Market research queries – used thoroughly and with artful sensitivity – can identify a market’s key publishers, key content, key audiences and define the pains and passions that make that market’s participants a cohesive entity. Marketers who develop a methodology for classifying, collating and documenting their market queries facilitate, speed up and create meaningful work segmentation opportunities at all stages of a content marketing campaign.
This article outlines not a methodology, but the elements I believe are required for developing your own methodology. I recommend recording these “elements” in a spreadsheet, which is for now the most effective way of making these query elements portable.
First and foremost some definitions for those who may be new to using queries thoroughly for prospect discovery and content ideation.
1) Market Research Queries
I’ve written lists and lists of “link building queries” in the past – these are examples of market research queries designed to find a particular type of prospect at large scale. I’ve also begun creating lists of content research queries – when content marketers and brand journalists use these at scale they can catalog a market’s entire body of expertise. Market research queries, when used for large scale research (typically with a SERP scraper), provide fast and effective market entry and expansion intelligence.
Classification, as I understand the library science sense, involves surveying a body of knowledge or other information and determining logical categories. From a prospecting and content research perspective I’ve found this to be an ongoing process, and one that differs from market to market. This is what makes a methodology, as opposed to blanket market classifications, so important.
Collation, again as I understand it from the school of library science, involves the logical ordering of your categories. Collation is a unique and important opportunity for marketers, for frequently the biggest, quickest contributions one can make to an existing body of knowledge is simply to create a more meaningful and useful order. You will begin to discern these opportunities as you collate your market research queries.
So What Gets Recorded?
I’ve taken to recording my most-valuable queries in client reporting sheets – this is my way of remembering what worked, where I’ve looked already, and suggestions for the next time I’m searching for prospects. Of course at large and thorough scale this method falls apart, which necessitated my inquiry. For marketers seeking to preserve their valuable query experiments and discoveries it’s important to disect a market research query to look at its various parts. Consider these potential columns for your market research query spreadsheet.
Market research queries may not make sense outside of the context of the project for which they were devised. Keeping track of the project or client or initiative for which you generated queries and their pieces will help you better understand how to make use of them in the future.
2) Query Roots
Query roots are primarily the names of your target audiences or target markets. Query roots are typically useful for both content promotion opportunity discovery AND market expertise extraction. I’ve previously identified 7 types of market query roots. And it’s because I kept coming up with more that I realized I needed to speak to methodology rather than simply classifying and collating my findings. Researchers will find that markets have fewer roots than stems.
3) Query Root Audience Type
In some cases it will make sense to create classifications based on audience type, market segment or persona. This will help you in the future as you return to your previous work hunting for that perfect query root you’ve used in the past! Some sample query root audience types can focus on skill level – such as beginer, intermediate or advanced. Others could include small, midsized or enterprise companies. There are often – though not always – different query roots for each of these types. If you’re experienced in categorizing SEO keywords then this will be a snap for you.
4) Query Stems
Query stems focus on types of content or pages that you’re looking for, typically by identifying language patterns within a market. Query stems are more use specific than query roots – typically a stem for discovering directories will not be helpful in also discovering blogs. Further, stems that are highly productive in market expertise surveys will not be helpful for content promotion opportunities. Researchers will find that they discover unique stems – and names for stems – as they conduct research. For example, in some verticals it’s still common to call a single, published blog post a “blog.” So instead of using just “guest post” it could make sense in your market to include “guest blog” stems. Further, in some publishing verticals there are no “guest posts,” there are however “contributing writers.”
5) Query Stem Target or Content Type
In many cases the stem itself makes its target quite obvious. For example, “news tips” is a common query stem for discovering online PR opportunities. You could glance at a spreadsheet and know what it’s for. However, what about the stem [rumors inurl:submit]? That’s right – you need a column to mark the target type here.
6) Advanced Operators
Advanced operators function as stems that further narrow and “qualify” your results. I primarily lean on intitle: and inurl: operators. Here are more advanced operators, and here is some interesting thinking on using negative or reductive operators for increasing query productivity.
7) Query Root and Stem Productivity
I define productivity as the amount of useful information that is returned to the researcher. Productivity can be assessed roughly from the top 10 results in a SERP. If there are 0 results then that’s clearly not a productive query. If there are 14,000,000 results and none of the top 10 are useful then it’s not a productive query. At this time it’s best to mark productivity from your subjective user perspective. It’s important to note that the productivity of a root differs from the productivity of a stem, and an entire query must not be thrown out before determining if the root or the stem is the cause of low productivity. Further, if you’re adding in advanced operators you must remember to determine exactly what’s impacting overall query productivity.
Footprints are market research queries – however, they specific to a very unique and sometimes deep vein of opportunity. I personally use them when tracking prolific guest posters in a particular vertical. They will not be useful to me outside of a very narrow use and they are only discoverable from close on page scrutiny of a prospect. It should be noted that a marketer with a good nose for “footprints” will also have an easy time with discovering effective query roots and stems, which are simply broader footprints that define a language sphere used by a market.
I hope first and foremost that this article raises more questions than it answers! Further, that it helps you change your thinking about how you use the skills you already posess. These methodology elements are just my suggestions – I look forward to any thinking you have on cataloging, preserving and maximizing the value of your market research queries.
What a geek – you got to the end of this post! You may be geeky enough for this one too.
This is a draft excerpt from my upcoming book.
Keyword Research – Using Categories to Make Your Process More Actionable by Richard Baxter
Link Building Query Theory: 7 Crucial Keyword Types for Link Prospect Querying
Resource Page Cocitation Analysis for Authority Link Builders (and Other Content Marketers)
The Link Builder’s Guide to Competitive ‘How-To’ Content Analysis
The New School of Link Prospecting Keyword Research (+4 Tools & 2 Tips)
Link Prospecting with Garrett French
17 Tips for Tip-Based Content – How to Research, Scale & Promote