Post on 18-Feb-2019
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%