Executive Summary Average order value (AOV) is one of the most important key performance indicators for any ecommerce business. And online marketers who use AOV to discover new visitor segments will see an immediate impact on their bottom line.
There’s plenty to be said about AOV for common customer segments—such as new versus returning visitors, or shoppers with an affinity to a brand/category—but to achieve long-term revenue and growth, successful ecommerce businesses will identify customers who spend the most money and get them to buy again and again. As website traffic continues to make a drastic shift from traditional desktop and laptop computers to smartphones and tablets, EQ2 2012 takes a look at two visitor segments—platform type and inbound traffic source—that stand out as potential game-changers.
Lastly, EQ2 2012 tells the real story behind web browsers. While the amount of visitors accessing websites via traditional methods plummets, one web browser has nabbed a significant portion of market share and left the once-mighty Internet Explorer in the rearview mirror in a unique and revealing way.
ABOUT THE EQ
As ecommerce companies look for ways to increase customer engagement and sales in a highly competitive online shopping environment, they’re faced with challenges centered on massive amounts of data. This Big Data conundrum extends beyond the collection and storage of information about customers and prospects; the critical component of business intelligence is the ability to transform this never-ending stream of data into meaningful insights to create more relevant shopping experiences.
Managing this data is a big part of delivering relevance. Using a combination of historical and real-time data to target each website visit can delight customers who then become extremely loyal and share their experiences with others. Ecommerce businesses that tackle Big Data head-on focus their attention on three primary visitor segments, groups that will be explored (with examples of each) in every release of the EQ:
• Predefined: New versus returning; referring traffic sources; technographics; geography.
• Custom or Proprietary: Demographics;proximity to location.
• In-Session Behavior: Shopping cart activity; brand or category affinity.