📊 How to Forecast Retail Sales for Amazon and DTC Brands Looking to Make the Transition

When you reach a certain critical mass with your online sales channels– Amazon, DTC, marketplaces– the next logical step for growth is retail. So, you get on the phone and start calling buyers, right?

No. Not quite. First, you have a lot of upfront work to do to determine if retail is even viable for your brand.

The good news is that planning and forecasting are pretty straightforward processes for the sector, if you know what you’re doing.

If you take the time to forecast your retail sales properly, you'll not only understand the potential of the channel—you’ll know what kind of capital, inventory, and operational support you’ll need to get there.

Here’s a simple breakdown of how Amazon-native and DTC brands can forecast their first few years in retail, starting from the ground up. This post focus on top line sales forecasting; we will touch on forecasting additional costs in another post sometime in the future.

🕰️ First, Accept That This Takes Time

Here’s the hard truth: getting your product into a national retail chain takes about a year—just to start. And that’s after you get the buyer to say yes (chasing that “yes” could add another year to the process). You will need patience for this endeavor. 

With any major chain, you’re likely going to start in a series of test stores. You can ballpark this at 5-10% of stores (e.g. a 250 store test at a chain of 4,000 would be pretty standard).

Understanding this growth pattern is crucial for good forecasting. And a good forecast helps you:

• Anchor your expectations to reality

• Identify when you'll need cash for inventory

• Prioritize which accounts to target first

• Make informed hiring and operations decisions

🔍 Start With What You Know: Your Amazon Data

Your Amazon sales history is the single best predictor of retail performance. Here’s what to look at:

• Sales velocity: How fast does your product move on Amazon today? Are you a $1M/yr brand, or a $10M/yr brand? Your total velocity is a good indicator of A) how easy it will be to sell into retail, and B) how well you will sell on the shelves once in place.
  

• Relative performance between SKUs: If Product X sells half as well as Product Y online, it probably will in stores too. Use that knowledge from your existing channels to anchor your items’ relative sales velocity to each other in your forecasts. Such proportionality usually carries over.

• Competitor Benchmarking:

• How do your products rank in your category?

• How many reviews do you have compared to competitors?

• What’s your price versus theirs?

• Can you ballpark their sales using tools like Jungle Scout, Helium 10, or SmartScout?

• Then, if you can find public sales data for any of those brands that sell in retail, you can proportionally benchmark against that data. [more on this below]

Be sure to think in retail terms, especially around PPC and other marketing spend. Without ads, ask: Would this product move off a shelf on its own?

You’ll need to make some inferences—but do your best to anchor your estimates to real data, even if the numbers you are using are proportional and not nominal. You should be building out a model that allows you to quickly adjust input values as you gather more information.

So you have a decent idea of how big you are vs. your Amazon competitors, and the size of the market. Now, you need to

🏬 Do an In-Store Assessment

Next, go visit the retailers you want to sell to. Walk the aisles. Take pictures. Capture:

• Price points

• Package sizes

• Unit counts

• Value tiers of $/oz, $/unit, etc., for the premium, midtier, and low cost items.

Look at what’s actually moving (where are items low?) and where your product would fit on the shelf. Compared to what’s there, do you have better value? Better product quality? You may have to adjust your selling price to fit the consumer's needs in-store. You can do this by variating your product through different volumes, pack sizes, or item add-ons.

📈 Get Some Benchmark Data

You’ll also want some broader velocity benchmarks for your category. Here are a few free/low-cost ways to start:

• SPINS Free Reports (natural/organic categories): spins.com/resources

• Statista (limited, but sometimes helpful): statista.com

• ChatGPT or Claude: Ask for typical unit sales for your category, but double-check anything they give you.

• RetailDive, NielsenIQ articles, and sometimes LinkedIn posts from brokers or category managers.

If you’re totally at a loss for a benchmark, a rough starting point for many CPG categories is 1 unit per store per week (UPSPW). Some products will be higher, others lower. You’ll adjust as you learn more. But the 1 UPSPW starting point makes the numbers easy to work with, and is surprisingly realistic across a number of categories.

🧮 Build a Chain-Level Forecast

So you know where you want to sell. You have a couple items picked out. You know their sale price, and from there you can estimate their wholesale price (50% off retail price is a good place to start, but research your category). Once you have your potential per-unit revenue figured out, you’ll next want to map out how and when you will start seeing sales.

Retailers typically follow this rollout cadence:

1. Year 1:

• Test in 5–10% of stores

• 1–2 SKUs only

• Assume a 12-month runway from first meeting to on-shelf test

2. If the test goes well, Year 2:

• Chainwide rollout, or as many stores carry your category.

Functionally, the orders for that process look like this:

• Load-in order: Usually 2 case packs per store to start. That’s enough for 6–8 weeks of sales.

• Reorders: Weekly or biweekly orders that track to sell-through.

• The longer an account is in a steady state, the more your purchase orders will start to match the sell-through rate. At first it can be chunky, and many categories experience seasonality.

The basic formula for annual sales becomes:
UPSPW × store count × weeks in place x wholesale price = Revenue

Example:
1.5 UPSPW × 500 stores × 52 weeks x $10/unit = $390,000/yr

A very simple formula, but only as good as your inputs.

🏁 Create a Multi-Year Forecast

Repeat the chain-level forecast for your top 10 target accounts. Expand your salesplan to target another 20+, less ideal, but still suitable, accounts.

A realistic growth scenario might look like this:

• Year 1: Launch with 1 chain in a small test.

• Year 2: Expand nationwide at that chain, add 1–2 more retailers in test.

• Year 3: Roll out those chains nationwide, add 2–3 new chains.

• Beyond: Layer in smaller accounts, regional players, and new SKUs.

Over time, your annual retail sales start to snowball—both through new doors and through more velocity in your existing ones.

⚙️ A Forecast Is a Living Document

This isn’t a one-time spreadsheet exercise. Your forecast should evolve as you:

• Learn actual retail velocities

• Gain new insights from Amazon

• Win (or lose) accounts

• Adjust pricing and packaging

• Build operational scale

But even your first draft is powerful. It tells you where to deploy capital, when to make inventory bets, and what your upside could look like in 3–5 years.

🚀 Ready to Start Planning?

I help digitally-native brands use retail forecasting to build go-to-market plans, and avoid expensive mistakes.

If you’re preparing for retail expansion—or just trying to figure out if the channel is worth it for you—let’s talk.

I’ll help you build a plan that makes your retail launch a realistic and predictable path to growth.