Keyword Targeting Quality Score

This post will purpose a "back of the envelope calculation" to create an additional baseline to measure your SEO efforts, called Keyword Targeting Quality Score. It started as I was thinking the other day about the challenges of SEO and reporting success.

I'm going to call this the Keyword Targeting Quality Score. The goal is to gather data on the expected traffic and "realized traffic" and show how well this relationship works for a website.

The keyword Targeting Quality Score is not a granular calculation but a high-level observed behavior type metric. Essentially to inform how well your site ranks are doing in bringing in traffic. This score is not a one-shot metric and used with other data points and quality/efficiency scores.

Here is the thought process.

Standard variables SEO's look at are:

  1. Traffic to a site, with source info (organic, direct, etc.)
  2. Average Seach Volume for a Keyword
  3. Estimated Traffic for a Keyword
  4. Average Session Duration ( aka Time on Site)
  5. # Page per Session 
  6. New vs. Visitor Sessions
  7. Landing Pages and Exit Pages
  8. Time-series Comparison
  9. Other Variables

Keyword Targeting Quality Score - The Setup - Challenges in SEO Reporting

Keyword Targeting Quality Score report iconLooking at all the variables above, only some of these could seem reasonable to track. For example, one month you have 500 visits and the next you have 600, that is good, right?

But what if it is not the right traffic? I.e., You get people coming to your site, but the organic word they found for your site was a product or service you no longer offer. These additional visitors could be calling/contacting you for something that isn't going to help your business.

Does that mean we don't track this? NO! But we do need to contextualize it. i.e., we also need to look at the other variables and factor those in when we evaluate them.

Contextualizing the Data

Knowing how to pair up the data is another challenge. Which data points work together, and which data points are in their lane or part of another cluster?

Going back to the visitors per month, if we look at the Average Session duration time in relationships and see a decrease or increase in session time, that can give us a clue as to how well this new traffic is doing. We can also pair an increase in traffic to New sessions and Visitor Sessions data. Maybe the uptick is from return visits?

These metrics and their relationships can allow us to start the conversation on how we may be succeeding or failing.

When success metrics fail

So with these various data points and the various relationships, it is easy to set up expectations that may fail at one point. A classic example is increasing traffic to the site by increasing keyword/page ranks. Two variables, both are moving in a positive direction. Good, yes?

Well, it depends!

If you are moving ranks up, and there is an increase in traffic, is it the right traffic? I.e., does it convert to sessions and pageviews and ultimately to a sale?

That is the problem with some of the data points. Just because it's a positive number doesn't mean it's good.

Recently I had the opposite happen (increase in ranks decrease in traffic).

I have a client who continuously improves the site to increase their reach (awareness) and conversion to sales. As we have moved forward with specific terms, we have gravitated towards keywords with lower search volumes but better intent. This strategy has netted more keywords ranking in Top 1 and Top 10 spots.

Three things started to happen:

  1. Organic traffic to the site has decreased (adjusted for seasonality)
  2. I suffered what felt like a  minor heart attack as we have been using an increase in organic traffic as a success metric.
  3. The number of qualified inquires and leads increased.

So, should I have known that increasing traffic to the site would top out at some point? Yes, and I did, but I thought we had a longer runway. i.e., more keywords to target that had a high search volume. But as we have been having success with the content with lower search volumes and higher intent, we pivoted, but the measure for success had not.

It was easy for me to show clearly how this was new traffic (the data showed an uptick in new sessions) and the behaviors showed new landing pages, and the keyword rankings showed new words moving into the Top 1 and Top 10. There was a case the latest rankings were bringing in more new traffic.

So this leads to my next thought.

New Metric?: Keyword Targeting Quality Score (Estimated Traffic vs. Actual Traffic)

I was thinking about how SEO tools suggest keywords, and one variable that can be assigned is the search volume. Depending on the program, they then use that data to give estimated traffic. The rationale is if you were to rank well for that keyword (#1 or on the first page), you would get a certain amount of traffic for that ranking word/page.

So if you had a phrase with a search volume of 1,000 searches a month, the estimated traffic could be 300 visits if the keyword rank is on the first page. Of course, this is an oversimplification because there have been cases studies to show the higher the position on the first page, the higher the click-through rate.

However, these estimations appear to be for first-page rank rankings. In their form, this would allow for some variance in click-through rate for specific keywords, given that the SERP displays more than just the URL, but the title and meta descriptions, which could influence a web searcher's choice to click through or not.

There is also the question of the page 2 ranks, but the case studies would show an even lower click-through rate for these results.

So, assuming that page 1 SERP results will produce some traffic, we have to do our best to estimate that traffic amount.

At this point is where I was thinking through the estimated traffic rate vs. actual rate.

Educated Guess

So I propose a metric that takes the estimated traffic for the keywords and pages on the first SERP (total the estimated traffic for all keywords ranked #1-10) and divides it against the 3-month average of organic traffic.

Total of Estimated Search Traffic for SERP 1 results = T

Average of 3 months of Organic Traffic = O

O/T = Keyword Targetting Quality Score

This formula would give you a baseline to measure your website's ability to bring in traffic based on what estimates traffic for ranked words.

What does one do with the score?

Well, If the score is low, you can improve it. The input variables would be:

  1. Improve the ranks of existing keywords.
  2. Improve the positions of keywords with better intent (maybe lower search volumes, better conversion?)
  3. Shift keyword concentration to better-utilized words (maybe how you describe your product is not what people are searching for)
  4. Improve your Titles, Meta Descriptions (better enticement for people to click through)
  5. Drop ranks for underperforming pages (So a page has a keyword ranked #1, but the page it's tied to is a low performing page)

The Keyword Targetting Quality Score would be a sort of buoy in the water to inform you how well your ranks are converting. One goal would be to improve the score by ranking better for words that convert to more traffic.

In speaking with an acquaintance, she mentioned that the score could also be problematic if it were too high. Imagine a 90% score. Almost every keyword that is ranked would be bringing in the traffic estimated. It would mean that you have isolated your market and have the perfect flow. But it also means that you would not be engaging people at other buying stages or from newer markets.

Please take with a grain of salt.

I am by no means saying this metric is complete. One of the first problems with this formula is "branded terms." These can cause a problem because a brand may be ranked for several variances of branded terms, each having an estimated traffic rate but a lower click-through rate. Together this would cause higher estimated traffic for positive ranks.

Is this metric useless? Well, it's something, and given the relationship is could have merit. This metric/formula needs to be tested on more websites than my current book of clients.

As an SEO, part of my job is to go from infinite ignorance to a football field of knowledge and data to make the best plan for my clients. I can't actually guarantee traffic and conversion, but I can always work towards those goals. This Keyword Targetting Quality Score could be one more metric to demonstrate how the site performs against expectations.

If you want to drop some ideas below, please do. If you want to chat, please hit me up.

 

 

 

 

 

 

 

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