Beneath the Surface of Search Jan 1, 2007 12:00 PM
, By Brian Klais
JobZone
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If you are like most merchants, you've followed the advice of your natural-search optimization (NSO) firm and completed some basic site optimization projects. You routinely spot-check your Google indexation and your rankings on 100 or so “trophy” keywords to show your executive team. And a look at your Web analytics shows that sales driven by your natural-search efforts are growing. So what's wrong with this picture?
The problem is that you are looking only at the surface of the situation, oblivious to something gigantic that lies beneath. To explore deeper, you need more-sophisticated tools and methods to understand and diagnose the opportunity so that you can take appropriate action. In fact, chances are high that your natural-search channel is seriously underperforming.
As NSO best practices become commonplace among your competition, you need to look deeper to gain an advantage. Fortunately, by approaching natural search with an understanding of long-tail dynamics, new key performance indicators (KPIs), and yield management techniques, you can move beyond the traditional project-based mentality of NSO to a more-sophisticated approach to capture the enormous potential that lies beneath the surface.
The long tail of natural search
To understand the KPIs and management techniques, let's examine what lies beneath the surface: the long tail — a common statistical distribution featuring a tail-shape curve, as in the chart below.
In the long-tail graph, the Y axis is Website traffic as measured in hits, and the X axis represents unique search terms. Traffic from branded search term accounts for the spike at the far left side of the graph. Traffic from unbranded search terms is visible as you follow the graph farther to the right.
According to a research report, “Chasing the Long Tail of Natural Search,” we at Netconcepts recently published, for every search that occurs for the average merchant's brand name, nearly 40 relevant searches occur for more-generic, brand-neutral keywords.
For instance, if there are 100,000 searches for “L.L. Bean” this month, there are an estimated 4 million searches for hundreds of thousands of “unbranded” keyword markets that L.L. Bean pages could compete within: “furniture slipcovers,” “women's flannel pajamas,” “men's reindeer sweater”… The matching category or product pages on www.llbean.com ideally could position the L.L. Bean brand high enough in the search results to win these millions of click decisions — and sales — on the cheap. And even if these pages do not convert 100% of these searches into clicks, if they are well ranked the pages could nonetheless build brand by association with these millions of corresponding “unbranded” searches among the searchers who used the terms.
This is the long tail of natural search — the universe of diverse, unbranded keyword markets that, while perhaps not as frequently searched on an individual basis, cumulatively, add up to hugely greater search potential than the branded search traffic that most merchants naturally receive. This long tail is the prize every savvy merchant seeks.
Because brand popularity is relative, a more objective way to think of this long-tail potential is as a function of your Website size. Our research suggests that for every unique page on a merchant's site, nearly 100 unbranded searches are conducted in an average month. If you have a 20,000-page Website, your long-tail potential would be calculated as 2 million unbranded searches. Tracking your unique pages and their yield is therefore a critical measurement to understanding the dynamics of your natural-search channel performance.
Capturing the elusive tail
The long tail of unbranded keywords is a new concept for most marketers to grapple with. What drives it? How do you quantify it? What is good performance? What is bad? How do you capture it?
To answer these questions, we developed what we refer to as page yield theory. It aims to break down, quantify, and model the components of a merchant's long tail into manageable units and was developed using natural-search data gathered from a few dozen top online merchants using our GravityStream natural-search optimization proxy technology. In the process, we developed a set of metrics to understand the dynamics of the long tail. We then used the results to develop seven KPIs for the natural-search channel.
KPI #1: BRAND-TO-NONBRAND MIX
What percentage of your natural search comes from brand keywords vs. nonbrand keywords? What does it mean if your keyword curve is dominated by brand terms? If most of your traffic is coming from searches for your brand, this is symptomatic of a larger problem lying just beneath the surface: Very few of your pages are actually yielding traffic.
Many retailers find that 95% of their search traffic comes for brand terms, with — not coincidentally — a small percentage of their Website powering that brand traffic. Once you've done some search optimization, however, you should find a very different distribution curve. For instance, you may discover that 40% of your pages are yielding traffic, and that 60% of that traffic is unbranded keyword traffic. This in fact is the core hypothesis of page yield theory: Unbranded-keyword traffic volume grows as the number of pages yielding natural-search traffic grows.
