Optimization Pt.1

Channel and Data Feed Optimization

To properly speak about optimizing, we need to first break this apart into 2 discussions. The first will revolve around data. Data refers to the actual information being sent to the shopping comparison engine or marketplace. This data needs to conform to the destination site and this means the comparison engine data may look very different than the data taken from the origin website or merchant platform. The second portion of optimization revolves around product selection and return. I am not aware of any merchant who sees equal profitability on all products. Many products will loose money no matter what is done to the data, and essentially should be removed. Product selection should ultimately be determined by the often misunderstood Holy Grail of web marketing, ROI (return on investment) or ROAS (return on ad spend).

1. Product Data

Product data is defined for this article as any type of data relating to the listing and display of an item for sale. Product Data is different for each product and includes everything from product name, to product sku, to product description. The biggest misconception about product data is that it if a successful formula is found on a merchant’s website, this formula or structure should be the same across all selling channels.

INCORRECT! Actually, product data should be changed and altered based on the destination site. Every good public speaking or writing class will emphasize either speaking/writing based on the audience. CSE’s and marketplaces are the same. Each is a different audience and the information needs to be changed for that audience.

I am going to skip past basic manipulations such as indicating information such as ‘In Stock’ or what type of shipping is available. This should be an automatic first step, but finer adjustments are best illustrated by the description field and product name.

Product Attributes

A big deal is being made about product attributes as the future of data structure. Attributes are an important piece, and engines like Shopzilla and Google Product Search are turning to attributes as a way to classify products accurately across millions of skus. The best way to show how these fields come together is using Shopzilla. Shopzilla/Bizrate uses the name and description fields to place products using product attributes.

Shopzilla has a pre-defined list of product attributes that look like categories, but are in fact, attribute groups. There is no category id or category indication that can be made to place products in these groupings. The attribute terminology must be present in the name and description fields.

In the example show below, if a merchant sells golf clubs, and has a set irons for sale, the should absolutely make sure the term ‘iron set’ is included in the product name, description, or both. Using this term allows Shopzilla to correctly identify this set of golf clubs as an iron set, and will then place the clubs in the proper group. If a merchant uses a term like ‘set of irons’, this will not place highly and may not even find its way into the ‘Iron Sets’ group.

Using the correct Shopzilla category id when sending these items, cat id#12070300, is advised, but this will only take a merchant so far on this engine. By changing the product names and descriptions to match what Shopzilla is looking for, a merchant will see much more targeted traffic and then more sales.

Creating New Customized Data

Another possible manipulation would be adding a short description specifically geared for Shopzilla. Since in this example, Shopzilla is only displaying the first 50 characters of the description, most of the website description is never even seen by the consumer! As we have already pointed out, the engine in this case is using the description field mostly for placement, so what if for the first product, a description was instead set like this, where bold characters are within the first 50 characters to be displayed, and the rest is for placement:

Free Shipping on Orders over $50. Thousands of clubs available. Callaway Golf 06 Big Bertha Iron Set. S2H2, Tru-Bore and VFT — are part of the DNA of Big Bertha Irons. Add extreme Notch Weighting, a deeper 360-Degree Undercut Channel and a constant-width sole.

These are just a couple examples of data optimization. Many more are possible and advisable. For example, the actual ranking of these items on Shopzilla are determined by many factors including relevance to the group or search term, participation in the customer ratings program, price, and bid amount. Of course, data is just one factor in optimization, the next are is in regards to product selection and return on ad spend.

*In the below illustration, a search was made on the Shopzilla.com home page for ‘golf clubs’. Then when the selection came up, the prospective customer clicked on ‘Iron Sets’. The arrows indicate the ‘Iron Sets’ attribute grouping and then where the term ‘iron set’ is used the product names and descriptions to have products come up in these sections. Actual merchant names have been hidden. Click on image to enlarge.

June 23rd, 2007