This post is by Paul Faguet. Paul is the founder and CEO of Sellerscale, a managerial accounting platform for Amazon sellers.
Selling on Amazon is a numbers game. You commit capital to a particular product, and then strive to recover that capital over time – including an additional return on top of that to make the whole effort worth your while.
In order to nail your product selection, it is crucial to be numbers-driven and apply high-quality profitability analysis during the research phase. You want to properly model out the potential of candidate products before making decisions on how to allocate your capital. One of the best ways to gain this understanding is through unit economics analysis.
This kind of analysis doesn’t actually take much effort, and it will give you that extra advantage over competition since most sellers don’t ever bother to properly model out profitability in advance.
Here are all the steps involved in performing a detailed unit economics analysis, including a free Google Sheet to help you get started.
Setting up your unit economics model
If you’re comfortable with Excel or Google Sheets, you can model out your unit economics in a spreadsheet. Here’s a Google Sheet which contains the spreadsheet below.
You can either copy the file and simply populate it with your own data, or create your own custom spreadsheet using this one as a reference.
An alternative is my company’s app Sellerscale, which combines a web-based unit economics tool with data from the Amazon API.
This particular unit economics model contains three sections: assumptions, costs, and profitability.
Your assumptions are essentially inputs you will be able to play with in order to simulate different profitability scenarios as part of your analysis.
For instance, you could adjust your sales price and observe how profit margin changes in response. Or play with the ACoS (advertising cost of sales) metric and learn how it drives your ROI. Or see what happens to profitability if you give away two units per day at a 30% discount.
Your costs are where you aggregate all the variable, direct costs associated with each product.
This includes your unit landed cost (manufacturing, shipping and prep), all of the Amazon fees (FBA and referral fees, storage costs, etc), and your per-unit PPC expenditures.
Note that fixed costs like product photography, or indirect costs like monthly software subscriptions, are not in the unit economics model. With unit economics, we only look at direct costs that scale directly with sales volume. You should account for your other costs separately.
Finally, the profitability section contains your profit margin, ROI, payback period (time it takes to recover your initial investment), and total monthly earnings.
This is the section you will be looking at to gauge the final impact of any adjustments in your input assumptions.
Calculating baseline profitability
Before you dive into the analysis, you’ll need to research the associated costs and plug them into your model to determine baseline projected profitability. Below are some of the metrics you’ll need to find.
Unit landed cost
This is your total cost per unit of manufacturing and delivering the product to an Amazon fulfillment center. This includes packaging, package inserts, tariffs, etc. In other words, this is your fully loaded cost of making and delivering one unit of product to the warehouse.
If your supplier quoted you a total of $2k to produce 1k units of product (including all packaging, marketing brochures, etc), and your freight forwarder quoted you another $1k to ship this batch from the supplier all the way to an Amazon FBA warehouse, then your unit landed cost will be $3.
This is the fee that Amazon will charge you to fulfill a single unit of product to a customer. You can estimate FBA fees using Amazon’s revenue calculator, or calculate them directly by taking Amazon’s formula and running through it with your product’s dimensions and product category.
This metric reflects your expected advertising efficiency level. It indicates how much you need to spend on PPC ads in order to generate $1 in ad sales. For example, if you spend 30¢ to generate $1 of PPC sales, your ACoS is 30%.
ACoS is impossible to accurately predict in advance, but on average, an established product might get an ACoS of roughly 30-70%. As such, you can use 50% as your baseline ACoS, and then play with this number to see how profitable your product could be at different ACoS levels.
Again, remember that your goal here isn’t to guess the exact ACoS of any given product. It’s to simulate product profitability using a range of ACoS values, and approximate the average expected profitability of each product you’re evaluating.
Also, it’s important to recognize that ad spend doesn’t simply generate ad sales. It also affects your organic rank, and as such – your organic sales. Therefore, advertising should be looked at as an investment that increases product visibility and generates an “indirect” economic return on top of PPC-attributed sales.
This is your percentage of sales that is generated through PPC advertising. If you sell 100 units and 30 of those came through PPC ads, your PPC share of sales will be 30%, and your organic sales will be 70%.
Needless to say, organic sales are much more profitable than PPC-generated sales. But that doesn’t mean that you want to minimize ad sales, since they can
- Generate incremental profit, and
- Boost the search rank of your ASIN, increasing its organic sales
Similar to ACoS, this data point is very hard to predict in advance. But for an average product, a steady PPC share of sales could be anywhere in the 10-50% range.
As such, you can use 30% as a baseline when forecasting the profitability of potential new products, and then play with the numbers to simulate a range of scenarios.
Daily unit sales
This is the number of units you expect to sell every day, on average.
You basically want to ensure that the product niche you’re getting into has enough demand, but doesn’t have excessive supply (competition) already absorbing that demand. So if you have a high-demand, low-supply, high-margin product – you’ve found a winner.
You can estimate sales volume using a Chrome extension such as Jungle Scout or Helium 10, or by looking at the number of reviews and competing listings for any particular product you’re looking at.
But keep in mind that sales estimates are just that – estimates. Take them with a grain of salt and make sure that regardless of projected sales volumes, the unit economics you’re looking at are solid.
Performing the unit economics analysis
Now you can start playing with the assumptions in the model (price, ACoS, PPC Share, unit landed cost), observing how they drive profitability, and through that gradually build a deeper understanding of the profitability potential of each individual product.
Only after having performed such sensitivity analysis (also known as “what if” analysis) do you then commit to particular products. This due diligence process will substantially increase your odds of being profitable down the line.
Here are a few examples of important questions you can answer using sensitivity analysis:
How efficient does my advertising have to be to generate an acceptable ROI?
You probably don’t want to get involved with a product that could only generate a decent margin if you were to be extremely efficient with advertising or undercut competitors on pricing. Sure, a product like that could still be viable given a high sales volume and ample resources to ramp it up, but it would undoubtedly be pretty high-risk.
To test, set the sales price in your model to a level similar to your competitors. Aso, set your ACoS to 50% and PPC share of sales to 30% (baseline assumptions). What are your resulting margin and ROI?
If your margin is < 20% and/or ROI is < 50%, you probably want to keep looking for a different product. This level of profitability may not be sufficient to offset the various risks of selling on Amazon.
What is my breakeven ACoS?
This is the ACoS at which your margin is roughly zero. In other words, you will start losing money on every sold unit as soon as your actual ACoS exceeds your breakeven ACoS.
If your breakeven ACoS is less than 30-40%, it means you will have to be extremely efficient with your advertising in order to generate a profit. Not a good thing. Try to find a product where your breakeven ACoS is at least 70-80%, while the price is in line with competitors.
How does PPC share of sales drive profitability?
Explore how profitable each product would be if ALL of its sales were organic (i.e. PPC share of sales = 0%).
What about 50/50? Compare a number of potential product candidates under the same conditions, and see which ones come out on top in terms of their expected unit economics.
In general, during the first few weeks after you launch a new product, virtually all of its sales will be ad-generated, not organic. As Amazon’s algorithm starts seeing that consumers visit your product listing, convert at an acceptable rate, and then leave positive reviews – it will start ranking your product higher and higher on the search engine results page, increasing your percentage of organic sales over time.
Ultimately, your goal is to launch a great product. One that customers will love buying and Amazon will rank highly – generating significant organic sales as a result.
What will my ROI and payback period be at different price points, ACoS levels, and sales velocities?
ROI (return on investment) is basically your net profit divided by your initial investment. So if you invested $1k into a batch of product, and earned a net profit of $500 from that batch, then your ROI is 50%.
ROI is probably the single most important profitability metric – it shows how efficiently you’re using capital to generate a financial return. And how much cash you’re tying up in the product. Your margin could be great, but if the product is very expensive, you’ll need to tie up a lot of cash in it – cash that could be invested in other products.
Likewise, your payback period is a crucial metric that shows how fast you can recover the cash you’ve invested into a particular batch. Payback period depends on the size of your batch, the speed with which you are able to sell through it, and the profitability level of the product.
When evaluating multiple products, you want to compare their ROI and payback periods under similar conditions. Which products looks best if we price similar to competitors? How about if we price a little higher or lower than that? What about different ACoS levels, as well as different sales velocities (daily unit sales)?
What are my breakeven price and ACoS under different conditions?
If your breakeven price comes out significantly higher than the prices of similar products on Amazon, you will be under a lot of pressure. That would mean that just to break even, you would already need to sell at a higher price than substitute (competitor) products. You want to avoid this at all costs.
Similarly, if your breakeven ACoS is too low, it means you’ll need to be very efficient with advertising to make a profit – which is inherently difficult.
You want to find a product where breakeven price is lower than competitor prices, and breakeven ACoS is at least 70-80%. Simply by having this as an additional criterion during your product selection due diligence, you will be far more thoughtful and scientific about your approach than the majority of sellers.
How would a $1 reduction in unit landed cost impact ROI and other KPIs?
One of the decisions you’ll need to make when launching a new product is order quantity.
The larger your order, the lower your supplier will be willing to go in terms of cost per unit. Delivering your inventory to Amazon will also be cheaper per unit as your batch size increases.
As such, you want to model the impact of every $1 reduction in unit landed cost on your profitability, and use that analysis to make smarter decisions about initial order quantities.
If you are able to generate $1 in savings per unit by ordering slightly more inventory, and this reduction in unit landed cost raises your ROI from 40% to 60%, it’s a no-brainer – you should order the larger batch.
Look for the highest profit potential
Profitability is a highly dynamic thing – it will fluctuate daily based on a number of variables. If you don’t understand which factors drive profitability, you will essentially be flying blind – guessing vs. relying on hard data.
So prior to committing any capital to new SKUs, it’s imperative that you model out their unit economics, spend time playing with profitability drivers and examining how they correlate with margin, ROI, and payback period – and ultimately make thoughtful, numbers-driven managerial decisions.
Do your research, model out the unit economics of the potential new products you’re thinking of launching, and simulate different scenarios to ultimately pick products that show the highest potential profitability under a broad range of scenarios.
This post was by Paul Faguet. Paul is the founder and CEO of Sellerscale, a managerial accounting platform for Amazon sellers. In the past, Paul was one of the first 200 employees at Uber, and launched Uber Russia – which was later sold for $1.1B. Paul also has an MBA from Cornell University, and built a 6-figure Amazon business prior to founding Sellerscale.