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As manager of the search engine optimization (SEO) strategy for several multinational com-panies over the last seven years, I have seen this industry undergo significant evolution. Yet it still amuses me to peruse the SEO “help wanted” ads on Craigslist to see the perceptions people have about search engine optimization.
People seeking to hire SEO expertise sometimes envision their site ranking #1 on Google for certain keyword phrases. For example, here is an excerpt of one ad I saw recently:
“I will pay $1,000 if I see our … keywords TOP in Google and Yahoo.”
My first question is, “Which keywords?” If the keyword is “Camry,” there are currently 7,600,000 other pages in Google competing to rank for that word. If the keyword phrase is “Toyota Camry,” the number of competing pages drops to 1,620,000. And if the keyword phrase is “2007 Toyota Camry,” the number of competing pages drops to 723,000, less than one-tenth the number of pages competing for “Camry”. Fewer pages competing for a term means the term should be easier to rank #1. Is the prospective employer from Craigslist willing to pay $1000 to see his site rank #1 for a word like “Camry” or for a phrase like “2007 Toyota Camry”? There is a 10x difference in the amount of competition for these words.
Similarly, there is a vast difference in the traffic one could expect to receive from searches for these terms. The following chart from Google Trends shows the relative number of searches for the three different keyword phrases discussed above. There are more search-es for “Camry” than for “Toyota Camry,” and there are more for “Toyota Camry” than for “2007 Toyota Camry.” For this example, it is intuitive that ranking #1 for “Camry” would drive more traffic than ranking #1 for “2007 Toyota Camry.” Are both #1 rankings equally worth $1,000 to our prospective employer above?
Furthermore, which searcher is most likely to actually purchase a vehicle? Intuition and experience agree that it is the one searching for the most specific term, i.e. “2007 Toyota Camry.” A more hyperbolic example would be the difference between someone searching for “car” and someone searching for “2007 white Toyota Camry with sunroof Austin, Texas.” The more specific term is closer to the point of sale.
This analysis is a very simplified view into the long tail of search, i.e. the collection of search terms that are only used a few times each, but which collectively account for more traffic than the top keywords for any site. Your best bet for driving long-term, highly-converting search traffic lies in effectively targeting terms that are close in proximity to purchase intent. Even though your competition may be driving up the costs of customer acquisition within the top 20 percent of searches, most of your potential for growth in traffic and sales lies in the bottom 80 percent. How to go about growing traffic and sales in that bottom 80 percent is the question marketers should ask.
In an August 2006 report, Jupiter Research found that 77 percent of online shoppers use product reviews and ratings1– that is, reviews written by other consumers - when purchasing, and a recent Yahoo! and comScore study found that 76 percent of brand advocates use search engines to research products prior to making purchases.2 The popularity of product reviews among shoppers coupled with the usage of search engines to conduct pre-purchase research has resulted in an interesting symbiotic relationship between search traffic and customer reviews.
In this report, we examine the impact of consumer-generated product ratings and reviews on the natural search traffic to the websites of 21 retail brands, ranging from consumer electronics to apparel to sporting goods. We consider “natural” search traffic (as opposed to “paid” search traffic) to be the referrals from a major search engine like Google, Yahoo, or MSN to a brand’s web page. We find the following:
Search engine queries to review content are substantially more likely to use “generic”, rather than “retailer-specific” words, which indicates that review content outperforms product content in driving first-time customers to a retailer.
Search engine queries to review content contained about 1.5 words per query more than queries to product content. The longer query strings indicate that review content does a better job than product content of driving higher-converting visits.
Referrals from ratings and reviews content generate 97 percent more revenue per referral than referrals from natural search engines to product pages.
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