The Economics Behind Free Shipping Programs
Who is this for?
Read this if you want to promote a free shipping option to customers that is still financially feasible. Free shipping doesn't have to be simply eating the costs. There are ways to make the margins tenable, which begin with establishing the economics that best fit your business model first.
We have all seen the industry reports the last couple years, so there is no reason to belabor it: Consumers want their orders quickly; 36% say they will shop elsewhere if it's not available. We previously wrote a play on implementing a profitable 2-day shipping program because of this urgent importance to operators.
But did you know that free shipping is twice as important?
It's true, consumers vastly prefer free shipping over fast shipping if given the two options.
- Several industry studies publish numbers anywhere between 75% and 80% of consumers will shop elsewhere if free shipping isn't available.
- Offering free shipping was a growth driver for Amazon long before Prime came on the scene. Before Prime, free shipping was regularly the preference for customers over fast shipping.
- Zulily became the fastest growing ecommerce business of all time in small part because the business was oriented around free shipping.
You need a free shipping program to compete. But a strategy that simply eats the costs of shipping is unsustainable as you grow, so you need a smarter plan. This play walks you through the ideas to achieve a profitable shipping program.
Providing profitable free shipping is a financial problem (it's in the name—"free"), so most solutions will lean heavily on economics more so than hardcore physical supply chain hacks.
The story of free shipping is a story about margins. You must hit a margin target in order to make the option feasible.
Note that there are two margin targets to consider. One is per-order and the other is per-shipment. While similar, both are different ways to get economics to work in your favor. We will highlight which type of optimization matters when going through the plays.
Ultimately, profitable free shipping is a combination of two distinct areas of innovation:
- Economic and financial solutions. Manipulate the unit economics so that the cost of shipping is lower than it would have been. With better economics, you can get aggressive with implementing and promoting free and fast shipping.
- Which brings us to complimentary frontend and backend innovations. Once the economics are set, there are ways to incentivize affordable free and fast shipping options on the frontend, while ensuring the execution and costs of it on the backend are in alignment.
Discussing both is too large a topic for one article, so we have split them up. This article focuses on the economics of smart free and fast shipping programs.
Recasting Unit Economics
Financial innovation in this context means changing the economics that influence cost-per-unit metrics specifically, and operating expenses (opex) broadly. Let’s unpack that.
Global and Local Optimizations
Outbound shipping is a per-unit expense. Every order has (N) number of shipments to fulfill the order. Most of the time it's one shipment per order, but it could be two or more.
It turns out that outbound shipping is also the most expensive operating expense in a typical ecommerce P&L, which is considerably different from traditional brick and mortar business models. The industry average evens out to 12% of annual online sales, but your mileage may vary (literally).
|Example Annual Ecommerce Sales||$100,000,000|
|Average Cost of Shipping||12%|
|Total Shipping Costs||$12,000,000|
A company selling $100 million of merchandise a year will average out to $12 million per year in shipping costs. Yikes!
Therefore the single most important cost metric to improve is the cost of delivery. Even something as simple as saving 50¢ on shipping a $35 order seems trivial, but it is in fact one of the most meaningful operating optimizations you could make because it is a per-unit (or "local") optimization as opposed to a series of optimizations upstream (a "global" optimization).
Let's illustrate why saving a few cents per delivery has a 140x improvement on cost-per-unit metrics than halving inbound shipping costs. Warning: The math is going to get heavy, but it will be worth it because the big idea creates the foundational principle for inexpensive free shipping.
|Average Container Size (Shirts / Container)||80,000|
|Shipping Cost / Container||$1,500|
|Shipping Cost / Unit||$0.019|
|Shipping Margin / Unit||0.054%|
Pretend you are a fashion retailer that sells $35 shirts. A container arrives in Los Angeles housing 80,000 shirts (industry average). In addition, the average industry cost of shipping that container from Asia to Los Angeles is $1,500 (as of summer 2021), which comes out to $1,500/80,000=$0.019 cost per unit. What's important is margin, so the cost of inbound shipping is 0.054% of margin on a $35 shirt. Miniscule.
Let's say you improve the freight forwarding process that results in the inbound cost dropping to $750 per container. That seems like a lot because it's a 50% reduction across 80,000 units! But in fact, $750/80,000=$0.01 cost per unit, which even at 50% improvement in total costs, margin is only improved by 0.001%. Your cost-per-unit metric did not really improve relative to the shirt ASP, which means margins didn't improve as much as you would hope. That's a meaningless local optimization that doesn't move the global optimization target of increasing margin.
IMPROVED INBOUND SHIPPING
|Improved Cost / Container||$750|
|New Cost / Unit||$0.009|
|New Shipping Margin / Unit||0.027%|
|Total Margin Improvement||0.001%|
Now compare outbound shipping to the inbound shipping example above. Let's say, on average, customers buy 1.25 shirts per order, meaning most buy a single shirt but once in a while customers buy more. It costs $5 on average for a single shipment, which is actually a pretty good rate, and, for simplification, you've done a good job of making sure it's always one shipment per order. As a result, total shipping costs for that previous sample size of a container of 80,000 shirts comes out to $320,000, or outbound shipping averaging 11.43% of margin per-unit. (That's suspiciously close to the industry average of shipping costs being 12% of annual online sales!)
|Average Shirts / Order||1.25|
|Sales / Order||$44|
|Average Cost / Parcel Shipment||$5.00|
|Average Shipments / Order||1|
|Average Shipping Cost / Order||$5.00|
|Total Shipping Costs / Container||$320,000|
|Outbound Shipping Cost / Unit||$5.00|
|Shipping Margin / Unit||11.43%|
You now add another fulfillment location in the Midwest that that improves the average shipment cost by 50¢ to $4.50 because shipping distance is usually shorter. Now, when taking the previous sample size of a container of 80,000 shirts, total shipping costs come out to $288,000 for a total savings of $32,000, which is a lot more than $750 of savings on the inbound container!
IMPROVED OUTBOUND SHIPPING
|Improved Cost / Parcel Shipment||$4.50|
|New Shipping Cost / Order||$4.50|
|New Total Outbound Shipping Costs / Container||$288,000|
|New Cost / Unit||$4.50|
|New Shipping Margin / Unit||10.29%|
|Total Margin Improvement||1.14%|
- Reducing inbound container shipping costs by half only improved the cost-per-unit metric by 1¢. A paltry local optimization.
- Meanwhile reducing the cost of outbound delivery by a mere 50¢ improved the cost-per-unit metric by $1.40. That’s a 140x CPU difference! A much more meaningful local tweak that contributed to the global goal of better margins.
Now, to round out the case study, consider the different levers available to manipulate outbound shipping economics.
For example, let’s assume the prior improvements around average shipment cost are in place because of the new Midwest fulfillment center. However, because there are so many SKUs given the high variability of shirts, their sizes, and their styles/color, inventory is unevenly spread across multiple FCs.
When customers place a multi-shirt order, you regularly need to send “split shipments” meaning more than one shipment per order. One SKU is shipped from the West Coast FC and the other from the Midwest FC because that’s where those SKUs are located. Split shipments are margin killers.
In this scenario the total number of shipments per order ticks up 5% from an even ratio of 1-shipment-per-1-order. That means shipments-per-order is now 1.05. Let’s run the numbers again.
OUTBOUND SHIPPING WITH SPLITS
|Original Shirt Price||$35|
|Original Average Shirts / Order||1.25|
|Sales / Order||$44|
|Improved Average Cost / Shipment||$4.50|
|New - Average Shipments / Order||1.05|
|Updated Shipping Cost / Order||$4.73|
|Updated Total Shipping Costs / Container||$302,400|
|Updated Cost / Unit||$4.73|
|Updated Shipping Margin / Unit||10.29%|
Total Savings (Compared to original $320,000 outbound shipping costs per container at $5/shipment and 1 shipment/order)
Yikes. That small change crushed the total savings you made by reducing outbound shipping costs from $32,000 per 80,000 shirts (a container) to only $14,400 per 80,000 shirts. This is why reducing unnecessary split shipments by even a percentage point can have a major impact on margins and cost reduction.
Did you notice something? The local optimization of “inventory placement” upstream is now impacting the localized costs of outbound shipping downstream. This is an excellent example of how improving global optima is about understanding the most important localized steps to optimize.
The bottom line: The purpose of this demonstration is to emphasize how a local cost optimization does not always translate to impactful global optima. While you must make continual process improvements along the chain, it is important to choose the ones with the biggest impact. The net savings of focusing in outbound shipping over inbound shipping provides a better path to profitability, and is what frees up the capital to begin promoting competitive free shipping.
Minimum Constants versus Variable Scale
Unit economics related to outbound shipping always start with the minimums available. Shipping costs do not scale linearly up or down. Instead, you have a starting cost that sets the floor, and costs scale up logarithmically from there.
When negotiating carrier rates, you will be presented with a minimum. For ease of math, let's say the minimum is $5, meaning each shipment made will cost at least $5. Shipping costs do not "scale down" proportionally to your average order price, so whether the product you sell is $1 or $100, it will cost at minimum $5 to ship. If you sell $5 widgets, you'll never make a profit on customers who only order one widget.
On the reverse side of the equation, costs typically scale non-linearly from the minimum. Let's say your widget weighs one pound which costs $5 to ship. Selling and shipping two widgets, which now weighs two pounds, does not necessarily mean you pay $10 to ship. It might be a small increase like only $5.24 to ship.
This is how almost all carrier rates work. Use this to design financial models and policies to your advantage.
For example, you might make a policy to not allow shipping that is more expensive than the order amount. This would be a baseline.
Increasing Average Order Size
More likely, you will want to design programs around leveraging these economics to spur both growth and profit.
Put yourself again as the fashion retailer that sells $35 shirts. You are considering what types of promotions best lead to improved operating costs. Cart thresholds to invoke a free shipping option work great here.
If the shirt is $35, then buying three is $105. Shipping one shirt costs $5, or 14.2% of margin, while it turns out shipping three shirts only costs $6, or 5.7% of margin. Another way to say it is shipping three shirts together costs $6 while shipping those same three shirts individually would cost $15, so shipping together saves the company $9. Clearly, one of the best ways to improve margins is to improve average cart size.
In this scenario, the retailer might set a promotional threshold of "Free Shipping on Orders over $X" like the banners we often see.
This is because "saving" $9 effectively pays for the $6 to ship three shirts, netting the business $3 of pure profit for doing nothing more than simply shipping a few shirts together instead of individually. This is the math and logic behind every "Free Shipping on Orders over $X" promotion you see.
Subscription businesses offer a few additional economical levers.
The key benefit is not predictable revenue at an interval. That doesn't necessarily help the specifics of profitable free shipping.
Instead, what matters is the predictability of operations around the subscription order.
We wrote a play on how to manage subscription-based shipping, which goes into much more illustrated depth.
Here, we'll simply recap the key insight about subscription shipping:
- Because you know the committed delivery date, you can work backwards to pick the cheapest possible option that will deliver on that date.
- For example, if the cheapest method to deliver from the FC to the customer is USPS ReadyPost with an estimated 2-7 day window, you start checking around 10 days prior to the committed delivery date whether or not to ship it today.
- The end result is subscription shipments always being the cheapest possible method selection.
There are a few other tricks to consider with subscription business models, too.
The first relates to the bundling examples above. Subscription business models offer stronger promotion opportunities that lead to better margins. Some examples:
You are a healthy snack food subscription business that ships an assortment of items per month. July's shipment includes items that weigh a combined 0.7 pounds. It turns out your contract with USPS is such that everything under 1 pound is shipped the same rate. Therefore if you could add 0.3 more pounds to July's shipment, the fixed costs of shipping will be the same while increasing sales, thus improving margin and cost-per-unit metrics. But customers aren't paying for those things yet, so the marketing team does a flash sale concept to ask if customers would like to include one of Items A, B, or C into their July subscription box for an additional charge. Each of A, B, C are 0.3 pounds so any customers who purchase will lead to better profits.
Here, a team member is a customer of the Bright Cellars wine subscription service and gets 4 bottles per month. This is a targeted upsell meant to increment to 6 or 12 bottles, which not only impacts revenue growth, but will make the economics of shipping the order better for Bright Cellars.
Promotions and Samples
Samples are a great bundling opportunity, too. Now you are a haircare subscription business that ships whatever items customers select on a monthly basis. SKUs are variable weight, but since customers pick which SKUs match their needs, each shipment is usually different from the next. But after studying your customer base, you know that customers of a certain shampoo tend to enjoy a certain conditioner as well. It turns out the shampoo weighs 1.6 pounds, and your rate card changes at 2 pound shipments. It just so happens that you have small sample bottles of conditioner that weigh 0.3 pounds. As a result, the marketing team decides to include a free sample of conditioner in July's shampoo subscription shipment because it poses no additional shipping cost. By August, a major success! 20% of shampoo customers have opted to include a bottle of conditioner in their subscription as well going forward. You now get to send two SKUs per order instead of one, thus improving cost-per-unit metrics.
Thrive Market will sometimes throw in free samples with an order. Consumables—food, health and wellness, necessities—where there are a lot of SKUs and high variability of order profiles are the most fertile ground for this approach.
This brings us to loyalty programs. The king of the retail world.
Consumer loyalty within retail has been a desirable thing for decades. The single biggest reason comes down to balancing out customer lifetime value metrics with customer acquisition costs. Every time a previous customer purchases with you, the cost ratio to have acquired them gets better.
Loyalty helps with profitable free shipping, too, but in unexpected ways.
People point to Amazon Prime as the prototypical loyalty program with free shipping. There are many aspects to Prime, but as far as free shipping goes, the secret has little to do with the annual membership fee. The $119/year fee doesn't "pay" for free or fast shipping in totality like some would say. Instead, Prime created a loyalty incentive for customers to shop online with Amazon.com more than other websites. As a result, the average Prime member would spend several thousand dollars per year more than a non-Prime member on Amazon.com.
With more orders, and thus more shipments, it was easier to find economical innovations like bundling that led to better margins and profit. This in turn would allow for more available capital to promote continuously more aggressive delivery options (free and fast) that would prompt ever more buying with Amazon.com, and thus a virtuous cycle was born. It's just one piece of the larger Amazon flywheel, but it is an important piece.
Companies can certainly consider a membership fee concept to effectively subsidize free shipping. It's an option. But the key insight with loyalty programs is that good ones will catalyze more volume per customer, and, crucially, better performance among key economic metrics like average-order-value and average-order-size. Those unit economic improvements are what lead to financially feasible free/fast shipping options more so than any membership fee.
How Shipium Helps
A profitable free shipping program is primarily an economics problem, which requires a plan to solve intelligently.
Once a company has a plan, then executing it becomes the challenge.
The most important requirement to great execution is the integration of frontend and backend systems such that marketing teams can merchandize and incentivize behaviors that lead to good free shipping opportunities. As customers convert, the challenge shifts to connecting things like a delivery promise and order details with backend fulfillment operations such that outbound shipping decisions are optimized for improved customer experience and reduced costs.
This is precisely the problem that Shipium's platform addresses.
Customers integrate our product APIs into their technology stacks to help make a promise they can keep on their frontend stores, then keep the promise that they made with fulfillment operations.