Giovanni Lux

20 Novembre, 2010

Implementare un sistema di

customer loyalty per migliorare la

customer experience: un caso di

successo

What’s Customer Experience?

2

Understand which experience turns a prospect into a buyer and into a brand

promoter and enable the «repetition» of such an experience at key steps of

the customer journey

OPINION

what Prospects & Customers think of the company

DATA

the hard things we know about prospects/customers:

Who, where, what they bought

2

CSI/NPS Sales/Service

TRANFORM PROSPECTS INTO BUYERS AND PROMOTERS

Marzo 2011

3

Sales Cycle

Service/Owner

Cycle

Equity Position on

Finance Contract

Market Awareness

Repurchase

Consideration

Avoidable Defection

Natural Defection

Sales Retention /

Defection Cycle

Customer Experience

Warranty Repair

Customer Feedback

Scheduled Service

Inspection

Customer Complaints

Dealer Defection

Brand Defection

Vehicle Recall

Repairs

Customer Feedback

CSI Information &

Complaints

Consideration Set

Brand Enquiry

Demo

Negotiate

Shopper Feedback

Lost Sale

Order

Delivery

Sales Customer Feedback

CSI Information

Customer Experience & CRM - Activities

Understand our customer to improve sales and service effectiveness

4 Inserire Titolo Evento

DLR Digital DM Campaign/SEM

Web site lead capture opt.

CRM Campaigns Brand/Dlrs

Shopper Feedback Coaching

Lead Management

Sales CSI Customer Feedback

After Sales CRM Campaigns P&S/DLR

Service Customer Feedback

Objectives Activities

Showroom

Traffic

Conversion

rate

Workshop

Traffic

Customer Experience Stages

Customer

Experience

Data

Bas

e, R

ep

ort

ing

, S

ale

s t

rac

kin

g

Customer Experience & CRM: what we do

Understand our customer to improve sales and service effectiveness

5

Customer Satisfaction

Measurement

Customer Database, Business

Intelligence and

Reporting

Direct Marketing and Lead

Management

Dealer CE&CRM Services

(Shopper Feedback, Pipeline

Management, DM, SEM)

Analytical & Operational CRM

Visibility

Traffic

Loyalty

Understanding

Local traffic

Experience

Closure Rate

Marzo 2011

Analytics

dbCARE Customer Analysis, Relation & Experience

vendita autovetture nuove

prodotti finanziari

interventi riparativi assistenza stradale

concessionari

lead

customer satisfaction

passaggi di proprietà, rottamazioni, cambi di indirizzo…

Operational

dbCARE

Privacy management Contact rules Data use rules

CE&CRM MKT Campaign management

Target selection

Contact history

Loyalty plan mgmt.

Response rate mgmt.

CE&CRM HQ Data mining

Predictive modeling

Targeting

Reporting / response rate

mgmt.

fonti esterne - validazione / arricchimento - concorrenza ( i )

1

2

3

4

56

F

M

18-24

25-34

35-44

45-54

55-64

65-74

fedeltàSEGMENTO

fedeltàMARCA

I auto

Possesso 0

Possesso>0Acquisto NUOVO

Possesso>0Acquisto USATO

7

Analytics e Campaign Managment

Cluster Analysis

FGA Customers – A,B,C,L0

8

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6

N-% auto 8 - 15% 7 -13% 16 - 29% 7 - 13% 9 - 16% 8 - 15%

N-% acquirenti 17,846 - 26% 6,915 - 10% 14,341 - 21% 16,459 - 24% 7,980 12% 5,083 - 7%

Segmento A/B A/B A/B B C L0

FIAT GRANDE PUNTO ALFA ROMEO MiTo CITROEN C1 CITROEN C3 FIAT BRAVO CITROEN C3 PICASSO

FIAT PANDA SEAT IBIZA FORD KA FORD FIESTA FORD FOCUS FIAT FIORINO QUBO

FIAT PUNTO LANCIA Y/Y10/YPSILON OPEL CORSA HYUNDAI I 30 FIAT IDEA

FIAT SEICENTO NISSAN MICRA PEUGEOT 206 OPEL ASTRA FORD FUSION

RENAULT TWINGO PEUGEOT 207 PEUGEOT 308 OPEL MERIVA

SUZUKI SWIFT RENAULT CLIO RENAULT MEGANE

TOYOTA AYGO VW POLO

TOYOTA YARIS

CHEVROLET AVEO FIAT 500 MY 07 CHEVROLET MATIZ AUDI A3 LANCIA MUSA

DACIA SANDERO MAZDA 2 HYUNDAI I 10 BMW SERIE 1 MERCEDES CLASSE A

HYUNDAI I 20 MINI KIA PICANTO VW GOLF RENAULT MODUS

SKODA FABIA SMART NISSAN PIXO

TOYOTA IQ OPEL AGILA

PEUGEOT 107

SUZUKI ALTO

SUZUKI SPLASH

Sesso/Età Over 45 Under 35 Femmine M under 25 / F under 55 Maschi Maschi over 35

Parco Poss/Acq Poss>0 Acq Usato I auto / Poss 0 I auto /Poss>0 Acq Usato I auto Poss 0 /Poss>0 Acq Nuovo Poss 0 /Poss>0 Acq Nuovo

Fedeltà Marca Segmento Marca Marca

Marca/Modello

LEGENDA

B benzina

D diesel

G gpl

M metano

Alfa

Fiat

Lancia

Abarth

LEGENDA

B benzina

D diesel

G gpl

M metano

Alfa

Fiat

Lancia

Abarth

Analytics e Campaign Managment

Cluster Analysis

FGA Customers – A,B,C,L0

9

Sul miglior 5 % la lift è pari a 6.5, sul miglior 20% a 3.2

1

2

3

4

5

6

7

Training

Validation

Totale

ventili di popolazione (ordinata in base allo score)

lift c

um

ula

ta

Ventile Training Validation Totale

5% 6.45 6.47 6.47

10% 4.62 4.64 4.63

15% 3.72 3.73 3.73

20% 3.14 3.17 3.15

25% 2.76 2.77 2.76

30% 2.46 2.47 2.46

35% 2.22 2.22 2.22

40% 2.01 2.02 2.02

45% 1.86 1.86 1.86

50% 1.72 1.72 1.72

55% 1.61 1.61 1.61

60% 1.50 1.51 1.51

65% 1.42 1.41 1.42

70% 1.34 1.34 1.34

75% 1.27 1.27 1.27

80% 1.20 1.21 1.20

85% 1.15 1.15 1.15

90% 1.10 1.09 1.10

95% 1.05 1.05 1.05

100% 1.00 1.00 1.00

LIFT cum

Analytics e Campaign Managment

Predictive Modeling – Cluster 1 Brand Fiat Loyalty

30%

40%

50%

60%

70%

80%

90%

100%

Training

Validation

Totale

ventili di popolazione (ordinata in base allo score)

%ris

po

sta

cattu

rata

cu

mu

lata

10

Sul miglior 5 % si cattura il 32% del target,

sul miglior 30% il 74%

Ventile Training Validation Totale

5% 32.3% 32.3% 32.3%

10% 46.2% 46.4% 46.3%

15% 55.8% 56.0% 55.9%

20% 62.8% 63.3% 63.0%

25% 69.0% 69.2% 69.1%

30% 73.7% 74.0% 73.7%

35% 77.6% 77.8% 77.7%

40% 80.6% 80.9% 80.8%

45% 83.6% 83.7% 83.6%

50% 86.0% 86.0% 86.0%

55% 88.4% 88.4% 88.4%

60% 90.3% 90.3% 90.4%

65% 92.1% 91.8% 92.1%

70% 93.8% 93.6% 93.7%

75% 95.0% 95.1% 95.1%

80% 96.3% 96.4% 96.3%

85% 97.6% 97.4% 97.6%

90% 98.8% 98.4% 98.6%

95% 99.4% 99.3% 99.4%

100% 100.0% 100.0% 100.0%

% RISPOSTA CATTURATA cum

Analytics e Campaign Managment

Predictive Modeling – Cluster 1 Brand Fiat Loyalty

11

Sul miglior 5% la lift è maggiore di 7

Sul miglior 20% la lift è pari a 3

Analytics e Campaign Managment

Predictive Modeling – Brand Alfa Romeo

12

Sul miglior 5% si cattura il 44% del target

Sul miglior 30% si cattura il 70% del target

Analytics e Campaign Managment

Predictive Modeling – Brand Alfa Romeo

Marzo 2011

Marca Acquistata

Marca posseduta Contatto DM FGA Concorrenza Auto

FGA NO 45,77% 54,23%

SI 51,19% 48,81%

Concorrenza Auto NO 18,04% 81,96%

SI 24,46% 75,54%

Totale 31,21% 68,79%

13

Direct marketing

+ 5,4% loyalty

Marzo 2011 14

Fonte: Netpop Research – Italy 2009

Search engine Geo-localization capability gives opportunity to invest on-line at national

level, at local (area/city) and at dealer level with more specific promotional activities

Brand area focused campaign (ex Milano Mito campaign)

Dealer Campaign (ex FAV frankfurt sept campaigns)

Brand National campaign (ex Giulietta DE)

WEB: Lead Capture

optimize sem/ses (digital direct marketing)

Marzo 2011

Lead Management

Leads Capture

Leads Qualification (Prospect)

Leads Profiling

Leads Dispat- ching

Sales Tracking

WEB Corporate

Web campaign

SES/ Landing

page

Inbound Calls

DM Campaign

Customer/Leads Feedback

Dealers Reporting

From lead capture, treat lead, qualify, book appointment, dispatch, and process at the dealer

to monitor and manage with Sales Reps.

Governance (KPIs) • Lead Capture

• Sales on Leads

• Qualified leads on total leads

• Leads managed within service level • • Customer (lead) satisfaction

Marzo 2011

NetMining and Lead Management

16

Attract Traffic

Conversion Marketing

Lead Generation

Sales

Behavioural Targeting

Internet users Key elements:

On-line scoring based on

navigation pattern traced using

existing site page tags

Dynamic registration for action

forms triggered by on-line score

to capture leads

Lead Processing through: lead

treatment, visit booking,

disptaching and closure tracking

On line Profiling Lead Management

Marzo 2011 17

Shopper Feedback

Active management of pipeline

What is it?

Active management of dealer sales pipeline by following up with all prospects that “shopped” at the dealership and coaching salesman to understand and react to shopper feedbacks

What you get?

Monitoring and improving of dealer “traffic” and sales process

Why and how many shoppers rejected

What actions are required to make undecided shoppers buyers

Shopper profile and cross shopping considerations

Increased Win-back Sales

Showroom

traffic

Rejecters

(lost) Undecided

(win back)

Buyers

(won)

Traditional

focus

Shift done

Relevant

focus

Marzo 2011 18

Shopper feedback

Impact on Sales

Shopper Feedback ensures 100% follow-up on prospects. The

positive benefit is an increased “win-back” rate

Shopper Management increase closure rate of

“undecided”

Not Processed by Shopper Feedback

Processed by Shopper Feedback

Closure rate on “undecided” shoppers 3 months after proposal date

2,4%

4,8%

+ 100%

Sales tracked on processed shoppers are 50% incremental

Marzo 2011 19

Shopper Feedback

Impact on rejection rate

1) Shopper Feedback based on site coaching

and dealership management of salesmen

improves NPS.

2) Improved NPS reduces Rejection Rate and

therefore minimizes lost sales

3) Can help sustaining overall Customer

satisfaction (NCBS ranking AR Italy)

15%

20%

25%

30%

35%

25% 30% 35% 40% 45% 50% 55%

Reje

cto

pn

rate

Shopper NPS

Dealers with NPS >50% decrease their rejection

rate by 30%

NPS vs Rejection Rate

Results FGA Italy Gen-July 2010, dealers with more than 100% interviews and that recorded more than the expected number of offers .

+36%

42%

Potentially increasing their sales by 20%

2008

Top

Avr

Bot

2009

Marzo 2011 20

Shopper Feedback

“real time” Marketing Intelligence

Collecting Shopper feedback we can monitor the traffic volume and

the profile of our potential customers Mito Shopper Profile

Marzo 2011 21 21

- Quanto sei soddisfatto dalla tua esperienza in concessionaria?

- Raccomanderesti la concessionaria?

- Ti hanno proposto una prova su strada della vettura?

Sales

SEMPLICE, VELOCE E TRASPARENTE

Cosa avrebbe dovuto fare la

Concessionaria per migliorare la tua

opinione?

Qual è l’aspetto che hai apprezzato maggiormente?

PROMOTER?DETRACTOR?

Cosa avrebbe dovuto fare la

Concessionaria per ottenere un 10?

PASSIVE?

1-6 7-8 9-10

1

In 2007 we redesigned the program to:

• Provide faster and transparent customer feedback to dealers

• Refresh concept from long term “loyalty” to shorter term business

opportunity through word-of-mouth

NPS = % Promotors - % Detractors

Customer Feedback: Sales and Service

Marzo 2011 22

3,7%

3,6%

4,9%

6,8%

5,3%

5,1%

5,2%

5,3%

7,3%

7,0%

2,8%

3,7%

3,8%

3,6%

3,8%

6,2%

6,3%

7,2%

8,6%

7,7%

2,0%

2,5%

1,9%

3,9%

3,1%

1,8%

2,8%

3,6%

3,8%

3,0%

0,0% 5,0% 10,0% 15,0% 20,0% 25,0% 30,0% 35,0% 40,0%

2trim2009

3trim2009

4trim2009

1trim2010

2trim2010

prezzo tempi_consegna Informazioni

Gentilezza e Competenza modalità di consegna burocrazia, organizzazione,…

Processing the open ended questions on “what should we have done to deserve

a stronger recommendation?” we can identify the priorities in the eyes of the

customers

Customer Feedback: Sales and Service

Marzo 2011 23

CON ALMENO 10 INTERVISTE

N° Dealer

44,5 %volume di

vendite

4 63

dispersione

indice

32 1

SOPRA LA MEDIA

MERCATO: 162 dealer

SOTTO LA MEDIA

MERCATO: 130 dealer

%

vo

lum

e v

en

dit

e i

n a

mb

ito

media mercato

62.8 %

INDICE NPS ( -100% ÷ 100% )

best performers

87.4 %

55,5 %volume di

vendite

Totale DEALER = 292

107 30 78 94

2,90%

21,60%

32,40%

28,50%

11,10%

1,50%0,60%0,80%0,20%0,30%

( -17.5 ) ( -5.9 ) ( -5.9 ) ( 5.3 ) ( 5.3 ) ( 16.5 ) ( 16.5 ) ( 27.7 ) ( 27.7 ) ( 38.9 ) ( 38.9 ) ( 50.1 ) ( 50.1 ) ( 61.3 ) ( 61.3 ) ( 72.5 ) ( 72.5 ) ( 83.7 ) ( 83.7 ) ( 94.9 )

Customer Feedback: Sales and Service

The Contribution of CRM Sales as a % of Sales to Retail Customers grew

year over year but is still half of it’s potential

CE & CRM Sales

Current State & Potential

The turning point was in 2008, when we started providing DLR CE&CRM Services to dealers supported by on site coaching: this increased the adoption of DM and Dealer Pipeline Management (Shopper Feedback) .

Potential target is 25% (the performance of DRL CRM Services heavy users is 25-30%!)

1,10% 2,30%

4,90%

8,70%

12,50%

15%

0%

5%

10%

15%

20%

25%

30%

2006 2007 2008 2009 2010 2011

24

+10% p.ts

Target value 25%