October 17, 2005, 12:00 AM

SPONSORED WHITE PAPER: Comparison Shopping Optimization: What Every Online Retailer Needs...

Channel Intelligence, Inc.
Published: July 2005

Comparison shopping sites and portals like Shopping.com, Shopzilla, CNET Shopper, Yahoo! Shopping and others can be very effective at driving highly qualified leads to a retailer`s online store. However, many online retailers fail to achieve these results due to data problems that limit the effectiveness of these marketing programs. Comparison Shopping Optimization is an ongoing process that significantly improves traffic, conversion rates and profitability from these sites – and provides the metrics to measure their success.

What is Comparison Shopping Optimization?
If a brick-and-mortar retailer flips through its Sunday circular and finds that one-third of its pages are blank, someone is going to get an irate call first thing the next morning. If the retailer realizes that some of its key products were supposed to be advertised on those blank pages, someone is going to get a really irate call that very moment. A Sunday circular would never allow itself to fail in this manner.

The same type of problem is happening every day to online retailers, but it has gone largely unnoticed. Comparison shopping sites and portals, like the circulars in the Sunday newspaper, allow consumers to research and compare products before selecting a retailer for final purchase. But in many cases, a significant number of products that the retailer chooses to display on these sites fail to appear at all or, if they do, the products may show up in a non-optimal location on these sites. As a result, the effectiveness of the marketing dollars spent at these sites is reduced, in some cases, significantly.

Comparison shopping sites attempt to ensure that their clients` products are listed properly. But with thousands of retailers and tens of millions of products available for sale, it is nearly impossible for each retailer`s products to get the attention they deserve. The volume and complexity of the data is too much to handle on this scale.

For this reason, the Comparison Shopping Optimization process was created. This process ensures that every product appears in the optimal location on each comparison shopping site. The process gives control of these marketing programs to the online retailers, not the comparison shopping sites. In fact, five of the top 16 online retailers listed in the 2005 Internet Retailer Top 400 are already seeing the benefits of Comparison Shopping Optimization.

Learning from the Failures of the Past

When online retailers struggle to succeed with a comparison shopping site, these are some of the common reactions:

1. Bidding for placement to improve product visibility

2. Eliminating product categories that appear to have low traffic or conversion rates

3. Completely removing all products from that comparison shopping site

4. Trying a different comparison shopping site (go to Step #1)

The problem with this approach is that the underlying source of the problem is not addressed. Until the product data is optimized for each comparison shopping site, the retailer will never achieve optimal results with these sites.

Once the root cause is solved, however, Steps #1 and #2 above are perfectly valid techniques to promote specific products or categories. Until then, these techniques simply mask the underlying cause of the problems.

Getting to the Root Cause – Data, Placement, Search

There are three components of a retailer`s product data that directly affect its success with comparison shopping sites:

  1. Accurate and Complete Product Data – Sending accurate product identifiers, such as model number, UPC, manufacturer name, ISBN, etc., is critical to ensure that all of the products appear at the comparison shopping sites. This is especially important for products like electronics, computers, books and video games.
  2. Correct Placement – Correctly categorizing products into the category tree of each comparison shopping site is necessary to ensure that the products are listed where consumers expect to find them. The retailer may decide to pay for better placement within that category, but the first step is to place each product into the correct category.
  3. Optimized for Search – Consumers find products at comparison shopping sites either through the navigation built into these sites, or through the product search option. Providing product data that is optimized for search will result in more consumers finding these products.

Data – The Universal Problem

Every retailer works to ensure their product data is accurate and complete, but this is a challenge in the online world. With the push for online stores to significantly expand their product catalogs, and the continuous introduction of new products, it is nearly impossible to achieve the goal of accurate and complete data for every product.

As a further complication, the data expected by the comparison shopping sites may differ from the data the retailer has in its systems. It is common for a product to be referred to by different model numbers and manufacturer names, which could lead to confusion for consumers, improper categorization of products and missed sales opportunities.

Comparison Shopping Optimization solves the problem of sending product data that is inaccurate, incomplete or simply different than the data expected by the comparison shopping site. This optimization process automatically "unifies" the retailer`s product data with that of the comparison shopping site. This translation process ensures that the retailer`s products appear at these sites.

Improved Product Placement without Bidding

Every online retailer and comparison shopping site places products into categories to provide an intuitive navigation method for consumers. Anecdotal evidence suggests that just over half of consumers use navigation to find products online, while the rest use search. Placing products into the correct categories is an essential online merchandising strategy. But incorrect or non-optimal placement is fairly common at comparison shopping sites due to the data being sent to these sites.

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