Here is a list of problems we identified:

• Campaign Structure = Display advertising, branded and non-branded keywords were all mixed together making it difficult to understand the true performance of CTR, conversion rate, spend, and return on investment.
• Low CTR = Major items affecting this were display advertising, large usage of broad match, poor correlation of ads to keywords that resulted in a CTR below .30%
• Low Conversion Rate = Major items affecting this were poor landing page selection, ads running on out of stock products, ads running on products with no images, ads running on products with high price points that resulted in a conversion rate below .75%

• Budget Allocation = Underfunding of top converting campaigns resulting in lose of exposure daily on top converting keywords.
• Effective Revenue Share (Cost / Revenue * 100) = Extremely High, above 45%.

Solutions we proposed and implemented:

First, we developed a new blue print for the account infrastructure using something we call a tree structure. The tree structure we constructed provided a framework that made for a more logical segmentation of the account by:

• Segmenting the campaigns based on branded and non-branded keywords.
• Once segmented into branded and non-branded we further segmented the keywords based on Dataqdirect’s manufacturers and product names.

The additional segmentation allowed us to better understand how CTR, conversion rate, and ERS were performing for branded and non-branded keywords.

Second, using a 3rd party software we constructed the following:

• Campaigns using the manufacturer name
• Ad groups using the manufacturer name + product number
• Keywords using manufacturer name, manufacturer name + product number, product number

• Ad Copy using regular price and sale price to show non-sale ads when the products were NOT on sale and sale ads when products were on sale.

Third, we migrated poor non-converting broad matched keywords to phrase and exact match.

Fourth, we ran a departing analysis to understand when their customers were shopping and buying their products. Using that analysis we day parted their account to run during peak visitation hours as well as increase their bids during peak hours of conversion.

Fifth, we ran a budget analysis identifying which campaigns were going dark. Using that analysis we realigned daily spend to top converting campaigns that were being underfunded.

Sixth, we setup automated bid management to pause and unpause keywords based the product stock levels. If products were out of stock we had the system pause the keywords. If the products were in stock we would unpause the keywords. Additionally we paused all products/keywords from the feed that were missing product images, until a time when images could be added.

Finally, we completely turned off their display network as it had a miserable return. The display campaigns were also combined with the search campaigns, making it difficult to understand the true performance of CTR and conversion rate..

The Results

Over a 5-month period Dataqdirect.com experienced a phenomenal turn around. They saw significant improvements in all major metrics. Below is a complete picture of the results:

• Revenue increased 50% YoY
• Conversion rate increased 90% YoY
• CTR increased 352% YoY

• Visits increased 23% YoY
• ERS improved by 77% YoY
• Average order value increased 139% YoY
• Impression Share increased by 73% YoY