This is the first in a series of posts reflecting on the Google ‘Panda’ Update’s impact on search marketing and how it has re-defined the industry.
The search industry was rocked in late February of 2011 with Google’s now-infamous Panda update to its ranking algorithm. Affecting a whopping 12% of queries, traffic drops were so drastic for some domains that many of those sites penalized were pushed to the brink of financial viability. Many more businesses and their associated websites folded up entirely.
For those of us in the industry who understand the importance of diversified traffic referrals to a website, it’s hard to sympathize with those business models whose sole source of revenue is centered upon organic search referrals. At the same time, it did leave many questioning what we could learn from the toxic content and traffic that caused these sites to be affected.
Upon further examination of several affected sites, one of the main parallels we found were sites ranking for queries they had no business ranking for in the first place. Much of this begins at the query level and a deeper understanding of keywords, connective phrases, and the user’s thought process behind why they entered them into a search bar in the first place.
Learning from Queries
When you break it down, we’ve realized that there are a few different classifications that we can assign queries (a practice Google confirmed is ongoing en masse with user experience data collection). Google has their own system, but for our purposes we’ve broken these queries down as Advanced and Intermediate.
If we back out the idea of search as information retrieval, and begin to look at queries as questions, you can reverse the cognitive process to understand the different types of questions that are being asked. This should provide us a baseline as to the best types of content to answer those “questions.”
Advanced terms are your “what is _______?” queries, of which there are sub-classifications. It is assumed that at least some of the search term elements within the query exist outside the general conversational vernacular. In most cases, content on landing pages for this type of query traffic should provide the best baseline overview of the query topic.
These are queries performed by those seeking a comprehensive description for a term or connective phrase they likely have little knowledge of beyond its spelling.
For example, a search for “African armyworm,” a type of crop-eating African moth, is likely performed by someone who is simply looking for information on a relatively non-distinct species.
These queries are second tier terms with qualification elements. It is assumed that the user has internalized the meaning of an advanced-investigative level term and is simply seeking the next level of specific information. When creating content for these queries, it is important not to re-hash descriptive or overview material.
An example of this would be “African army worm insecticide,” which would infer the searcher already knows “what” the African armyworm is, and is now seeking clarity on how to kill the buggers.
These queries are those that contain obscure or professional jargon. It’s important in many niches to consider these terms when assessing the general sophistication of the copy language.
Following our model, an example of this type of query would be “Spodoptera exempta,” which refers to the Latin species name for our friend the African armyworm.
Intermediate Level Queries
Intermediate level queries consist of known terms and connective phrases. These too, can be broken-down further in a few different categories. All intermediate level terms can be appended by location.
These are widely known terms or phrase-queries around which a user is likely seeking the most up-to-date information about a familiar topic. In addition to general overview material, content created around these phrases should be current and support what exists in the public discourse.
For example, a search for “milwaukee brewers” is likely performed by a person who’s knowledgeable of the baseball team, but is probably looking for scores, roster information, etc.
These are services and products that people would utilize web search to find. These are often appended with location variables. Content should support quickly connecting the user with precisely the service they seek for the location variables they may use.
Keeping with Wisconsin’s favorite boys of summer, an example for this type of query might be “Milwaukee Brewers jersey sales,” which seeks a product-type site related to a known entity.
These queries contain a number of known elements, but are generally tied to a specific time, place, or event.
An example would be “brewers spring training scores.”
Translating Search Intent into Quality User Experiences
Once we establish the types of queries a site is receiving traffic from, it’s important we ask ourselves two questions:
1.) Does my site honestly deserve traffic for this search term?
2.) If so, does my page accurately answer the query in such a way that creates a positive user experience?
Bounce rates, time-on-page, and common sense can answer question number one for you. If the answer is no, remove the content. Toxic traffic is a major signal to Google’s Panda system that the page is irrelevant, of poor quality, or not satisfactory with regards to the query- all of which translate to poor user experience.
As for question number two, first classify the types of terms that are garnering search traffic to your site then decide if you’re satisfying the query. Are you answering questions? Are your visitors arriving and leaving or migrating to different parts of your site? For general-level (advanced-investigative) terms, use this as an opportunity to drive them to the more qualified areas of your site. Allow entrance pages for these terms to dictate your information architecture. Don’t restrict interpretation of content as simply page copy; consider the use of bulleted lists, multimedia elements, or other data visualizations to satisfy queries.
Traffic, in and of itself, is not a means to an end. Furthermore, the content arms race is over. Relevant, qualified traffic translates to qualified and predictable user engagement with your site and its content.
If Panda has taught us one thing, it is that the role of the search engine optimizer has largely been redefined. The search spider’s experience and the user’s experience with your content are no longer mutually exclusive events, and by necessity, the SEO’s goals and the goals of the search engine are slowly marrying one another. True optimization from here forward means merging the traditional tenets of SEO with those centered on optimization of human experiences, understanding full well that the line between the two is vanishing.