Hong Kong Web Analytics Wednesday #6

Web Optimization To Improve Conversion
Louis Ngai | Solution Consulting Lead

© 2010 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

Area to Optimized for Retail Site

 Campaign Optimization
 Identify Fallout Point
 Content Influence Optimization
 Content Targeting


Omniture Fusion
External Campaigns Success

The Fundamentals Sample Business Questions
1. Page and Content Identification  What kind of return am I getting
2. Page Effectiveness
for my campaigns?
3. Page Real Estate Valuation
(ClickMap)  Which channels deserve more
4. Shopping Cart Performance marketing spend?
5. Payment & Fulfillment Methods
6. Product Category Analysis
 Relationship between Campaigns
7. Product Finding Methods
8. Product Merchandising
9. Internal Search Optimization
10. Internal Campaign Success Key Metrics
11. External Campaigns Success
12. Paid and Natural Search Tracking
 Visits  AOV
 Orders  Conversion
 Revenue  Yield

© 2008 Omniture Inc., Confidential & Proprietary

Four Key Areas of Facebook Measurement

Public/Fan Pages Applications

Facebook Ads Facebook Open Graph


External Campaigns Success

Measure marketing channel performance

Channel by Partner


Case Study: Measure Campaign Performance

 Determine which campaigns influence new vs. loyal members
 Measure the channels that are the most influential
 Reveal what drives most effective member loyalty

Determine Campaign Frequency

Reveal Campaign Channel

Understand Campaign Influence

6

Omniture Fusion
Page & Content Identification

1. Page and Content Identification  What are my most popular pages?
 What paths do users most frequently
(ClickMap) take?
4. Shopping Cart Performance
 Where do users exit my site?
5. Payment & Fulfillment Methods
6. Product Category Analysis  Which pages have the highest bounce
7. Product Finding Methods rate?
 Page Views  Bounce Rate
 Visits  Exit Rate
 Path Views  Avg. Time Spent


Use Case Examples

Understand page usage and abandonment

Evaluate high-level content consumption


Use Case Examples

Measure movement through page types


Actions

1 Optimize overall
navigation and site 3 Reduce premature
site abandonment
usability

2 Enhance landing
page performance 4 Leverage content
affinities to enhance
online experience


Omniture Fusion
Page Effectiveness

1. Page and Content Identification
 Which pages contribute most to
an order taking place on the
(ClickMap) site?
4. Shopping Cart Performance
5. Payment & Fulfillment Methods  Which pages drive conversion?
6. Product Category Analysis
 What are the poorest performing
7. Product Finding Methods
pages?
 Order Participation
 Revenue Participation
 Page Conversion Rate


Page Effectiveness
Overview

Landing Content Cart Order Confirmation
Pages Pages Pages

? ?
 Purchase


Page Effectiveness
Use Case Examples

Measure the influence of site content on key success metrics


Page Effectiveness
Actions

1 Promote high-
converting 2 Maintain an
optimal mix 3 Identify and
remove “dead
content of content wood” content


Conversion and Acquisition Strategies Are Not Aligned

Conversion
Funnel Increase Conversion
Invest to make easier for
existing visitors to become
customers
NUMERATOR
$$$
DENOMINATOR
Drive Acquisition
Invest to acquire more customers to
Conversion site and push through funnel
Funnel


What Would Even a 1%
Conversion
Conversion
Funnel
Funnel
Conversion Lift Mean
For Your Business?

$$$


Understand you Visitors

Test

Target Segment


Landing Page A/B Test

Landing Page Order

Landing Page 1 $50
30

Landing Page 2 65

Landing Page 3 95


Testing to Optimize – Landing Pages

Converting 30% less
than general keywords
landing page

Goal: Increase “baby names” keywords landing page form completion


Results Summary

Conversion
Lift Confidence
Rate


Hundreds of Variables Make up the Personalized Visitor
Profile

Environment Variables
Site Behavior Variables
IP address Highly
Country of origin
Time zone
Customer/prospect
New/return visitor
Operating system predictive
Browser type
Previous visit patterns
Previous Product interests –
Screen resolution anonymous
top level
Previous Product interests –
low level Referrer Variables
visitor profile
Searches
Previous online purchases
Previous Campaign exposure Referring domain
Previous Campaign responses Campaign ID
Affiliate
PPC
Natural search
Direct/bookmark
Temporal Variables

Time of day
Offline Variables
Day of week
Recency Offline Purchases
Frequency In-store Activity
Service Activity
More…

23

Visitor Segmentation: Analysis

Passing a User ID for
each registered visitor
allows you to view who
is completing defined
success events

Using SAINT you can
group registered users
into segments


How it Works


Automated Targeting

Challenge: Results:
 To encourage visitors to drive deeper •250% increase in engagement
engagement and open new accounts.
•Revenue lifted by $1 million per quarter
 To deliver more relevant experiences
based on visitor information/behavior.


Hong Kong Web Analytics Wednesday #6

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