Assessing the Total Addressable Market is a key element of every business plan. TAM should, however, not be confused with the actual current market size as I have explained in my previous post called In short, TAM represents the maximal potential market. So, if everyone who could possibly buy your product bought it, times the price of each unit - that is the total addressable market..
|Think big when calculating your TAM|
TAM calculations are in general not concerned with your ability to execute and with the market’s readiness. That means, when calculating your TAM, you are not worried about your geographical presence, your competitive win rate, your ability to avoid discounting, the strength of your brand, or your products’ maturity and quality. All those factors (and more) ultimately reduce the TAM down to what is your current revenue.
Between those two data points lie other metrics that are sometimes used such as Serviceable Available Market (SAM) or Serviceable Obtainable Market (SOM). Those metrics are basically derived by applying some of the execution constraints on the TAM like a set of filters. While interesting, those metrics become very subjective and specific to any organization. For instance, your absence in certain geographies reduces your SAM but that absence is a result of your recent decision-making and it may or may not be easily revisited (i.e. by entering geographies such as Japan, China, or Africa). That’s why TAM is the most common metric because it avoids all such nuances and recent strategic and tactical business decisions.
So, how do you determine your TAM? First, search around and see whether it already exists. In established markets, one of your competitors, an industry analyst, or an investment bank might have already published a TAM, whether or not they disclose how they came up with it. If you find such data point, it’s your lucky day. Senior management and investors love to quote Gartner or Goldman Sachs and their numbers are hardly ever questioned.
There are a few other possible data sources including large system integrators (Deloitte, Accenture, etc.) as well as some of the online collections of useful and less useful statistics such asand . Obviously, publications such as The Economist, The Wall Street Journal, and Business Insider also frequently quote useful data points. It’s a good habit to collect the articles with relevant data points for when you might need them.
But, let’s face it, you are probably reading this article because you have not been successful finding your market’s TAM and you are stuck. Well, if you can’t find it, you have to calculate it.
There are multiple methods of calculating TAM. Each one involves certain judgment calls and educated estimates. This is key – to calculate TAM, you will have to rely on your market expertise and make some estimates. Just like I discussed in my previous blog post on calculating the market size, your educated estimates will be much better than no data at all. After all, that’s exactly what the analysts at Gartner, Deloitte, and Goldman Sachs do.
The three methods I will discuss here are:
1. Bottom Up Calculation
The bottom up method is based on your licensing model and estimates the maximum number of licenses available in the world.
2. Top Down Estimate
The top-down method is based on the share of valet from the overall worldwide spending in a given sector.
3. Economic Impact Estimate
This method is based on the estimate of the economic impact of your product and what companies might be willing to spend to capture that benefit.
I’m sure that there are other methods out there but these three I have found most practical. So, let’s take a closer look:
This is my favorite method of estimating the TAM because it tends to be the most accurate and relies on data that is hopefully available with some level of accuracy. Simply put, this method counts the maximum number of licenses that you could possibly sell. If your licensing is by household, you count the number of households. If you are licensing by sales person, you count the number of sales people. And if your licensing is based on number of wind turbines, you count all the wind turbines out there.
Let’s take a specific example. Let’s say that you are manufacturing a black box device for aircraft. Your licensing is basically per aircraft and hence you need to the data on the number of aircraft in the world. That data exists – it won’t take you long to find a number of data sources providing the annual production for key manufacturers, the active fleet for each airline, etc. You as the experts in this space should know those data sources and be able to assess their validity.
Now, that you have the maximum possible number of licenses, you multiply it by the price of your unit and voila, that’s your TAM. Of course you can get more granular. Let’s say that your product is only for commercial aircraft and not for private jets. You can calculate your TAM based on that. Or maybe the long haul jets require two units – you can adjust your TAM accordingly.
But remember, as you are adjusting your TAM to fit your specific product, you might cross the line from TAM to SAM or SOM because some of these filters are based on your business decisions that have reduced your addressable market. For example – not selling to private jets might be a smart GTM focus but they need your black boxes just as much as the commercial jets and your TAM should reflect that. While it is important to put some boundaries around your company’s or product’s opportunity, don’t restrict that opportunity based on tactical thinking.
The challenge of this method is that the number of possible licenses might not exist or that it is not precise enough. Let’s say you license by number of sales people, but your product is only relevant to those who are on the road every day. Or maybe it’s only for sales people selling insurance. Finding that data may prove much more difficult. Still, there are many sources worth checking out:, , , , , , , , and many others.
Another way to get to relevant data is your own customer base. Let’s say that you have a product licensed for your customers’ IT helpdesk and so you need to know their number of IT helpdesk workers in the world. Analyzing your own customer data, you might be able to determine that your customers have on average 8% of their employees in IT and out of those, 25% work the helpdesk. Knowing this ratio is extremely useful and if you have at least a few hundred customers, it is very accurate.
With that ratio, you will need to establish the employee population in your target market. If you sell to Financial Services, it’s easy to find out that there are 6.3 million workers in that sector. If 2% of them work the IT helpdesk, you have your TAM.
If you can’t find the employee population in your target market, you can get it from the number of companies and their respective employee numbers. That data is available from data sources such as Dun & Bradstreet, Lightning Data (Salesforce), LinkedIn, NAICS.com, and others.
A similar process works for other licensing models - number of vehicles, terabytes of data, or megawatts of energy produced. Sure, sometimes you may need to estimate some of the data points. This is where your own expertise comes in. It’s OK to estimate but always, document your estimates and data sources. That way, anyone who doesn’t agree with any of your decisions can follow your logic and adjust accordingly if they think they know better.
The top down estimate is based on the share-of-valet calculation for your product. The basic idea is that from a macro-economical standpoint, there is a finite amount of money spent on certain goods or services. That spend is often well documented as several analyst firms publish the total annual spend on markets such as IT, retail, travel, advertising, etc.
I’ll stick to the IT sector, since this is a blog on technology and that’s what I know. Here, firms like Gardner, Forrester and IDC regularly publish data on the worldwide market spend for IT technologies. Let’s take Gardner – they forecast it for the next five years in their quarterly IT Spending Forecast. That number is not going to grow because of your product, no matter how amazing it is. That means, you need to take some of the share of valet from the all other products. In other words, you’ll need to convince the IT buyers to spend some of their precious budget on your product at the cost of all the other IT spend. You need to take over some share of their valet.
The Gardner forecast gives you some amount of granularity, using a two-layer taxonomy for software and providing the data for each of the categories and sub-categories. For example, under CRM, Gardner forecasts the following sub-categories: Customer Service and Support, Digital Commerce Platforms, Marketing, and Sales. This is very helpful to further narrow your available share-of valet down to the respective subcategory.
Your product will likely occupy an even narrower category and you will need to estimate the share your category will take from the Gardner taxonomy. Let’s say your product is a CPQ solution (Configure, Price, Quote), which clearly falls under the Sales sub-category under CRM. Now, the good news is that because this is a category recognized by Gardner (with its own Magic Quadrant) there is likely more data available, including the current market size and maybe some breakdowns by geography and vendors. Gardner doesn’t publish this data but they track it and they will share it if you have the right subscription.
If that data doesn’t exist, you need to estimate. List all of the solution types in a given sub-category and assign them percentages based on your best judgment. Again, your educated estimate is going to be better than no data at all. But in general, this method is more useful for market sizing and forecasting than to estimate the TAM. Still, having the understanding of the overall market spend and its taxonomy is useful for TAM calculation.
Economic Impact Estimate
The economic impact estimate is trying to assess the value your solution has for the customers and estimate how much they would be willing to pay for that value. The basic logic is that if a particular product lowers your cost by 10%, customers would be willing to pay, say, 1% of that cost to realize that benefit. This rationale makes a lot of sense economically, however, I consider this method rather unreliable.
First, companies are really mistrustful of any promise of hard cost savings or revenue growth. All the ROI calculators in the world are usually met with severe skepticism. On top of that, companies are very reluctant to promise you a share of their savings or growth. What they want is a predictable and elastic operating expense that they can throttle up and down as needed. That’s why all the software is moving to the cloud – it shifts any risk towards an operating expenditure.
Still, the TAM calculation based on the economic impact estimate makes sense on a macro level. For example, you can estimate the impact of the entire IT infrastructure on a particular sector – i.e. how much does technology make a difference in banking or in retail. Or perhaps the impact of a major industry trend such as mobility or IoT. But as you start getting more granular, it’s hard to defend that your particular product has made all of the contribution to the bottom line. That’s why using this methodology can lead to unreasonable TAM estimates.
As you can see, there is more than one way to go and if you are serious about estimating your TAM, I do recommend you try them all. Don’t expect the results to be same but hopefully at least within the same number of digits. If they differ by order of magnitudes, you might have to revisit some of your estimates.
Good luck estimating and…trust your judgment!