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Dell.com Landing Page Test
MGMT 461.42 - Online Analytics & Measurement
UCI Extension – Summer 2013
By: Corinne Blair 1 September 2013
DELL.COM| LANDING PAGE TEST
OPTIMIZATION PROJECT
OVERVIEW
Dell.com Summer Clearance PC Sales Landing Page from sponsored PPC ads is a top landing page with high traffic
levels, yet struggles to generate a strong conversion rate.
The goal is to increase Summer Clearance PC Sales among online shoppers. An A/B split user experience test will
be implemented to evaluate the best way to increase landing page click-through rates, increase product page
views, decrease bounce rates, and complete the sale conversion.
There are two types of Summer Clearance Sale sponsored PPC landing pages – Electronics and PC. Both pages are
top landing pages with a high level of traffic. However, the bounce rate for the PC sales landing page is over 30%,
while the Electronics sales landing page has a strong conversion rate.
The design treatment of the Electronics clearance sale landing page is different than the PC clearance sale landing
page. So, the goal of the A/B split test will identify which version of the landing page design delivers the desired
conversion outcome from the sponsored PPC referral source.
The test will target visitors who come to the landing page via sponsored PPC ads on search engines - Google.com,
Bing.com, and Yahoo.com. The traffic will be split in half – 50% Version A; 50% Version B
The page treatment that generates a higher user engagement will be adopted as the winner experience for PPC
landing page.
The design template below reflects Version B. However, the following copy and product images changes are
needed to prepare the landing page for testing:
 All references to “Electronics” will be changed to “PC”
 “Electronics up to 87% off will be changed to match the offer copy on Version A “up to $370 off select PC”
 Product images will be replaced with relevant PCs sales items - Laptops, Desktops, and Ultrabooks.
PPC Landing Page - Version A
PPC Landing page - Version B
Dell.com Landing Page Test
MGMT 461.42 - Online Analytics & Measurement
UCI Extension – Summer 2013
By: Corinne Blair 2 September 2013
DETAILS
Test start date: October 1, 2013 (proposed)
Duration: 2 to 3 weeks – depending on data set gathered from traffic.
Country: US only
Target audience: Visitors from sponsored PPC Ad featured on prominent search engines – Google, Bing and Yahoo
SUCCESS METRICS
1. Increase click-through rate to sale product pages
2. Increase completion of sale conversion
3. Increase time-spent per visit
4. Average Order Value
TRACKING REQUIREMENTS
Use Hitwise to track all sources of search engine traffic.
Track Test ID into a tracking variable.
Track the Treatment ID for each treatment into a tracking variable.
GA
We will be setting a visit-level custom variable for tracking the Test Name and Treatment IDs
This is the format we would use:
_setCustomVar(index, test name, treatment ID)
You can find additional instructions on how/where to make this call, here:
http://code.google.com/apis/analytics/docs/tracking/gaTrackingCustomVariables.html#setup

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Dell.com Landing Page Test Recommendation. By Corinne Blair. Online Analytics & Measurement - UCIrvine Extension - Sept. 2013

  • 1. Dell.com Landing Page Test MGMT 461.42 - Online Analytics & Measurement UCI Extension – Summer 2013 By: Corinne Blair 1 September 2013 DELL.COM| LANDING PAGE TEST OPTIMIZATION PROJECT OVERVIEW Dell.com Summer Clearance PC Sales Landing Page from sponsored PPC ads is a top landing page with high traffic levels, yet struggles to generate a strong conversion rate. The goal is to increase Summer Clearance PC Sales among online shoppers. An A/B split user experience test will be implemented to evaluate the best way to increase landing page click-through rates, increase product page views, decrease bounce rates, and complete the sale conversion. There are two types of Summer Clearance Sale sponsored PPC landing pages – Electronics and PC. Both pages are top landing pages with a high level of traffic. However, the bounce rate for the PC sales landing page is over 30%, while the Electronics sales landing page has a strong conversion rate. The design treatment of the Electronics clearance sale landing page is different than the PC clearance sale landing page. So, the goal of the A/B split test will identify which version of the landing page design delivers the desired conversion outcome from the sponsored PPC referral source. The test will target visitors who come to the landing page via sponsored PPC ads on search engines - Google.com, Bing.com, and Yahoo.com. The traffic will be split in half – 50% Version A; 50% Version B The page treatment that generates a higher user engagement will be adopted as the winner experience for PPC landing page. The design template below reflects Version B. However, the following copy and product images changes are needed to prepare the landing page for testing:  All references to “Electronics” will be changed to “PC”  “Electronics up to 87% off will be changed to match the offer copy on Version A “up to $370 off select PC”  Product images will be replaced with relevant PCs sales items - Laptops, Desktops, and Ultrabooks. PPC Landing Page - Version A PPC Landing page - Version B
  • 2. Dell.com Landing Page Test MGMT 461.42 - Online Analytics & Measurement UCI Extension – Summer 2013 By: Corinne Blair 2 September 2013 DETAILS Test start date: October 1, 2013 (proposed) Duration: 2 to 3 weeks – depending on data set gathered from traffic. Country: US only Target audience: Visitors from sponsored PPC Ad featured on prominent search engines – Google, Bing and Yahoo SUCCESS METRICS 1. Increase click-through rate to sale product pages 2. Increase completion of sale conversion 3. Increase time-spent per visit 4. Average Order Value TRACKING REQUIREMENTS Use Hitwise to track all sources of search engine traffic. Track Test ID into a tracking variable. Track the Treatment ID for each treatment into a tracking variable. GA We will be setting a visit-level custom variable for tracking the Test Name and Treatment IDs This is the format we would use: _setCustomVar(index, test name, treatment ID) You can find additional instructions on how/where to make this call, here: http://code.google.com/apis/analytics/docs/tracking/gaTrackingCustomVariables.html#setup