The Wall Street Journal published an article detailing the customer fees for restaurant delivery services. The below chart juxtaposes these values from the leading delivery providers. Keep in mind these fees are likely closer to true costs as investors have pulled back on subsidies and companies like DoorDash are announcing positive unit economics for their operations on a per-order basis.
At first blush these numbers look reasonable: a delivery from Amazon costs the same as a delivery from a well-established pizza company at around $3 per order.
But this is only showing the cost of delivery to the customer.
What it’s not showing is the even higher amount that’s being passed to the low margin merchant. These delivery services charge merchants an additional fee of 20-35%, and that’s not including the sometimes-markups on items. For a $25 order, this accounts for another $5 to $8.75 in fees.
If we want to be honest about the economics we need to ask if a customer would be willing to pay $8 to $11.75 on a $25 order. Surveys definitively say the answer is most likely no.
There are a few points that need consideration.
First, consumers are increasingly demanding the convenience of delivery, so shouldn’t I provide it? You have to weigh the costs of providing this service. Merchants have proven time and time again that undertaking anything remotely technical in-house becomes a financial disaster. If the only two options are to partner with a third party or build it internally the latter should never be considered, especially if you’re a restaurant.
Second, aren’t these delivery services producing incremental customers? That’s a great sales pitch, but do they ever prove it? A simple litmus test is to see if a customer from one of these providers was a customer previously. This can be done by looking at credit/debit card numbers of guests (which are encrypted but each encrypted hash is unique). A half measure is to see if a customer generated through these services uses your own service on the second visit. In other words, is this customer only using an aggregator to find you and racking up a 20% commission on each subsequent visit or are they going direct to your site after thereafter?
Third, and related to the second, aren’t the customers being generated from delivery providers higher margin since they’re incremental?
This takes us a little deeper into math but it’s something every merchant needs to understand about their business. Because the reality is that you need absolute conviction in your numbers to emerge unscathed.
For the sake of our analysis we’re only going to consider two costs: the costs of the food (COGS), and the cost of labor. The fixed costs like overhead and equipment we’re going to ignore since they’re arguably there to run the walk-in portion of the business.
Labor and COGS are what’s typically referred to as prime costs. These two equate to 50% – 60% of a restaurant’s costs when summed (legislative labor pressures are increasing these costs but well-run operators are finding ways to replace manual hours with automation). The remaining 50% are reserved for things like rent and utilities, supplies, repairs, marketing, etc.
The net result is that a restaurant can expect a pretax margin between 2% – 6%. That amount is obviously much smaller than the 20% – 35% commission fees for orders passed through a delivery service. So what has to happen to make this math work out?
Let’s assume a customer’s check is $10 on average. $0.60 (6% of the $10 check) of that is generously pre-tax profit. $5 (50% of the $10 check) goes to prime costs: labor ($2.50) and COGS ($2.50). Let’s also assume that the $2.50 in labor can produce 100 checks per hour and this is a maximal rate. So, 100 checks per hour * $2.50 in labor per check = $250 in hourly labor costs lest you risk understaffing.
The reasoning of these third party providers goes something like this. You’re already paying the $250 in hourly labor whether you have delivery orders coming or not. So if you’re paying $250 for an hour of labor and you’re producing less than 100 checks per hour, a third party can help you reach your maximal throughput limit. Here’s an example:
Restaurant spends $250 on labor from 1 PM to 2 PM. During that time period there are only 50 checks at $10 per check. COGS of those 50 checks is $125 ($2.50 COGS per check * 50 checks). Labor cost, however, is now pretty high: it’s $250 over 50 checks, or $5 per check. So now your prime cost is COGS + labor = $7.50 per check, or 75%.
That ain’t good.
The delivery service adds 50 checks from 1 PM to 2 PM. Since your labor is already “fixed”, those 50 checks from that delivery provider have “no” labor cost and are thus “incremental”. So using the third party’s math, your profit per check rises from $0.60 to $3.10 ($0.60 + $2.50 in “saved” labor) on those 50 checks generated by the third party delivery provider.
Except we now have to subtract the third party’s 20% – 35% commission.
So a “profit” of $3.10 falls to $1.10 if the commission is 20% (-$2.00) and even further to -$0.40 if it’s 35% (-$3.50).
But we’re not quite done; there’s one more HUGE wrinkle in here.
Labor isn’t simply a flat number: it’s divided between back of house (BOH) and front of house (FOH). BOH are your staff making the food (chefs, etc.) and FOH are staff serving the customers (cashiers, waiters, etc). In many states FOH labor is actually cheaper than BOH labor because FOH is expected to earn tips. In Texas, the hourly rates for FOH staff is $2.13 while they’re $7.25 for BOH staff.
Delivery orders shouldn’t materially impact FOH operations. So for the sake of our labor argument we should reasonably expect to subtract FOH labor costs from delivery orders. But only a crackhead would believe there’s “no” labor cost associated with turning out the delivery orders. We’re going to assume that FOH labor cost is the same as BOH labor cost, even though the latter can be more than twice the price of the former as shown in our Texas example.
Returning to our example above, we’re spending $250 an hour on labor from 1 PM to 2 PM and only have 50 checks at a $10 check average that the business generated over that period. Now we’re going to add 50 more checks at a $10 check average from a third party delivery service. We decided to weigh FOH and BOH labor equally, so the $2.50 labor cost per check (which came from our prime cost equation) is really $1.25 FOH labor and $1.25 BOH labor.
For the 50 checks generated by the restaurant, our labor is the full $2.50 per check since it takes both FOH and BOH labor. This comes to $125 in labor costs. However we’re NOT going to believe the delivery party’s story that we have to spend $250 on labor for the hour. Let’s assume we can go ahead and cut labor that’s not being used, or even better that we used an analytics tool that more accurately forecasts what our labor should be based upon customer traffic projections.
Now 50 orders come in from the delivery partner. These orders must be made, so we’re going to apply the BOH labor cost of $1.25 to each order. $1.25 * 50 checks = $62.50. Our total labor for 100 checks is now $125 (from the restaurant’s own 50 checks) + $62.50 (50 checks generated by third party delivery provider), or $187.50.
What this really means is that those checks generated by the delivery partner DO have an associated labor cost of at least $62.50. So we need to make sure to subtract this from the prime cost of the checks to find our profit.
Our starting profit was 6%, or $0.60 of each $10 delivery check. COGS is our expected $2.50 but our labor is now higher than $0: it’s $1.25 per check. So this leaves us with a profit of $1.85 per delivery order ($0.60 from original check margin + $1.25 in “saved” labor by avoiding FOH labor costs).
Except we now have to subtract the third party’s 20% – 35% commission.
So a “profit” of $1.85 falls to -$0.15 if the commission is 20% (-$2.00) and even further to -$1.65 if it’s 35% (-$3.50).
What’s happening?
What’s happening is that third party delivery companies are hoping that restaurants have at least one of the following attributes:
- A bad labor model with chronic overstaffing that leads to idol BOH labor
- Staff that can be motivated to increase output per unit of BOH labor
- Delivery orders with materially higher check averages
- Very bad math skills
A best-case scenario for a third party delivery company and a merchant is a combination of #2 and #3, where the restaurant is already running ideal prime costs yet somehow squeezes more production out of their BOH staff to handle delivery orders. Even then, the restaurant is going to need a lot of help in the way of lower commissions to find profit on the services unless the check sizes are substantially larger. Here’s that math for an example.
We’re going to assume that the delivery check is 25% larger than a walk-in check, so $12.50 relative to $10. The COGS still hold at 25%, which is now $3.13. All the other overhead ($5 – $0.60 in profit = $4.40) stays the same. So let’s subtract the COGS and overhead from the $12.50 check: $4.97.
We’re going to assume the BOH labor is the same value it would be to produce a $10 check ($1.25). We now subtract that from $4.97 to get a “profit” of $3.72 from the delivery order.
Except we now have to subtract the third party’s 20% – 35% commission.
Now a “profit” of $3.72 falls to $1.22 if the commission is 20% (-$2.50) and even further to -$0.65 if it’s 35% (-$4.38).
So even with 25% increased check sizes these third party delivery companies can kill the merchant’s economics if commissions are too high.
And by the way, this still doesn’t take into account the need to forecast delivery orders so as not to overwhelm the kitchen. What if the third party delivery company delivers so many orders that the dine-in customers are waiting a long time to receive their food? That’s going to slow down kitchen output across the board, and why good ordering systems order throttle.
This third party delivery game is a very delicate business model riding on thin margins and fuzzy outcomes. Every merchant needs to do this math for their own operation to see if it makes financial sense.
Luckily for you we’ll be releasing a calculator that allows you to do this math for yourself. Stay tuned…
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