Explication d'écart de performance avec DataMa chez le groupe Pierre et Vacances Center Parcs

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COMMENT TRANSFORMER SON SUIVI DE PERFORMANCE WEB
EN DÉCISIONS RAPIDES, PRIORISÉES ET VALORISABLES ?
2 octobre 2019

2. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Agenda
1. Objectifs et présentations
2. Organisation analytics et outils
3. Suivi de performance
4. Retour d'expérience & questions

3. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
• Bonnes pratiques du suivi de la performance de
son site eCommerce
• Comment structurer et organiser sa démarche de
suivi de performance
• Quels outils pour accélérer ces analyses
Objectifs de la présentation

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Qui sommes nous ?
Anne-Cécile MALBERT Guillaume de BENAZÉ
Manager web analytics CEO & Fondateur

5. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
+8M visiteurs par mois CP/PV/SPde taux de conversion1,5%
Revenus online50% 1.5B€ de CA en 2018
Pierre & Vacances Center Parcs
Quelques chiffres

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Cooperation
Simplicity
Conversion
Pierre & Vacances Center Parcs
Une approche data driven
“Think Customer first & track consistently to build together a simple &
innovative customer journey through all channels”
“Think Customer first & track consistently to build together a simple &
innovative customer journey through all channels”
1
2
3
CUSTOMER FIRST

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DataMa
Nos solutions
Analyse d’écart de KPI
entre deux segments
Analyse des
dimensions impactant
le revenu
Analyse de la
significativité des
variations
Analyse comparative
des parcours
utilisateurs
DataMa JOURNEY
Add-on
On-
premiseSaaS

8. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Agenda
1. Objectifs et présentations
2. Organisation Analytics et Outils
3. Suivi de performance
4. Retour d'expérience & questions

9. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Qu’analyse t’on sur un site eCommerce ?
Les différents niveaux d’une analyse
Contenu
Parcours Utilisateur
Profil Utilisateur
Conversion Funnel
Processus, ressources, outils, gouvernance
Traffic Sources

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Profil Utilisateur Contenu
Parcours
Utilisateur
Conversion Funnel
Processus, ressources, outils, gouvernance
Traffic Sources
Quelle organisation
Les grands pôles de l’équipe digital
Analytics
Product
Acquisition, CRM
IT/ Tech
E Merch, Marketing

11. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Quelle organisation
L’équipe analytics
Design & Analyse des AB Tests
Measurement (Tag Mgt, Data Quality, GDPR)
Data science
Ad hoc analysis & Forecast
Attribution & Data-driven Marketing
Report & Analyse de la performance digital
Analytics Product
Acquisition &
CRM
IT/ Tech
E Merch &
Marketing
Report & analyse business global des Sales
4 senior & 2 junior webanalysts
4 analysts & 2 data scientists

12. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Quelle organisation
Nos challenges
Analytics Product
Acquisition &
CRM
IT/ Tech
E Merch &
Marketing
QUALITY: production and follow up on actionable business insights
We need to further reduce the time to respond
Our analysis needs to be more insightful
We need to drive more actions for improvements
QUANTITY : coverage of all the brands, markets, and touchpoints
FR BE NL
DE CH AT NFM
UKX
For all BRANDS… For all MARKETS…
B2B
1. Online Media
2. Search Engine
3. Reservation websites
4. Call Center
And for all TOUCH POINTS
X
5. Work Council channel
6. Stay planning websites
7. Email Campaigns
8. Mobile Apps

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Quels outils
Echantillon des outils
Analytics Product IT/ Tech
Design & Analyse des AB Tests
Measurement (Tag Mgt, Data Quality, GDPR)
Data science & Business analysis
Ad hoc analysis & Forecast
Attribution & Data-driven Marketing
Report & Analyse de la performance digital
Acquisition &
CRM
E Merch &
Marketing

14. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Quelle organisation
Focus sur le suivi de performance web
Focus aujourd’hui
Analytics Product IT/ Tech
Acquisition &
CRM
E Merch &
Marketing
Design & Analyse des AB Tests
Measurement (Tag Mgt, Data Quality, GDPR)
Data science
Ad hoc analysis & Forecast
Attribution & Data-driven Marketing
Report & Analyse de la performance digital
Report & analyse business global des Sales

15. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Agenda
1. Objectifs et présentations
2. Organisation analytics et outils
3. Suivi de performance
4. Retour d'expérience & questions

16. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Suivi de performance
Quelles questions pour un analyste
Les questions qu’on se pose en tant qu’analyste
• Comment expliquer les variations de la performance ?
• Comment prioriser les analyses et les facteurs explicatifs ?
• Quelles actions mettre en œuvre, et par quelle équipe ?
Comment traduire ça en terme d’analyse
• Analyse du tunnel de conversion
• Analyse des dimensions explicatives

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Suivi de performance
Gouvernance et RACI
MonthlyMonthly QuaterlyQuaterlyWeeklyWeekly
Weekly
IDENTIFY SHARE ACT
FEEDBACK &
CHECK

18. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Suivi de performance
Comment identifier les root causes Monthly QuaterlyWeeklyWeekly
Weekly
Analytics
Reporting
Highlight des top/ flop par
Marque & Marché
Deep Dive Analysis
Marque – Marché – Device – Sources –
Landing Page – Browsers - AB/test Version –
Funnel Steps
20%
30%
50%
TRAFFIC| Acquiz-CRM CVR| Emerch-Product-RM
SHAREIDENTIFY ACT FEEDBACK

19. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Suivi de performance
Comment partager les analyses Monthly QuaterlyWeeklyWeekly
Weekly
Analytics
Product
Acquisition &
CRM
IT/ Tech
E Merch &
Market
Coordination
Causes
& Actions
Top / Flop
Traffic & CVR
20%
60%
Analytics 20%
Monitoring Committee
SHAREIDENTIFY ACT FEEDBACK

20. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Suivi de performance
Comment agir en conséquence Monthly QuaterlyWeeklyWeekly
Weekly
Analytics
Product
Acquisition &
CRM
IT/ Tech
E Merch &
Market
Business Review
& Actions
par département
Feedbacks sur les
actions menées &
ValidationAutres
départements
Sales
Business Meeting
Direction
SHAREIDENTIFY ACT FEEDBACK

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Le suivi de performance
On veut (Presque) toujours comparer à quelque chose
Start
(e.g. LY)
End
(e.g. TY)
?KPI
(e.g. Revenu)

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La solution:
Procéder par étape et faire un peu de maths!
Tunnel de conversion Segments produits et utilisateurs

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L’analyse du tunnel de conversion:
Relier des PI à un seul KPI
Tunnel de conversion Segments produits et utilisateurs

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L’analyse du tunnel de conversion
selon la méthode de l’équation de marché
• DÉCOMPOSER LES EFFETS DE VOTRE ACTIVITÉ
• SUIVRE LA PERFORMANCE À CHAQUE ÉTAPE DE SON TUNNEL DE CONVERSION
POURQUOI FAIRE

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L’analyse du tunnel de conversion
Rappel sur un tunnel
Utilisateurs
#RevenuSessions
Fiche
Produit
Panier
Navigation Conversion
Achat
Revenu

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L’analyse du tunnel de conversion
Construction d’une équation de marché
Utilisateurs
#RevenuSessions
Fiche
Produit
Panier
Navigation Conversion
Achat
Revenu
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠 𝑥
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠
𝑥
𝑃𝑎𝑛𝑖𝑒𝑟
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝑃𝑎𝑛𝑖𝑒𝑟
= 𝑅𝑒𝑣𝑒𝑛𝑢 (€)

27. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse du tunnel de conversion
Généralisation à d’autres champs d’application
Web analytics 𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠 𝑥
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠
𝑥
𝑃𝑎𝑛𝑖𝑒𝑟
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝑃𝑎𝑛𝑖𝑒𝑟
= 𝑅𝑒𝑣𝑒𝑛𝑢 (€)
𝑂𝑢𝑣𝑒𝑟𝑡
𝐸𝑛𝑣𝑜𝑦é
𝑥
𝐶𝑙𝑖𝑐
𝑂𝑢𝑣𝑒𝑟𝑡
𝑥
𝐶𝑜𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛
#𝐶𝑙𝑖𝑐
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝐶𝑜𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛
=
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝐸𝑛𝑣𝑜𝑦é
Campagne mailing
𝐼𝑚𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛𝑠 𝑥
𝐶𝑙𝑖𝑐
𝐼𝑚𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛
𝑥
𝐶𝑜𝑢𝑡
𝐶𝑙𝑖𝑐
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢𝑒
𝐶𝑜𝑢𝑡
= 𝑅𝑒𝑣𝑒𝑛𝑢 (€)Display
𝑉𝑜𝑙𝑢𝑚𝑒 𝑥
𝑅𝑒𝑣𝑒𝑛𝑢𝑒
𝑉𝑜𝑙𝑢𝑚𝑒
𝑥
𝑀𝑎𝑟𝑔𝑒
𝑅𝑒𝑣𝑒𝑛𝑢𝑒
= 𝑀𝑎𝑟𝑔𝑒(€)Marge

28. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse du tunnel de conversion
Construction d’un bridge
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠 𝑥
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠
𝑥
𝑃𝑎𝑛𝑖𝑒𝑟
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝑃𝑎𝑛𝑖𝑒𝑟
= 𝑅𝑒𝑣𝑒𝑛𝑢𝑒
𝑅𝑒𝑣𝑒𝑛𝑢 = 𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠 𝑥
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑆𝑒𝑠𝑠𝑖𝑜𝑛𝑠
𝑥
𝑃𝑎𝑛𝑖𝑒𝑟
𝐹𝑖𝑐ℎ𝑒 𝑃𝑟𝑜𝑑𝑢𝑖𝑡
𝑥
𝑅𝑒𝑣𝑒𝑛𝑢 €
𝑃𝑎𝑛𝑖𝑒𝑟
Start EndStep 1 Step 2 Step 3 Step 4
Start
End

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L’analyse du tunnel de conversion
Avec l’outil DataMa

30. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse des dimensions:
Distinguer effet mix et performance
Tunnel de conversion Segments produits et utilisateurs

31. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse des dimensions explicatives
• COMPRENDRE L’IMPACT DES CHANGEMENTS DE MIX À L’ACQUISITION SUR LA
MOYENNE OBSERVÉE
• IDENTIFIER LES SOUS SEGMENTS AYANT UN PROBLEME DE PERFORMANCE
• CHOISIR LA DIMENSION D’ANALYSE LA PLUS PERTINENTE
POURQUOI FAIRE

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L’analyse des dimensions explicatives
Exemple de dimensions

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L’analyse des dimensions explicatives
Le principe de l’effet mix
Conversion
(Achat/
Session)
Mix (% Sessions)
Desktop
Mobile
Total
Last Year This Year
Purchase Sessions CVR % Sessions Purchase Sessions CVR % Sessions CVR % Ch
Mobile 500 100 000 0.5% 10% 2 400 400 000 0.6% 40% 20.0%
Desktop 18 000 900 000 2.0% 90% 15 000 600 000 2.5% 60% 25.0%
Total 18 500 1 000 000 1.9% 100% 17 400 1 000 000 1.7% 100% -5.9%
• Pris isolément, Mobile et
Desktop augmentent en
performance
• Pourtant, la moyenne
globale baisse
• « L’effet mix » explique
cette baisse, due au delta
de conversion entre
Mobile et Desktop
• On veut ‘netter’ l’effet
mix pour expliquer la
performance

34. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse des dimensions explicatives
Le principe de l’effet performance
Conversion
(Achat/
Session)
Mix (% Sessions)
Total
Last Year This Year
Purchase Sessions CVR % Sessions Purchase Sessions CVR % Sessions CVR % Ch
SEO 500 100 000 0.5% 10% 300 100 000 0.3% 9% -40.0%
SEA 18 000 900 000 2.0% 90% 17 000 1 000 000 1.7% 91% -15.0%
Total 18 500 1 000000 1.9% 100% 17 300 1 100 000 1.6% 100% -15.0%
SEA
SEO
• SEO et SEA baissent en
performance
• Comme le SEA
représente une partie
importante du mix, on
risque de se concentrer
sur celui-ci
• Pourtant, c’est le SEO qui
a une baisse de
performance
préoccupante au regard
de la moyenne

35. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Analyse des dimensions utilisateurs
Avec l’outil DataMa

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Résumé du suivi de performance
Avec l’outil DataMa

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Agenda
1. Objectifs et présentations
2. Organisation analytics et outils
3. Suivi de performance
4. Retour d'expérience & questions

38. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Retour d’expérience
Nos enseignements clés
Les DO’s
• Avoir un KPI framework clair et des données propres et standardisées
• Automatiser au maximum le reporting, et les analyses communes
• Avoir une approche top down
• Utiliser des dimensions actionnables selon les étapes analysées
• Clarifier l’organisation et les responsabilités (RACI)
• Travailler en Task Force avec un team lead pour le suivi des actions
Les DON’T
• Une organisation avec des reports et analyses réalisées en silo
• Commenter pour commenter, au lieu de focuser sur les priorités et sur les leviers actionnables
• Regarder des moyennes

X

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Retour d’expérience
Les bénéfices de DataMa Compare pour PVCP
Notre conseil
• Etre clair sur ce qu’on cherche à suivre
• Mettre en place la gouvernance adéquate
pour utiliser l’outil
• Simplifier au maximum pour assurer
l’adhésion des équipes business
Les bénéfices
• RAPIDITE pour identifier les priorités et les
insights clés à partager
• SIMPLICITE avec une vision globale du tunnel
de conversion
• CLARTE grâce à un système d’analyses et
d’alertes automatisé

40. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
Questions et réponses
Anne-Cécile MALBERT Guillaume de BENAZÉ
Manager web analytics CEO & Fondateur
annececile.malbert@groupepvcp.com guillaume@datama.fr

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Annexes
2019

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Tarification et modèle économique 2019
PACK MULTI
+ 1 module
+ 2 modules
550€/mois | 5500€/an
650€/mois | 6500€/an

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Les liens
Link Content
Docs.datama.fr Documentation on the solutions
News Latest releases on solutions
Solutions.datama.fr SaaS applications
Slack For live support
support@datama.Fr Email if need be
Sources Exemple of sources working with DataMa
Datama.Fr DataMa website

44. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse des dimensions explicatives
Principe de covariance
A (End)
e.g.
Revenue
End
A/B
B
e.g. Revenue/
Purchase
e.g. Purchase
A (Start)
e.g. Revenue Start
B Effect
A/B Effect
Covariance
Start
End

45. This information is confidential and was prepared by DataMa solely for the use of our client; it is not to be relied on by any 3rd party without DataMa's prior written consent
L’analyse des dimensions explicatives
Séparation des effets mix et performance
Dim 1:
Segment 2
e.g. BU:
Spain
Dim 1:
Segment 1
e.g. BU:
France
Dim 1:
Segment 1
e.g. BU:
France Dim 1:
Segment 2
e.g. BU:
Spain
Mix Effect
Segment Performance
Both (Covariance)
Start
End
A/B
Mix (% of B)
e.g. Rev/
Purchase
e.g. % of Purchase