www.tabcom.com/

solutions:

• Dynamic Site Accelerator
• Advertising Decision Solutions

DOWNLOAD TABCOM CASE STUDY

• Gained more in-depth understanding of purchasers' intent
• Drove new customer acquisition
• Boosted revenues
• Avoided need to implement tracking pixels

TABcom, ranked No. 230 in Internet Retailer's Top 500 Guide is a multi-divisional, multi-channel Internet-based company that focuses on the pet, equine, garden and green spaces. Based in Hazelton, PA, TABcom develops and maintains 'conscious lifestyle' Web sites that offer products, social engagement and interactive content for enthusiasts with a variety of interests. TABcom's family of Web-based brands include Dog.com, Horse.com, Garden.com, Groomer.com, Ferret.com, Fish.com, Bird.com, Petsupplies.com, Bike.com, Solar.com, and StatelineTack.com. Each month, 2 million unique visitors click through the over 5,000 sites under the TABcom umbrella.

In order to pinpoint which of its marketing channels were converting clicks to purchases and optimize results, TABcom wanted to develop a sophisticated online marketing program. What the company needed was a way to better understand site visitor behavior on each page of its sites. However, it didn't want to use tracking pixels.

Akamai introduced TABcom to its new predictive modeling services available through Akamai's Advertising Decision Solutions (ADS). This first-of-its-kind functionality is designed to enable retailers to capture up to 100% of their Web site audiences, without the use of IT-intensive pixel implementation. Plus, pixel-free implementation optimizes site performance and enables more robust predictive modeling with richer data.

Because pixel-free implementation is powered by Akamai DSA, it can be automatically enabled for every end-user interaction with TABcom's Web sites. According to Pfeifer, this architecture has allowed the e-tailer to capture larger audiences and more site visits, in turn, providing a much richer set of data to model against. "Instead of only capturing purchases and browsing behaviors at a high level, the pixel-free approach enables modeling at the product category and product detail level, providing us with a much more in-depth understanding of a purchaser's intent."