…..

Method and approach

• The customer feedback process provided us with a snapshot view about how customers felt

• Feedback mechanisms included an event triggered customer satisfaction survey, customer complaints, compliments and documented reasons as to why customers refuse planned maintenance work

• Other feedback came direct from the resident involvement framework

• This data was not held centrally within our business and therefore we lacked a repository of customer feedback that could be used to explore broad trends or shifts in customer opinion, views and requirements

• The current feedback data capture process was neither rigorous nor consistent and data analysis had been extremely limited

• Information held was of varying quality across the different teams and it was not clear how this information was analysed, interpreted or shared

• We had stopped surveying customers once they have been through the complaint handling process – we don’t know how customers perceive our ability to manage complaints

• Voluntas have been contracted to deliver our customer satisfaction feedback survey through to 31st December 2012

‘Outside-In’ processes &

Right First Time

Effective Customer Contact

Management

Maximum Customer Loyalty

& Minimum Customer Effort

Customer Experience Strategy - Maximise Customer Loyalty / Minimise Customer Effort

Customer Feedback

Customer Insight

Business Improvement

Activity

• Do what we say we will• Do it when we say we will• ‘I’ can do it

• Respond to individual customer needs and preferences• Multi-channel access and customer choice• Consistent

• NPS• Effort

Sources of Satisfaction- What we do well- Drivers of satisfaction- Do more of / continue doing / do less of- Compliments

Sources of Dissatisfaction

Complaint root cause analysis -Reduce process

error, risk waste -

Prioritise and agree action -

Customer Profile

Inputs Insight Outputs

Feedback UnderstandingPriorities for

change

Survey data

SurveySurvey

Com

plai

nts

Dat

a

Refusals data

Neighbou

rhoo

d

com

men

ts

Compliments

data in one place

Survey mechanism

• Survey construction• Survey channel maintenance• Data sample governance• MI & Reporting

• Automate data sample generation and feed• Relationship with survey provider(s)• Owner of customer feedback data

• Performance – Effort/NPS• Drivers – correlation / regression / verbatim• Importance to customer• Root Cause Analysis (RCA)• Mystery shopping

share & inform

Insight

• do more of / continue doing / do less of• Sources of satisfaction & dissatisfaction• Market research & benchmarking• Customer Profiling

Business Improvement

Activity

• Share insight, knowledge and understanding• Reduce process errors, risk and waste• Reduce complaints• Lever and increase drivers of satisfaction and advocacy• Measure and monitor benefits

Curo Customer Insight – ‘to be’ process

How to Calculate our Net Promoter Score

NPS is based on the fundamental perspective that every company's customers can be divided into three categories: Promoters, Passives, and Detractors. By asking one simple question — How likely is it that you would recommend Curo to a friend or colleague? — you can track these groups and get a clear measure of Curo’s performance through its customers' eyes. Customers respond on a 0-to-10 point rating scale and are categorized as follows:

•Promoters (score 9-10) are loyal enthusiasts who will keep buying and refer others, fuelling growth.•Passives (score 7-8) are satisfied but unenthusiastic customers who are vulnerable to competitive offerings.•Detractors (score 0-6) are unhappy customers who can damage your brand and impede growth through negative word-of-mouth.

To calculate Curo Net Promoter Score (NPS), we take the percentage of customers who are Promoters and subtract the percentage who are Detractors.

Customer Insight – Net Promoter Score (NPS)

How likely would you be to recommend Curo Housing to family or friends?


Net Promoter EconomicsPromoters and Detractors exhibit dramatically different behaviours and produce dramatically different economic results. Several factors distinguish Detractors from Promoters — explaining why it is so compelling for companies to increase the number of Promoters and decrease the number of Detractors in their business.

Retention Rate: Detractors generally defect at higher rates than Promoters, which means that they have shorter and less profitable relationships with a company.

Margins: Promoters are usually less price-sensitive than other customers because they believe they are getting good value overall from the company. The opposite is true for Detractors: they're more price-sensitive.

Annual Spend: Promoters increase their purchases more rapidly than Detractors. They tend to consolidate more of their category purchases with their favourite supplier. Promoters' interest in new product offerings and brand extensions exceeds that of Detractors or Passives.

Cost Efficiencies: Detractors complain more frequently, thereby consuming customer-service resources. Some companies also find that credit losses are higher for Detractors. (Perhaps that is how the Detractors extract revenge.) By contrast, Promoters help bring down your customer-acquisition costs by staying longer and helping to generate new referrals.

Word-of-Mouth: Quantify the proportion of new customers who selected your firm because of reputation or referral. The lifetime value of these new customers, including any savings in sales or marketing expense, should be allocated to Promoters. Between 80 and 90% of positive referrals come from Promoters. Detractors, meanwhile, are responsible for 80 to 90% of the negative word-of-mouth, and the cost of this drag on growth should be allocated to them.

How to Improve Our ScoreA company's Net Promoter Score (NPS) helps corporate leaders define their companies' real mission and hold their people accountable for building great customer relationships — the only path to prosperity and true growth.

"Act Upon" the Three Groups of CustomersGrouping customers into these three clusters — Promoters, Passives, and Detractors — provides a simple, intuitive scheme that accurately predicts customer behaviour. Most important, it's a scheme that can be acted upon. Frontline managers can grasp the idea of increasing the number of Promoters and reducing the number of Detractors a lot more readily than the idea of raising the customer satisfaction index by one standard deviation.


NPS Leaders – US 2012 NPS Leaders – UK 2012

USAA Banking 83 Apple I-phone 69

Amazon.com 76 First Direct – Banking 62

USSA – Auto Ins. 74 Apple hardware 59

Trader Joe’s - Grocery 73 Tesco Mobile 47

Costco / Apple USAA (Homeowners Ins)

71 Simply Health 29

*

* United Services Automobile Association

*

2011 UK Net Promoter Industry benchmarks

Industry Avg. Best Worst

Banking 0 61 -34

Car Insurance -6 14 -

Home Insurance -20 -8 -38

Utilities -35 -19 -55

† †

†

*

† Satmetrix 2012 US Net Promoter Benchmark / Satmetrix 2012 European Net Promoter Benchmark

Voluntas Customer Satisfaction – Rated By Residents Survey

Re-Lets Responsive Repairs

Planned Works

Gas Servicing

600 pa (50 pm)

900 pa (75 pm)

900 pa (75 pm)

840 pa (70 pm)

Monthly data

sample

Fortnightly data

sample

Monthly data

sample

18 Qs 20 Qs 20 Qs 25 Qs

Fortnightly data

sample

Customer Satisfaction Service Area Target Aug July June3 months

to Aug3 months

to July3 months to June

How satisfied or dissatisfied are you with the service provided by Curo Housing Group – LETTINGS

Curo Group 95% 100% 96% 100% 97.53% 95% 94%

How likely would you be to recommend Curo Housing to family or friends - LETTINGS (Net Promoter Score)

Curo Group TBD 40.74% 48% n/a 45.43% n/a n/a

How satisfied or dissatisfied are you with the service provided by Curo Housing Group – REPAIRS

Curo Group 95% 96% 94.74% 96% 95.57% 95.12% 95.4%

How likely would you be to recommend Curo Housing to family or friends – REPAIRS (NPS)

Curo Group TBD 46.67% 47.36% n/a 47.40% n/a n/a

How satisfied or dissatisfied are you with the service provided by Curo Housing Group – GAS SERVICING

Curo Group 95% 89.13% 96% 96% 94.38% 96.11% 95.10%

How likely would you be to recommend Curo Housing to family or friends – GAS SERVCING (NPS)


How satisfied or dissatisfied are you with the services provided by Curo Housing Group – PLANNED WORKS

Curo Group 95% 100% 94.74% 100% 98.36% 95.99% 96.2%

How likely would you be to recommend Curo Housing to family or friends – PLANNED WORKS (NPS)


How satisfied or dissatisfied are you with the service provided by Curo Housing Group – ALL combined

Curo Group 95% 95.12% 95.45% 96.66% 95.74% 95.58% 95.2%

How likely would you be to recommend Curo Housing to family or friends – ALL (NPS) combined Curo Group 0 47.56% 44.08% n/a 45.34% n/a n/a

Repairs

0

50

100

150

200

250

300

350

1 2 3 4 5

Satisfaction / Likelihood

Cu

sto

mer

s

OSQ

Advocacy

Quality

Neigh'hood

VFM

Voluntas Customer Satisfaction – What do we know? Distribution curve…

Very dissatisfied Fairly dissatisfied Neither Fairly satisfied Very satisfied

Very unlikely Fairly unlikely Neither Fairly likely Very likely

Jan-May 2012

Lettings

0

20

40

60

80

100

120

140

1 2 3 4 5

Satisfaction/Likelihood

Cu

sto

mer

s

OSQ

Advocacy

Qua Home

Neigh'hood

Rent VFM

Voluntas Customer Satisfaction – What do we know? Distribution curve…

Very dissatisfied Fairly dissatisfied Neither Fairly satisfied Very satisfied

Very unlikely Fairly unlikely Neither Fairly likely Very likely

Jan-May 2012

Voluntas Customer Satisfaction – What do we know? Regression Analysis

The quest to determine real customer insight…

• June 2012 – Voluntas were asked to undertake regression analysis across 1241 survey responses gathered in 2012

• Data was placed in a stepwise regression model which builds the ‘best’ predictive model of overall satisfaction for Curo services

• The model starts with whichever variable covers the most unique variance in overall satisfaction (e.g. most extreme responses) and then adds more in order of how much unique variance they then explain, until its built the best possible model and stops adding variables

• In the following charts, Quadrant C and D (most potential quadrants) are those where effort and understanding should be focused as these are statistically predicted to have the most beneficial effect on overall satisfaction with Curo services

Why do this?

• Maybe this analysis should be carried out annually? - Trends shift slowly and over time – identify drivers, determine what we need to do more of / continue doing / do less of, implement changes and then track/monitor feedback over the next period…

Predictive Ability

Perf

orm

ance

H

HL

L

A

B

C

D


Ability of wider variables to 'predict' tenant's reponse to Q6: Overall Satisfaction, compared to current reported levels of satisfaction

Q12: Would recommend to family and friends

Q1: Given enough time to look at property

Q13: Member of staff did what they said they would do

Q7: Overall quality of home

87

88

89

90

91

92

93

94

95

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

R-squared relationship to Q6: Overall Satisfaction (Predictive ability)

Curr

ent

repo

rted

leve

l of s

atisf

acti

on (%

)

Quadrant C: High Predictive Ability/ High Satisfaction

Quadrant A: Low Predictive Ability/ High Satisfaction

Quadrant B: Low Predictive Ability/ Lower Satisfaction

Quadrant D: High Predictive Ability/ Lower Satisfaction

Re-Lets


Ability of wider variables to 'predict' tenant's reponse to Q11: Overall Satisfaction, compared to current reported levels of

satisfaction

Q1: Repairs easy to report

Q5: Property left clean and tidy

Q8: Satisfaction with repairs and maintenance dept.


Q13: Neighbourhood as a place to live

Q14: Rent provides value for money

Q15: Listens to your views and acts upon them


82

84

86

88

90

92

94

96

98

100

0 0.1 0.2 0.3 0.4 0.5 0.6


Curr

ent

repo

rted

leve

l of s

atisf

acti

on (%

)

Quadrant C: High Predictive

Ability/ High Satisfaction

Quadrant A: Low Predictive

Ability/ High Satisfaction

Quadrant B: Low Predictive

Ability/ Lower Satisfaction

Quadrant D: High Predictive

Ability/ Lower Satisfaction

Responsive Repairs




Q11: Member of staff did what they said they would


Q10: Person spoke to helpful

Q9: Satisfaction with gas servicing arrangements

90

91

92

93

94

95

96

97

98

99

100

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45


Curr

ent

repo

rted

leve

l of s

atisf

acti

on (%

)





Gas Servicing




Q10: Satisfied with planned maintenance service

Q4: Contractor wearing ID

Q16: Rent provides value for money

Q9: Satisfaction with contractor

Q7: Work completed within timescale

Q2: Views and preferences taken into account

91

91.5

92

92.5

93

93.5

94

94.5

95

95.5

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35


Curr

ent

repo

rted

leve

l of s

atisf

acti

on (%

)





Planned Works

Voluntas Customer Satisfaction – Regression Analysis summary

Based on this regression analysis, the following questions offer the best opportunity to improve or maintain overall satisfaction with Curo services, by service area (in no particular order):

QuestionOpportunity to improve

furtherRelatively High

Satisfaction already

Recommend to family and friends

Responsive repairs; Gas Servicing

Re-Lets; Planned Works

Overall quality of home Responsive repairs; Gas Servicing

Re-Lets

Listens to views and acts on them

Responsive repairs

Satisfaction with service area (e.g. repairs)

Responsive Repairs; Planned Works

Helpful person Gas Servicing

Member of staff did what they said they would

Gas Servicing

Satisfaction with contractor Planned Works

Rent provides VFM Planned Works

Work completed within timescales

Planned Works

Voluntas Verbatim – what are customers telling us? Responsive Repairs advocacy comments…

“The price is good for the

service I receive”

“I think they are brilliant – they are always there if you

need anything”

“Prompt service”

“Always happy with the way Somer treats

me”

“The lady I dealt with when I was

getting the flat was amazing”

“I think they should be

stricter with some residents”

“They are too slow to deliver

the service with regards to repairs”

“Poor services – they don’t do what they said they will, they don’t consider

personal circumstances and communication is

lacking”

Voluntas Verbatim – what are customers telling us? Gas Servicing advocacy comments…

“If you have a problem they are

very prompt – such as repair work. It’s

good they have checks every 10

months rather than yearly”

“Always very clean and tidy”

“Everybody is very helpful”

“They always listen”“Because Somer

have always treated us well”

“Overall I am happy but there are a few niggly bits which

have not been resolved”

“No-one seems to care – service

has gone downhill”

“Electrical safety check is still

outstanding and anti-social

behaviour still not sorted out”

Voluntas Customer Satisfaction verbatim – likely drivers of satisfaction/dissatisfaction?

Friendly and

helpful Had no problems

in the past

Relative performance –

better than other RPs

Keep your promises Long

standing resident

Impact of ASB

Not calling back

Time to wait for repair

Staff

attitude

Still waiting for

multiple

fixes

Customer Complaint – Top 10 Root Cause Analysis 2011/12– what do we know?

1. Quality of work (both Repairs and Estate Services in-house

repairs/contractors)

2. Internal/External lack of communication

3. Quality of service

4. Residents having to chase staff for a response to query – resulting

in a complaint

5. Repair – length of time to schedule

6. External contractors who work on our behalf don’t adopt the use of

our values or service standards

7. Rude staff/contractors

8. Confidence in our service

9. Multiple visits

10. Request for work we do not normally/cannot carry out

10. Missed appointments

Customer Insight – next steps: priorities and action based on what we know

Importance of

Advocacy

1• Develop true NPS advocacy measures across all surveys

• Need to understand important drivers of advocacy – what, when and why?

• Target and drive action to increase promoters to NPS

• Align and interpret with colleague NPS measure and drivers

Determine emotional elements

2

Quality of Home

Satisfaction with repair

Satisfaction planned wk.

• Need to determine emotional elements around key drivers of satisfaction

• What we need to do more of/less of/the same to preserve/ increase satisfaction

• State of decoration?

• Neighbourhood?

• Quality of Fixture & Fittings?

• Clean & Tidy?

• Right First Time?

• Durability?

• Repair Vs. replace?

• Speed of response?

• Value for money – customers appreciating planned works?

• Setting expectations around timescales?

Needs driven event

3 • Our agenda rather than customer agenda – e.g. Gas Servicing

• Customer isn’t asking anything of us…….but we recognise the importance of colleague attitude/friendliness/helpfulness and did what we said we would

e.g.

4Survey

structure• Survey requirements; tender process; sample governance & representation

Customer Insight Analysis

Business

Transcript of Customer Insight Analysis