You’ve worked hard to merchandise those great gifts for Christmas. So why would you hide them from shoppers looking to buy something special for their loved ones?

That is just what some retailers are doing as they send their well-intentioned product data feeds to comparison shopping engines.

Proper placement of a seller’s products on comparison shopping engines can make the difference between success in product sales and invisibility (and worse, the expense of curiosity clicks). It all begins with the product data.

Currently two major methods are used for mapping a retailer’s product data to the comparison shopping engines: category-level mapping and Product-level mapping. You’ll want to use a Product-level mapping system to make sure your products gain maximum visibility among the shoppers who are looking for them.

Here’s why. The basic difference between these two methods for mapping products can be found in the level of detail used to determine the categories where a retailer’s products should appear. Product-level mapping looks at each product to find the correct placement, while category-to-category mapping examines only the category names, assuming that all categories at retailers and comparison shopping engines are the same.

Retailers who use mapping at the Product-level are much more likely to see every product found in its optimal place at each comparison shopping engine, regardless of any differences in category names.

The assurance of proper product placement is possible because Product-level mapping provides intelligence based on the actual products found in each category for both parties, not simply forcing the match based on category names. It can see that a toy TV for children belongs in the toy category, where parents shopping for their children will find it, not in the broader electronics category where a product defined as a TV would normally be found.

The categories found on retailers’ web sites are as unique as their products and many cannot map directly to the categories found on the shopping engines, whose categories also vary from one to another. Also consider categories used for marketing promotions, like “gifts for her” and you are certain to see not only categories that don’t match, but also products that would benefit from being listed in a different category when mapped to the shopping engine.

Product-level mapping helps to support a shopping engines’ online plan-o-gram. Image the brick and mortar world for a moment. What are the odds that a department store, for example, would merchandise bath towels with children’s apparel? Not likely, because it would make for an odd shopping experience for the consumer. Plan-o-grams are designed to help store merchandisers group like products together for easy discovery by the consumer.

This is the same strategy used by shopping engines and their respective taxonomy structures. Marketing categories used online should be thought of like end caps in a store. End caps are used to help decorate or advertise certain products, while leaving the majority of the actual product units in their correct store location.

So what happens to those products in a category unrecognized by shopping engines? They are essentially sentenced to doom, filed under “miscellaneous”, which functions as a catchall category on many comparison shopping engines for retailer product categories that don’t match. How many shoppers searching to buy a set of golf clubs do you expect will click over to the “miscellaneous” category - especially when your competitor’s products are showing under the more appropriate comparison shopping engine category of sports gear?

It’s also common for retailers to have products appearing in inappropriate categories within their own taxonomy. Category-to-category mapping of those products cannot address this issue the way that mapping on an individual product level can.

The specification of product attributes, now required by several comparison shopping engines, is more comprehensive with Product-level mapping, which can work to identify contextual attributes (what a product is) in addition to derived attributes (what it is used for). That means a seller’s products can benefit from association of a more attributes that are more appropriate, and in turn show when shoppers narrow down or filter their product search using attributes on a shopping engine.

As an added benefit of Product-level mapping, accurate product-level analytics normally unavailable with category mapping can be seen clearly by marketers, aiding in effective decision making. This context of performance relative to other products, categories, and comparison shopping engines provides a basis for making informed decisions on a strategic level.

To sum it up, effective use of comparison shopping engines begins with ensuring good product data. Then, with this basis in place, retailers can enjoy the benefits of properly placed products and make decisions based on accurate performance data.

By Rob Wight, President and CEO, Channel Intelligence

Access this article at the Channel Intelligence web site:

Published on: 12:00AM on 30th October 2007