One of the biggest challenges in the industry of search engine optimization is having a conversation with your client, your boss or your CEO about the potential outcome of your SEO campaign. If you’re in the PPC field, it’s a very direct measurement that’s available between the budget that’s allocated to the program and the expected return on ad spend (ROAS) or return on investment (ROI). Those a simple, identifiable metrics, and they’re directly connected and controlled by the expert assigned to them.
SEO…not so much.
You can’t guarantee that x, y, or z will generate X amount of clicks, X amount of leads, X amount of sales DIRECTLY of course because organic results in search aren’t direct pay for play type of game.
HOWEVER. If you’ve been around a while, you DO know the strategies that GENERALLY work, and GENERALLY end up resulting in additional traffic, leads and revenue.
SO. If you could generate some sort of document that showed the POTENTIAL of traffic, leads, sales & revenue you could justify a budget being assigned to execute on those GENERAL SEO TASKS that create results.
Where do we start?
Forecast SEO REVENUE Potential & Not Just Traffic Volume
There’s several ways to go about gathering keywords from various SEO tools like SEMrush, Ahrefs etc. You can brainstorm out from your starting keyword. You can do customer interviews. You can use keyword magic and other shortcut tools. You can grab keywords from Google Search Console (Yes, even if you have more than 50,000 keyword queries).
My favorite process is to check the target keyword’s results on Google, grab their top 10 rankings and get the top 100 keywords from each of those sites (Spoiler alert, that’s our auto-magic process for our keyword service)
However you get it, you will want to get a focused list of keywords and their estimated monthly search volume numbers.
That’s when the fun begins!
- Gather the list of relevant keywords that are most likely actually purchase the product or service.
- Get the total volume of those keywords using a keyword research tool.
- Multiply that volume by a PLAUSIBLE organic click through rate for a specific ranking, this study by Advanced Web Rankings is pretty good. An “organic click through rate” is a fancy way of describing what percentage of people who click through on a search result to a website based on the ranking position of that site. Most traffic, upward of 35%. or more always flows to the #1 site. Depending on how “high in rankings” it’s plausible for you, choose a the estimated organic CTR for the #1 ranking. This is your potential monthly search traffic for #1 ranking.
- Calculate at what rate is traffic that turning into leads by filling out a form, ordering a product, or making a call. (Conversion rate).
- Take your potential traffic number and multiply it by the conversion rate. This is your potential # of conversions.
- Find out how many of your conversions actually turn into sales. **For eCommerce this is fairly straightforward, but you may need to talk to your sales team about Sales Qualified Leads and other processes first. Once you know how many leads(conversions) you had on your site and how many sales you had from THOSE leads then you can multiply the conversions from step 8.** This is your potential # of sales.
- You need to find out the revenue per sale for this product or service. While this COULD be straightforward for a product, potentially you may need to estimate the AVERAGE revenue from these clients because they could sign up for multiple months, or multiple services at once. For recurring income, find out the average lifetime of a client and multiply your monthly revenue by that value. This is your potential revenue.
- Repeat this process using #6 organic CTR
- This will provide you with two potential SEO Returns on Investment reports based on being “at the top” of the rankings, vs “just being on” the first page.
Second Opinion: An SEO Forecasting Process
Process for attempting to evaluate traffic potential , I have taken the following, general approach:
- I identify current device% breakout between mobile and desktop via analytics data
- I use Rand/Jumpshots study of click death by device type (this may be controversial to some people, but I’ve noticed it models our actual data pretty decently)
- desktop/mobile search volume from your tool of choice (e.g. SEMrush, Ahrefs, etc.)
- averaged CTR for top five positions (generally what we’re shooting for re: rankings), pulled from top X keywords in GSC
- *You can also take extra steps to consider “Keyword difficulty* in your forecast*
So, for example:
I want to project what my outcomes may be if I rank in top 5 for any given set of terms, thereby projecting what my opportunity is if I try to invest. This can be used in conjunction with other metrics, such as average difficulty for a corpus of keywords, etc. to make decisions on re: do you invest your time in them or not.
Here are the things I work through –
Calculating target ranking position (target ranking position = top 5) average – I recommend doing this for desktop and mobile to use the relative CTR for each later on:
- I pulled the top keywords from GSC into sheets for the last 6 months (capped out the pull at around 50k terms gathered)
- I rounded the position data to nearest whole position and applied groupings to them (position 1, top 3, first page, etc.) for future analysis
- I used averageif on CTR for all top 10 positions (averageif pos = 1, averageif pos =2, etc.)
- Then, I average the top 5 position averages, giving me a relative average for if I ranked in the top 5 positions
- this % gets used in final equation
Find device breakout for current audience:
- from your analytics of record (Omniture, GA, etc.), find out the device breakout by mobile vs desktop
- these % get used in final equation
Leverage click data from Rand/Jumpshot study:
- While a recent study – and one which people may scoff at, or ignore – I find being mindful of loss-of-click to be an important element; if you trust the click potential data from Ahrefs or SEMrush, you could use that info on the keyword level instead of using this broad study
- let’s say we don’t use Ahrefs or SEMrush click estimates though, I would use the 39% clicks on mobile (61% no clicks was the number referenced in the study), and 65% clicks on desktop (34.5% no clicks was number referenced in study) in my final equation
Get desktop AND mobile data for keywords, as available:
- for each term I’m going to include in my corpus for this analysis, I will try to get both the desktop data as well as the mobile data; if mobile data is not available (or vice versa), then I will use whatever is available
- the keyword data could be for existing rankings (current marketshare/footprint), and/or for new terms we want to go after (gap footprint) – these can be used to support different questions (e.g. should we invest in optimizing current content and what would outcomes potentially be if so)
- data needed = search volume and current ranking position (if pulling for current footprint)
Based on all this data, we can now calculate traffic potential.
Traffic potential = ((mobile sv*0.39) * mobile traffic %) * avg T5 mobile CTR + ((desktop sv * 0.65) * desktop traffic %) * avg T5 desktop CTR
This equation is applied to every keyword we currently rank for, not in the top 5 (e.g. position 6-100).
This should give us insights into answering the question of “if we improve our ranking position for this corpus of keywords, what might the traffic estimate look like”.
You can then use this in comparison/conjunction with other metrics, like average difficulty for a topical category (e.g. risk reward based on comp to traffic opp), etc.
Actionable Recommendation: Group Your Keywords By Conversion Potential
My recommendation for this is to not look at/forecast on a per-term basis, but instead to do it in groups or as a whole (e.g. all terms that make up a certain topical niche, or all terms that reflect the current footprint for a site).
By grouping things together, you get a better understanding of topical opportunity and risk/rewards (when looking at KW difficulty, revenue opps, etc). Don’t forget to actually look at the SERP results to make sure you’re not optimizing a mismatched keyword.