When launching a new product/company or seeking additional funding, forecasting against TAM (Total Addressable Market) is key.
TAM is an essential part of both your user acquisition strategy and your SEO campaign.
It can help you prioritize optimization activities and predict potential traffic based on predefined keyword combinations.
Your total addressable market is different from your total market, as your total market is your maximum potential opportunity if there is no competition or substitute products with different unique selling propositions (USPs).
Your TAM is a small part of this market but closely related to your personas and potential users whose needs closely align with your product/service.
What is the Total Addressable Market (TAM) Formula?
The specific formula for calculating TAM (General Business Meaning) is:
Potential market x competitive position = perfect
Your potential market is the number of potential users, for example, the number of email users in the world is estimated to be around 4.03 billion, but if your competitive position only serves US users, your TAM is roughly 250 million.
TAM can also be affected by users who use adjacent products.
For example, suppose you are an online service that focuses on user privacy as a primary USP.
In this case, users of other privacy-focused products such as Brave (browser) and DuckDuckGo may fall under the general TAM.
However, when we look at our SEO TAM, we can use existing tools and data to generate estimates for our total TAM and then segment it by potential user needs (matching your personas).
Create your own TAM
For me, creating an SEO TAM is a three-step process:
- Identify and fully identify product USPs and capabilities (current and expected).
- Comprehensive keyword research About your product/service/offer.
- traffic estimates (Click on Curves and Opportunity Gap Analysis).
For the first step, you can achieve this by meeting with the product owners and managers, and asking them about the product details, functionality, features, and product roadmap.
This information can then be used to inform your keyword research to create not only better content, but also a healthier user experience.
It allows the user to more accurately predict their experience with the product, reducing repetition and redundancy in the pipeline of unqualified leads.
With experience, these meetings can also help identify some potential angles and messages that can be included in content that competitors are ignoring.
The second step is to do a thorough keyword research and ranking. In addition to classifying by intent, this is also a good opportunity to classify by funnel stage.
The third step is to generate traffic estimates – and you do this by researching keywords, the current ranking positions of the target website (if any), and whether or not the search engine results pages (SERPs) for the keywords have SERP features. .
To show this process, I’ll use Narmi as an example (using publicly available data through SEO tools).
Narmi currently ranks for about 800 keywords in the US and based on SERP data estimated for CTR, the terms generate about 500 sessions per month.
If the domain ranks in the first position for all 800 search terms, the total potential organic traffic is around 81,000.
Now, this is taking the raw data set. For a more realistic TAM estimate, you’ll also need:
- Add additional search terms that you don’t currently rank for, but would like to.
- Remove irrelevant search terms from the dataset, eg random brands that you rank at position 81 picked because you mentioned them once in a blog post.
Ranking 1 position for all possible search terms is not realistic.
But with your data, you can create a tiered approach to show what improvements would be made if things were 10% better, 20% better, and so on.
From this, you can show other stakeholders and potential investors what improvement is required to achieve specific organic traffic goals – and then relate effort values to required resources.
Use your TAM
In addition to traffic forecasting, your TAM data can be used further to forecast leads and transactions.
For most SaaS and lead generation model companies, the pipeline is the most important metric that most C-level stakeholders and other stakeholders refer to.
This can be calculated in a similar way to a potential traffic opportunity and can be modeled using your existing lead data.
Using Narmi’s estimates, and assuming they currently get 11 SQL (sales qualified leads) each month, we can model that it takes an average of 38 sessions per SQL.
Based on this conversion rate, the potential lead opportunity on the keyword pool is estimated to be 2,116 per month.
Again, this is modeled at 100% first position rankings, but as with traffic estimates, we can model this based on incremental performance gain:
This can be expanded further if the expected lead number is multiplied against the lead value and used to forecast the long term based on rates of change and LTV (lifetime value).
This can also determine if there are retention issues.
If the pipeline shows enough numbers to sign up for the free trial, but then not enough convert to paid users, then the focus can shift to any product, customer service/SDR (sales development reps), potential detection issues with Website content and product messages.
If you’re an e-commerce store, you can make similar predictions of how many transactions you might generate, and total revenue (based on current or projected AOV).
If your data fluctuates a lot seasonally or because of the nature of the products you sell, you can break it down by product category or even seasonal category and combine the forecasts together.
Again, you can compare total organic transactions and earning potential data to incremental earnings:
For example, is the current user journey and site conversion rate sufficient to generate the leads/transactions required to generate ROI (Return on Investment) and growth?
Forecasting transactions or leads can help identify both opportunities and problems that may not arise until after they are missed or experienced.
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