How To Model Search Term Data To Classify User Intent
Query data is the first tool in every search marketers arsenal – it serves as a launch pad for developing information architecture, understanding market opportunity to creating landing pages with carefully worded ad copy to maximize conversions. To fully understand query data in any market segment, it is extremely valuable to understand and creating a model of search behavior.
A search behavior model is a data-driven process for classifying user intent for each search query to a specific source, type or subject. It’s a reflection of the total consumer search experience for products and services in any single market segment. Read more about Search Behavior Models here.
The Self Publishing Industry As A Test Model For User Intent
The ubiquitous spread of the Internet and the decline in the cost of printing books in small volumes has given rise to a growing online vanity publishing business. Memoirs and family genealogies are now easily preserved for future generations at a very reasonable cost. Family photo books are easily created, and if you are a budding short-story or fiction writer you have more publishing options than you ever had before.
When you examine the full data set of 800 queries (extracted from AdWords) for self publishing, you find that it accounts for about 20 million searches every month. The first thing you notice in this data is the relatively small numbers of keyword searches for a company brand name. In my opinion, this may reflect low brand awareness in consumers’ minds for self publishing services.
There is also potentially a lot of noise in this data – many of these queries are about mainstream publishing, and reflect interest in traditional products and services. However, I think consumers often start their search for self publishing services with the more traditional publishing houses because there is very little consumer brand awareness around the concept of self publishing.
Understanding Search Behavior By Hierarchy
There are 20 high-level categories of search behavior found in these queries. Usually, you can identify two or three top categories (by search volume) that provide potential for information architectural focus. This model is different. A couple of the sub-groups in the type and informational categories are useful to information architects (IA), but not all of them. The whole source and transactional categories are focused enough to be exploited by IA’s as landing pages.
Sub-Categories Steer Behavioral Choices
When you look at sub-categories, the count rises to 29 behavioral patterns with type being the most interesting and varied. It’s worth looking at some of these sub-categories because they provide several landing page opportunities. In particular, How To and POD (print on demand) stand out.
Unique Assets In The Self Publishing Model
This is one of the more complex models I’ve ever seen. The large number of categories was a surprise, and many of them are not particularly useful in a self publishing context. However, there are a few off-topic categories that can be exploited. For example, when consumers are searching for a publishing company, (1.46 million searches) they are not specifying a genre, a type of book or even stating they are interested in self publishing.
These searchers are looking for an unnamed publishing company to provide an unknown service. It’s a good bet that these people are interested in publishing a book, but have not considered self publishing as an option. It is possible that some of this traffic can be converted with a “If you are looking for a publisher, consider Self Publishing” micro-site.
The following model is displayed in descending order by traffic volume with Information having the most, and Quality having the least. At a glance, you can see that consumer search complexity is focused in the information, type, transactional and value categories.
To finish reading this article go to Search Engine Land where I first published this analysis.
Find Out More
If you are interested in finding out more about Search Behavior Models send me (Mark Sprague) an email at: Mark@MSprague.com, or call me now at: 781-862-3126
About Lexington eBusiness Consulting
Mark Sprague’s 25 years of product development experience, which includes expertise in Search Engines, Information Products, SEO platforms and Social Networking applications provide in-depth expertise to help you refine products and services, and improve your websites performance by:
- Developing a superior data-driven SEO strategy for your website.
- Understanding your customers’ search behavior and normalizing it to your content strategy.
- Understanding how search engine technology practically impacts SEO and content strategies.
- Understanding how search technology impacts content in a social networking environment.
- Developing a superior user experience based on sound information architecture, usability and coding standards.