Keyword Opportunity Cube is an innovative keyword research model. This model makes use of 3 dimensions and 8 keyword personalities. There are many ways Keyword Opportunity Cube model can be used. However, the Cube excels at highlighting Keyword Opportunities for a given purpose QUICKLY.

Recently, I was conducting a keyword research for a few companies. It happened that +AJ Kohn published a very captivating article about Keyword Match Ratio. What an eye opener!

That's how AJ Kohn defines Keyword Match Ratio:

I read the article, sat down and started playing with Keyword Match Ratios for all my keywords that I have selected for one company. It is at this time when an idea visited my mind and kept me up a few nights in a row. The idea comes from a combination of concepts.

One of them - of course - is AJ Kohn’s Keyword Match Ratio. I reversed the ratio and called it Search Term Exactitude. Sorry AJ, I had to do it for this model.  

Another one is "The 4 Quandrands of <you name it>". I guess the Four Temperaments test is something everyone remembers.

That’s where I started to test the “personality” of my keywords using competition and search term exactitude (that’s AJ’s reversed Keyword Match Ratio).  What became apparent was that I could not identify the true personality of my keywords. One other important dimension was missing-- volume. I added it to the equasion. That's how a 2D personality test became a Keyword Opprotunity Cube. 

Keyword Opportunity Cube: Purpose

I had to specify just one reason for the cube’s existence, it would be highlighting Keyword Opportunities for a given purpose QUICKLY. A by-product of this model is highlighting of potential keyword pitfalls.

Meet the Keyword Opportunity Cube

There are 3 dimensions (axes) with a reference point (or zero point) that separates high from low. When these axes intersect, they break the big cube into 8 smaller cubes. Each keyword has coordinates assigned to it (volume, competition and exactitude). Depending on coordinates, personality of these keywords is defined :

1- Big Waste of Time
2- Land of Opportunities
3- Healthy Competition
4- Big Brand Desire
5- Small Waste of Time
6- High Margin Opportunity
7- Specialized Competition
8- Eligible Variations

Some keywords will have extreme coordinates, but most of them will stay somewhere in the middle of the large cube.  In other words, most keywords won’t have strong personalities. In this model, attention is focused on keywords with strong personality. 

Keyword Dimensions

Exact Search Volume

  • Volume is directly available from Keyword Tool
  • High volume keywords are not necessarily better than low volume keywords for many reasons (including but not limited to difficulty to rank, profitability, etc.)
  • Values range from 0 to ∞ depening on the keyword list population

Exact Search Competition

  • Competition is available directly from Keyword Tool
  • Competition is defined as search volume VS advertiser saturation
  • Neither high nor low competition is good or bad in this model
  • Values range from 0% to 100%

Search Term Exactitude

  • Search Term Exactitude = exact search volume / broad search volume. Both these values are available from Keyword Tool
  • High term exactitude is preferable
  • Low search term exactitude is not a decision making factor alone
  • Values range between 0% and 100%

Now, it is very important for all of us to understand and keep in mind that keyword STE and search competition are “derivatives”. We derive these values using various volume figures that Google supplies us with. You know, volume numbers are often imperfected. 

Keyword Coordinate Space

For search term competition and exactitude, the scale is 0% to 100%. For volume, a logarythmic scale is used. The big cube is broken into 8 smaller cubes by the reference point (or zero point).

Reference Point (Zero Point)

Depending on the goals of a keyword research, the reference point on each scale can be the average value or anything that makes sense. 

Quantifying Keyword Personality

Until armed with a visual Keyword Opportunity Tool, I use a formula to calculate Keyword Personality Strength. The idea is to first measure the direction of the personality within two dimensions (competition and exactitude). Next, in order to express the 2D personality strength, direction is aided with magnitude (distance from point zero to keywords location).

Below are two graphs. The one on your left - Personality Strength  - demonstrates how deflection from the vector of Perfect Personality sharply reduces strength of a personality in a given cube. The graph on your right is - Personality Value - demonstrates how the total value of a keyword in a given cube is higher when 1) the score on each axis is higher and 2) deflection from the Perfect Personality is low.



And finally, 2D peronality strength is further aided by the magnitude of volume to become 3D. This 3D expression is easily used to sort the keywords in the specific cube by their total personality value. Unfortunately, I cannot aid the final formula with a graph of function due to technical difficulties (hint: a graph of 3D function is 4D).

Keyword Personalities

Now that you know the theory behind building the cube, let’s study the theory behind keyword personalities. Definition of a keyword personality relies on finding the keyword’s position relative to the zero point. In other words, if coordinates of a Keyword A fall into a small cube1, its personality is 1.

For each of the Keyword Personalities, I have crafted a list of keywords from my research into Solar Panels. These lists are manually compiled at a glance by selecting keywords with highest personality score. If a given cube is considered an opportunity, then the highest score is assigned to the keywords that should present the best opportunities. If a given cube is considered a pitfall, the higher the personality score the more of a pitfall the keyword is.

The topic of Solar Panels is particularly interesting in Ontario, Canada. We have a FIT (feed-in-tariff) program here in Ontario. Under this program, solar panels installed on the roof-tops may turn into very profitable investment. Government of Ontario is paying $0.80 per kWh fed into the grid from such panels. For comparison, the cost of electricity for a household in Ontario varies between $0.07 to $0.09 depending on the time of day.

Cube 1 – Big Waste of Time

Attributes: high volume, low competition and low exactitude

Search terms in this cube have high volume and low competition. Such term could make a good content marketing opportunity. But why do I call this whole category a waste of time? It’s the search term exactitude that changes the whole landscape. Bidding or optimizing for such terms is like bidding or optimizing for the term “cat”. Notice how keywords in this sample are very broad.

Cube 2 – Land of Opportunities

Attributes: high volume, low competition and high exactitude

Now that’s much better. A keyword with huge volume, highly demanded, scarcely supplied, yet searchers using this term have uniform intent. This keyword could be a good opportunity for content marketing or even for marketing a service or product directly.. Keywords may fall into this cube for several reasons:

  • This keyword is an opprotunity that has not yet been identified and/or dveloped. 
  • Keyword does not generate huge returns on investment for advertisers.
  • This is a great opportunity for content marketing. 

Notice how "ontario solar provider" could be a great keyword for direct marketing of solar panel installations services in Ontario. Other keywords appeal for content marketing.

Cube 3 – Healthy Competition

Attributes: high volume, high competition and high exactitude

While highly demanded, these keywords are also well supplied by advertisers. Competition is fierce. The good news is that the searchers are a lot more likely to be well-educated on the subject and know exactly what they are looking for (uniform intent). Thus, they are either looking for specific information or a product/service. If your website converts well and earns trust of the visitors, chances are your ROI for these keywords can be fairly high.

Notice how these keywords are either location specific or imply that the searcher's intention is to purchase solar panels. The keyword "solar shingles" probably does not fall well into this category. The low personality score for it demonstrates it nicely.

Cube 4 – Big Brand Desire

Attributes: high volume, high competition and low exactitude

The grounds for these keywords are fairly competitive. However, the landscape is also vast. In other words, searchers who use this search term can be looking for anything even distantly related to the corresponding broad term. Chances are, it is very hard to optimize your website for these search terms. I also find it hard to improve conversion rates for these keywords because searchers using them have various intents. Bidding or betting on these keywords is similar to bidding for “Garage Doors”. Big brands often bid for such terms and economies of scale helps them still stay profitable. This is not something small competitors can afford. 

Example below shows how keywords are generally more specific than in Cube 1. They also have high competition. While search intent is still not clear at this stage, bigger brands may find these keywords profitable or at least breaking even.

Cube 5 – Small Waste of Time

Attributes: low volume, low competition, low exactitude.

Of all keyword types, this one has the least potential for any kind of success. Look at the attributes – very few people use this search term (volume), advertisers don’t find it profitable and people using it may have no idea what they are looking for (fractured intent). Why did I say “least potential” rather than “none”? There is a slight chance this keyword is an emerging trend or it relates to high specialty services that haven’t been identified by advertisers yet. However, in majority of cases, these are grammatically incorrect variations, very long tail keywords, incorrect phraseology keywords and otherwise unsound variations. Export the opportunities in this cube - learn what not to optimize for. 

Just look at "how does solar panels work" - it's grammatically incorrect. Or does a person really intend to "install [one] solar panel"? I am not surprised that advertisers don't find these keywords valuable.

Cube 6 – Hight Margin Opportunity

Attributes: low volume, low competition and high exactitude

This type of keywords is very similar to the ones in Cube 2. What makes the difference is the search volume (low here). Hence, the change in personality. Keywords in this cube inherit a few big IFs as follows:

  • if the keyword closely relates to a high-margin and/or high-specialty product or service, then this keyword is golden for both content marketing and direct product/service marketing.
  • if the keyword is just a seldom used variation of the larger subset of keywords relating to a generic product/service, than investment in advertising and optimizing around this keyword might not be worth it.
  • if this keyword relates to a hot new trend that is about to take off, investment in it will most likely provide great returns in the nearest future (such as Responsive Website Design).

"Concentrated solar power" looks attractive. Yes, the traffic isn't promising but these panels are very expensive.

Cube 7 – Specialized Competition

Attributes: low volume, high competition and high exactitude

This is a cube full of identified opportunities. High competition makes it unaffordable for content marketers to participate in paid advertising. Thus all the competition is comprised of businesses that have a goal of marketing and selling something directly. My experience shows that keywords fall in this category for a few main reasons:

  • The keyword relates to high margin/high specialty goods/services
  • The keyword relates to highly localized services
  • The keyword has otherwise high ROI

Notice how searchers using the keywords in this cube are closer to the finish line in the buying cycle? Also, solar panels are a high margin product here in Canada. In order to qualify for the FIT program, photovoltaic panels must be manufactured in Canada.

Cube 8 – Eligible Variations

Attributes: low volume, high competition and low exactitude

I would forego looking at these keywords due to their low Search Term Exactitude and volume if not the high competition. The fact that competition is fierce for these keywords implies that advertisers find those valuable. This in turn implies that such keywords are perfectly valid variations within the larger subset of keywords related to a specific topic. If so, then these keywords are worth mentioning on your pages and/or advertising for. Since exactitude is low and competition is high, I would further deduct that Google is well aware of the other variations. Thus, using these keywords to diversify your keyword portfolio on a page won’t harm. Most likely you will even benefit from not over optimizing your page for one specific keyword. 

In the example below, I can already see how all of these search terms are perfectly acceptable variations of a larger subset of keywords.

Keyword opportunity Cube: Practice

Keyword Research: Process

The process is not all that difficult. All manipulations are done in Excel. Below I briefly describe the steps in this process without much detail.
- In AdWords Keyword Tool, enter a limited number of closely-themed keywords. Let Google generate the ideas. Download the list in CSV. You will need to do it twice – for exact match and for broad match.
- Merge the results in one table so that you have the keyword, exact and broad volume numbers and exact competition numbers. Filter out the keywords where exact match volume is too low and/or zero.
- The difficult part is creating all the derivatives, such as exactitude, coordinates on the 3 axes and assignment to a specific cube.  I used AVERAGE, LOG10 and STDEV functions for data manipulation.
- When you have all keywords assigned to corresponding cubes (automatically), filter the Cube column for the cubes that you want to research.
- Select the keywords that have strong personalities.
- Continue in-depth research by using Google Trends, estimating potential ROI and using any other tool you know that may further aid the process.

Keyword Research: Observations

The Grey Mass

If an average value on each scale is used as a reference point, most of the keywords will fall in the center of the large cube. This means that there is a dominant Personality of keywords that we didn’t discuss in the theory section – Normal Keywords or Grey Mass. I usually focus on keywords with strong personalities first.

Local Search

Often there is a need to do a keyword opportunity search for localized search. An example could be a keyword list with ideas around "Garage Doors Toronto". Most ideas won't have the location modifier. Thus, search volume numbers of non-localized keywords must be adjusted to reflect local volume in Toronto. Traffic Estimator tool does not seem to be helpful here. Therefore, use your judgement and population statistics in order to estimate the magnitude of required adjustments.

Skewed Distribution

Having hands-on experience with the cube, I noticed that distributions of competition and exactitude values are heavily skewed towards high competition (0.75+) and low exactitude (<10%). That is why, I sometimes manually adjust center points for these two axes. Adjustment depends on the goals I have set for my specific research.

Keyword Opportunity Cube: Grand Conclusion

Your ultimate tool is your own judgement. Keyword research cube is only as good at identifying possible use for a given keyword as are various temperament models at identifying a person’s purpose in life. So, not good. But the keyword opportunity cube is good at highlighting keywords for a given purpose for further refinement. Same as personality tests are good at selecting a larger group of people for a specific environment with the end goal of selecting only a few of these people for a certain purpose. Therefore, keep in mind, you need to define your keyword research goals clearly first. Only then will the keyword opportunity cube suggest opportunities.