CPC Strategy has begun another series titled “What Is?” aimed to help new and experienced merchants revisit their data and optimizations strategies for being successful on comparison shopping engines (CSE’s).  Our first post offered an overview of data feed quality and touched on some important optimization tips that will help merchants improve their data.

Categorize your products according to each engine’s taxonomy. Consult the list below for engine-specific categories and subcategories.

Google Product Search

Amazon Product Ads

Each shopping engine supports either a specific category ID or a unique category name.  Make sure to reference the links above to find out which shopping engine requires which.  For CSE’s like Google Product Search and PriceGrabber that employ category names, use the > delimiter to separate top-level categories from subcategory and so on:

Electronics > Audio > Audio Accessories > MP3 Player Accessories

If you have a product that qualifies for more than one category, Google Product Search allows merchants to submit multiple product type attributes.  To do so, surround each category with double quotations and separate them with a comma:

“Electronics > Audio > Audio Accessories > MP3 Player Accessories”,”Health & Beauty > Healthcare > Biometric Monitors > Pedometers”

This gives a particular product visibility in multiple categories on Google Product Search.  After a shopper places an initial search for, say “pedometer”, they can filter their results by category.  If your data feed includes multiple categories for a product, you can maximize visibility and show up under multiple filters (i.e. Biometric Monitors and MP3 Player Accessories).

For the paid CSE’s, cpc rates will fluctuate by category and subcategory.  Disregard the wavering cpc rates when categorizing your products and focus on where your product is most relevant.  Although one category may sport a higher cpc than another, it will typically drive more qualified traffic which will lead to better conversion.  Placing  products in a category such as “Miscellaneous” to take advantage of a lower cpc is not cheating the system; it’s cheating your ROI.

Also, avoid categories such as “Gifts” or “New Items.” CSE’s see this information as useless.  Be specific.  In what category(s) does your product fit?

Categorization tips

We understand that categorizing your data feeds can be overwhelming so we’ve included some tips to help merchants tailor their inventory to each shopping engine’s taxonomy.

  • Search Your Products on the CSEs for Ideas – To get a better idea where a product should be categorized, do a search for that product on a particular engine. This will show you where your competitors are advertising similar products and where your products will have the most relevant impact.
  • Populate Fields Initially – Use the most generic category to populate each product.  If you’re a merchant that sells bedding on Shopzilla, categorize each item under “Miscellaneous Bedding”.  This ensures that you don’t leave any category fields blank when you send in the feed.
  • Leave a Trail of Breadcrumbs – After you find a general category for each product, go through and add engine-specific subcategory data to them. For instance, for products in the “Bedding” category, narrow your scope to isolate those that are bedskirts, bedspreads, etc. and add the appropriate category ids.  Excel’s autofilter function is extremely handy here.

A merchant can use Excel’s autofilter function to sift through their internal categorization and match products to each shopping engine’s taxonomy.  Identify the products that fall within the scope of a top-level category by filtering certain keywords that directly correlate to that category.  Further refine your filter to isolate various product subcategories until you have the most detailed category names and IDs possible.

For more information, download our free CSE eBook or contact us with your questions.

About the Author+David Weichel is the Director of Paid Search at CPC Strategy. He specializes in conversion rate optimization, search behavior research and attribution analysis. David graduated from the University of California, San Diego with a B.S. in Management Science. See all posts by this author here.