SEOHow to Predict Keyword Profitability in New Verticals

How to Predict Keyword Profitability in New Verticals

Want to gauge organic keyword profitability? This four-step forecasting model will help you predict the potential value of your target keyword verticals, which should help you make a more informed business decision about where to invest capital.

predict-keyword-profitability“How profitable are those keywords?” is a question we get asked time and again when pitching clients on the idea of expanding into new keyword verticals.

The clear concern for the client here is return on investment.

“If I follow your recommendations and spend $X on targeting these new keyword groups, and I have dedicated landing pages created, work with you to launch content-based link marketing campaigns and social engagement efforts, etc, how much revenue can I expect to generate?”

It’s a valid question and one you need an answer for if you’re going to land the big money clients who are focused on cash not clicks. It’s also the same question we ask ourselves whenever we’re evaluating the potential profitability a new affiliate space.

4 Steps to Estimating Organic Keyword Profitability

One method of gauging organic keyword profitability and traffic potential is to run a quick and dirty PPC campaign. It’s an effective way to evaluate new verticals and gathering some actual data, but it’s not always a fit for every client.

Paid search aside, you can run a four-step forecasting model to estimate organic keyword profitability.

This profitability forecasting process assumes you’ve already done your initial keyword research and you’ve got a list of terms and phrases you intend to target. If you haven’t, then it’s potentially a five step process.

Step 1: Gather Keyword Search Volume

  • Start by dumping your entire list of keywords into the Google Keyword Tool. You can add up to 100 keywords at a time to get corresponding search volume data.
  • Since this about discovering new keyword opportunities, check the box that says “Only show ideas closely related to my search terms” so you’re only pulling search data for the specific keywords on your list and not other ideas and variations.
  • Set the match type to either “exact match” or “phrase match.” I prefer to run my analysis using phrase match because theoretically it takes into account traffic from long tail variations of my seed keywords that I might be overlooking.
  • Download the results.

Step 2: Calculate Keyword Click-Through-Rate

Next, take your keyword list and forecast for monthly CTR based on position in the SERPs.

With Google continually changing the face of the SERPs to include blended and personalized results and Google’s own web assets, this is hard to gauge with a high degree of precision. But the folks at Slingshot SEO did a pretty good job with their Google CTR Study analysis. You can use that data analysis to map to click rates for Google keyword rankings from any position 1 through 10 on your keyword targeting list.

If you’re working on an aged site with Webmaster Tools implemented, you might also grab site-wide CTR (you’ll need to download and average it yourself from WMT since average CTR isn’t an exposed data point) and use that as a data point, since you could argue that it’s a more honest estimate given it’s tied to your own site performance.

Step 3: Calculate Conversion Rates

When determining the conversion rate component of the forecasting model, I prefer working with real conversion data (be it site-wide or segment specific) available in an established site’s analytics.

If you’re working with a brand new site or exploring affiliate revenue potential in a new vertical and don’t have the luxury of real conversion data, it’s a little trickier. In those cases, you can use conversion rate averages from the MarketingSherpa’s 2012 Search Marketing Benchmark Report, which pegs organic conversion rates at a median of 4 percent and an average of 8 percent.

In my own projections where real data is unavailable, I like to forecast using up to three different conversion points: a conservative range of 1 to 2 percent, a more robust 3 to 4 percent and an optimistic 5 to 6 percent.

Step 4: Forecast Keyword Revenue Potential

For this step, you need to plug in a “profitability” computation, whether it be average value per sale, or lifetime value of a customer, or price per lead if you’re doing lead gen, etc.

Note that you can also leave this column blank in your projection if you don’t have access to this data yet, but then you’re really only forecasting for potential traffic and conversions and not overall profitability.

When you’ve completed this process, you’re going to have a spreadsheet that looks something like this:


The above is a brief snapshot from a larger SEO site audit report we ran for a site owner who was debating whether to invest in selling corporate gifts, and wanted an estimate on potential keyword profitability.

This example uses a Google rank of position No. 3 and we applied the client’s existing organic conversion data of 1.75 percent.

We plugged in existing order values across the site as the revenue calculation. We also ran a number of reports with forecasts for different SERP rankings for hundreds of keywords and plugged in a range of higher conversion rates, since the site owner was working with a conversion rate optimization expert and was optimistic about improving rates.

Final Thoughts on Keyword Profitability

Running these sort of forecasts will help you predict the potential profitability of your target keyword verticals, which should help you or your client make a more informed business decision about where to invest capital.

Obviously, this is an estimate and an inexact science, but that’s the nature of any revenue modeling. A working example like this is probably as close as you’re going to get without real world data to draw from.

It’s also worth noting that there are a range of SEO variables at play here that could directly impact site performance, rankings and potential CTR (like domain age, back link profile, competitive degree of the SERPs, brand presence and user behavior, seasonality, overall SERP volatility, etc.), which is why you should run a number of forecasts with different rankings and conversion rates to try and account for as many case scenarios as possible.


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