Analysing TAM & SAM Data

This is the total market demand for the client’s product or service, regardless of any existing competition or market share. To calculate this, we can use this formula:

TAM = (Total Population) x (Total Addressable Market Percentage) x (Average Yearly Expenditure per Customer).

Example: The total population of the US is approximately 331 million people. If 60% of our nationally representative US sample buys women’s clothes, the total market would be 199 million potential customers (331 million x 60%). We then multiply this by the average yearly expenditure (199 million x $425), and end with a TAM of $84.8 billion.

For a more accurate TAM and detailed market insights, we will want to re-run the TAM formula on filtered data for each of the specific quota groups we built. This will help us identify target customers and tailor our marketing and sales strategy recommendations accordingly.

Estimate the size of each segment by multiplying the percentage of potential customers for that group by the market population of the group as identified in the census data used to develop the sampling frame.

Example: Let’s say one of our quota groups consists of women aged 18-34 who live in urban areas and have a household income of $50,000 or less. You find that there are approximately 35 million women who fit this description in the US. Our sample shows that 10% of this demographic was tagged as potential buyers. That would be a potential market share of 3.5 million women (35 million x 10%).

To calculate this, you can use this formula for each demographic:

Revenue Potential = (Number of Customers in the Segment) x (Average Yearly Expenditure per Customer in the Segment).

Example: Let’s say the average purchase value for women’s clothing in the segment mentioned above is $50, and they make a purchase 10 times per year. The customer’s yearly value is estimated to be $500. The revenue potential for this segment would be $1.75 billion (3.5 million x $500).

Once the revenue potential calculation is repeated for each segment, we then add up the total across segments for a more accurate TAM. You can find an example in the “Bottom-Up TAM US” tab here.

The serviceable available market (SAM) is the portion of the total addressable market (TAM) that is realistically reachable by the client’s product or service. The SAM focuses on specific markets the client serves, which could be determined by geographic, demographic, or behavioral characteristics. Additionally, it narrows down potential buyers to those more squarely in the market for the client’s product or services. To calculate this, we use the same formula as before, but with different inputs:

SAM = (Total Population of Specific Markets) x (Percentage of Potential Buyers) x (Average Yearly Expenditure per Customer).

Unlike with the TAM, the population will be restricted to areas where the client currently serves or plan on serving in the near term. The percentage of potential buyers will be calculated with different inputs. For the SAM, potential buyers will be limited to those who are in the market for the client’s specific product or service. Lastly, you’ll need to make sure that the yearly expenditure is more specific to the client’s product or service.

Example: Let’s say the client’s product is high-end dresses for women, and they are targeting major metropolitan areas in the US. If we estimate the total population of these areas to be around 100 million people, and we assume that 20% of women in these areas are potential buyers of high-end dresses, the total SAM would be 20 million potential customers (100 million x 20%). We then multiply this by the average yearly expenditure per customer, which we estimate to be $600, and end with a SAM of $12 billion.

Example: If the client only serves major metropolitan areas, our total possible addressable market drops from all adults in the U.S. (331 million) to those living in the metro areas (282 million). Moreover, our TAM analysis showed that 60% of the US population purchases women’s clothing. However, for the SAM, we are specifically targeting buyers of high-end dresses. Based on the survey, 20% of respondents purchase dresses that are a minimum of $200. This means that our serviceable market drop is 56.4 million US adults. We then multiply the total number of serviceable customers by the average yearly expenditure. How the average yearly expenditure is calculated is more complex for the SAM. While the TAM took the total yearly expenditure on women’s clothing, the SAM may want to focus on the respondents’ yearly budget specific to dresses over $200. Using this method, the SAM would be (56.4 million x $600) $33.84 billion.

As stated earlier, WTP modules can greatly aid a SAM calculation. The above example detailed the SAM calculation using direct questioning methods. However, a conjoint with price as an attribute and a dual-response none option could provide better estimates. Respondents who choose none for all the options can be categorized as non-buyers. The percentage who would make a purchase can be categorized as buyers, and the average WTP for the sample can be used as an input for annual expenditure. Most likely, the WTP will need to be paired with a direct question about purchase frequency to calculate annual expenditure. This is a prime area for us to test different methods!

For a more accurate SAM and detailed market insights, we will want to rerun the SAM using the specific quota groups we built. This will help us identify target customers and tailor our marketing and sales strategy recommendations accordingly.

Estimate the size of each segment by multiplying the percentage of potential customers for that group by the market population of the group as identified in the census.

To calculate this, you can use this formula for each demographic:

Revenue Potential = (Total Population in the Demographic Group) x (Percentage of Potential Customers Identified in the Survey for the Demographic Group) x (Average Yearly Expenditure per Customer in the Demographic Group)

Once the revenue potential calculation is repeated for each segment, we then add up the total across segments for a more accurate SAM.