Introduction à l'analytique Web

INTRODUCTION À L’ANALYTIQUE WEB Université de Montréal Stéphane Hamel immeria.net [email_address] Web Analytics Association UBC Award of Achievement in Web Analytics eMetrics Marketing Optimization Summit

Qu’est-ce que l’analytique Web?

L’ analyse de données qualitatives et quantitatives provenant des sites web , de la compétition et des systèmes d’entreprises

afin de mener à une amélioration continue de l’ expérience des utilisateurs (clients et prospects)

qui se traduis par l’atteinte des objectifs de l’ utilisateur et de l’ entreprise .

La vérité… un rébus…

! 

 ≠ 

1  2  3

 +  +  = 

Le succès de l’analyse Web dépend de la capacité à maîtriser le processus et à agir sur la connaissance acquise.

Inspiré de Eric Peterson, « One Guru’s view of the Analytics Industry in 2007 »

Model de maturité analytique Level 1 Level 2 Level 4 Level 3 Level 5 IT driven, “feel good” information, few decisions, minimal value Business driven, working on metrics, accuracy and process Optimize the channel 330° view of customer (30° of privacy) Strategic Web Adapté de Bill Gassman, Industry Analyst, Gartner, presented at eMetrics Summit 2007, San Francisco

Empowered teamwork Business Technology Analysis Q&A Actionable insight Business requirement & objectives Means, tools and data Strategy Goals Technological capabilities & constraints Information architecture Tagging & BI Statistics Analytical mindset Synthesis Communication Equipe Ultime

Méthodologie

Systematique

Continu

En changement

Objectif SMART

Simple

Mesurable ( Measurable )

Atteignable ( Achievable )

Réaliste ( Realistic )

Temps ( Timely )

Actionable Insights & Metrics Behavior ClickStream Click Density Analysis Segmentation End to End Search “Intent Inferences” Experience Research Customer Satisfaction A/B & MVT Testing Usability “Voice of Customer” Orders/Leads Revenue: How, Why Conversion Rates Problem Resolution “Nuances of outcomes” Outcomes Win-win Outcomes Understanding customer Experience Influence optimal Behavior Strategie: Trinite With permission of Avinash Kaushik, kaushik.net

Multiplicité Adapté de Avinash Kaushik, Web Analytics Evangelist, Occam’s Razor, kaushik.net/avinash Vue holistique et connaissance du comportement utilisateur Analyse

Analyse

Perspective du visiteur

Perspective d’affaires

Qui vient sur le site

Degré d’engagement

Provenance

Facteurs sociodémographiques

Ce qu’ils veulent faire

Rechercher de l’information

Trouver un produit, obtenir un prix

Trouver un magasin, s’inscrire à un concours ou un newsletter, etc.

Est-ce qu’ils ont réussi?

Trafic ciblé et qualifié

Expérience agréable

Processus fonctionnel et efficace

Qui nous voulons

Comment les aider

En ligne avec nos objectifs stratégiques

KPIs fréquemment suggérés Adapté de Eric Peterson, « The Big Book of Key Performance Indicators » eCommerce Marketing Support Content Executive Level KPIs

Order conversion rate

Customer conversion rate

Average order value

Average revenue per visit

Average cost per conversion

Percentage high/low satisfaction customers

Average page views per visit

Average cost per visit

Average of high, medium, low frequency visitors

Average time to respond to email inquiries

Percent of high/low satisfaction customers

Percent new/returning customers

Lead generation conversion rate

Average cost per conversion

Average (estimated) revenue per visit

Strategic Level KPIs

Ratio of new to returning visitors

New and returning visitors conversion rate

Percent of revenue from new and returning customers

Home page and landing pages “stickiness”

Average visits per visitor

Percentage of high, medium, low time spent visits

Information find conversion rate

Percent visitors using search

Percent visitors in a specific segment

Percentage visitors in a specific segment

Average visits per visitor

Percentage of high, medium, low time spent visits

Percentage of high, medium, low recency visitors

Tactical Level KPIs

Search to purchase conversion rate

Cart and checkout completion rate

Order conversion rates per campaign and campaign type

Percent low recency visitors

Percent zero result and zero yield searches

Percent high, medium, low click depth visits

Subscription conversion rate

Percent of visitors using search

Percentage of high, medium, low click depth visits

Landing pages “stickiness”

Percent of high, medium, low click depth visits

Search result to site exits ratio

Form completion rate

Download completion rate

Landing page “stickiness”

Average searches per visit

Lead generation rate per campaign and campaign time

Exemples

KPIs Recommandés

Connaissances acquises grâce à l’analyse des éléments critiques, toujours présentés en contexte et selon un segment spécifique

Key Performance Indicators Executive

Online Sales Revenues

Cart & Checkout Conversion Rates

Average Order Value

Visits to Online Success Ratio (regardless of activity)

Strategic

Cost per Conversion

Ratio of First Time to Repeat Customers

Ratio of New to Repeat Visitors

Frequency / Recency Indexes for Visits and Orders

Tactical

Checkout Process Conversion

Form Abandonment for critical events

Bounce Rate, Time on Site, Visits to Purchase, Time to Purchase

Instrumentation

É cosystème

« L'ensemble formé par une association ou communauté d'êtres vivants et son environnement géologique, pédologique et atmosphérique. Les éléments constituant un écosystème développent un réseau d'interdépendances permettant le maintien et le développement de la vie. »

Source: Wikipedia.org

Example ecosystem

Direct competition:

X

Y

Z

Indirect online generalists:

A

B

Known competitors:

A

B

C

D

Source: Touchgraph.com analysis

Indirect/related:

E

F

G

H

Example report from Omniture SiteCatalyst

Conversion rates by source/revenue

Conversions & Revenues

Form overlay example

INTRODUCTION À L’ANALYTIQUE WEB Université de Montréal Stéphane Hamel immeria.net [email_address] Web Analytics Association UBC Award of Achievement in Web Analytics eMetrics Marketing Optimization Summit