As SEOs, we are often focused on organic traffic and revenue. But your site’s performance is only part of the picture - you need the context of your search category to know how well you’re doing.
Have you ever stepped back to measure how big your total addressable target market is? How many people search for your category every month? Is it growing or shrinking? What percentage of the demand is branded or unbranded?
With this data, you’ll be able to put your traffic in context - do you have just 2% share of that search, or 20%? And you'll be able to see how much room there is for growth with the right SEO strategy.
This guide will show you my template and step-by-step process for calculating total demand and search volume trends, including two methods to get all the keyword data using a range of tools. I’ll then show how to use this data to build ‘share of search’ reports to take your SEO reporting to the next level.
Often shortened to TAM (because we all need more acronyms in marketing), the total addressable market tells you how many people you can target with your brand.
In search, we can’t see users so for us, a TAM will define how many searches total are there for your category every month, and whether it’s changing over time.
This trending data also helps us put SEO performance in context. If your traffic is up 5% year on year, but your category size has grown 10%, you’re actually getting a smaller portion of the pie. Likewise if demand has dropped, your traffic may be lower but that doesn’t mean your SEO is declining - just your market size.
To work out your TAM, you need to know all the keywords for your category. There’s an easy way and a hard way, depending on how much detail you want.
Head to your favourite SEO tool, like Semrush or ahrefs. Put your domain in and export all keywords in the top 10 positions if you have a lot of rankings, or top 20 positions if your site is smaller. Repeat the process for a set of close competitors in your same category.
Combine all these keywords in Excel, deduplicate and sum up your search volumes, and you have your category size!
If you want a cleaner data set, it’s time for some keyword research. I always recommend brainstorming a starter list of key topics in your category for this. For example, if you sell coffee then you’ll want ground coffee, roast coffee, coffee beans, single origin coffee etc. Can you tell I wrote this on an early morning train and only had one thing on my brain?
Hit up your favourite tools with your starter keywords and export as much data as possible. The more sources you use, the more robust your data will be.
You can also export keywords from Google Search Console, but don’t just use this data as your source. Your category should include all keywords, not just the ones you already rank for. Include competitor brands and products to get a sense of the overall market size.
Combine your lists in Excel and deduplicate. You can then clean the data by going through to remove any irrelevant keywords. For example if you don’t sell coffee pods, you may want to remove those keywords from your list, as those people aren’t in your target market.
Once you have your final list, you’re ready to move to the next step!
This step tells you what portion of the category demand is branded, so you can see the brand and generic split.
I always include this because it’s more variable than you’d think - some categories have a really small branded search, while others are 25% branded. It’s useful to know how much of your total addressable market you can target via generic search, and what portion of the audience is searching for competitor brands.
To isolate these, it’s time for a bit of manual filtering. Search for keywords containing common brand names and mark them as branded. I like to add another column to mark the brand name so I can also compare volumes for the different brands. Make sure to include misspellings!
Pull your data into a pivot table to tell you total search, brand portion of that, and compare total searches for your competitor brands.
Now you need to know how demand for your category is changing over time! For this, you’ll need Google Ads access for Keyword Planner. Bulk upload your keywords in batches of up to 10,000 and export all available historical data - it should cover the last four years.
You can then total the columns for each month and plot the trends to see how your category is growing or shrinking over time. In our coffee example, you can see a clear spike in 2024 vs last year:
This data is huge for working out your SEO performance in context - if your category has grown 5% in the last year, and your organic traffic has also grown 5%, you’re not actually doing better. You’re driving the same portion of search from a bigger category.
Want to know what portion of the total category you own? Time to get some more data! For this I like to compare against competitors so you’ll want to use your favourite rankings tool.
It doesn’t matter if you use Semrush, ahrefs, SEO Monitor etc. They all have different methodologies for calculating estimated traffic and none of the data is pinpoint accurate, but as long as you use the same data source for all brands, you’re able to compare.
Export your rankings for every domain you’re comparing, including estimated traffic by keyword. Use a Vlookup formula to pull that data into your keyword list, in separate columns for each brand. You won’t have rankings for every keyword, so remove any #N/A entries.
You can then use another pivot table to total up everyone’s estimated traffic, and compare to the total search volumes to give you share of search like this:
This data is a smart way to simplify SEO performance reporting and help build business cases for SEO work.
You can also update the rankings data every month or quarter to get a sense of how your share of search has changed against your competitors.
Now you know:
If you want even more value out of this research, here’s how to expand it!
Categorise your keyword data by theme and topic so you can see your share of search by topic. For example, group product keywords together, and add topic groups for advice keywords like ‘how to make a macchiato’. You can go as broad or granular as you need.
You’ll be able to see the comparative size of each category within your data, and also your share of search for each one.
