Picture this: you’re getting ready to host a garage sale. You start putting your stickers on items, then freeze.
“How much is this worth?” you ask your nearest confidant. “Will they even pay it?”
Now take that same dilemma and push it to its maximum limits and you arrive at the challenge plaguing course creators everywhere:
How do I price my online course?
After you’ve put your heart and soul into a product, you want to see some returns on it -- but you also want to make sales. If you price it too high, you may never meet your profit goals, while if you price is too low…
You encounter the same cliff of missing your profit goals, or worse, leaving money on the table.
That’s where this guide comes in.
We looked at 132,323 course sales to get down to the bottom of this dilemma. Here’s what we found.
How we sourced online course pricing data
If you’d rather jump straight into the pricing data, you’ll want to skip down to the next section where we talk about the averages we found. But if you’re like us and want to know more about the data, here’s how we handled it.
We looked at our records of course sales going back to 2016 all the way up to August 2018.
We then pulled out all the free courses and set our price range at $5.00 and up, which left us with 448 unique products out of 132,323 sales.
We excluded values below $5.00 because, at a minimum, they’re not courses that can recover any of the costs incurred in their creation.
This is how the price range broke down in those courses:
As you can see, the overwhelming majority of courses fell within the $5-$50.00 range, and course prices began to whittle down the higher we moved up the price range.
Here were the top five most prolific categories:
- $5.00-$50.00: 175 or 39.06% of courses
- $50.01-$100.00: 84 or 18.76% of courses
- $100.01-$150.00: 34 or 7.60% of courses
- $150.01-$200.00: 30 or 6.70% of courses
- $200.01-$250.00: 22 or 4.91% of courses
After we looked at that, we removed extreme outliers from the data set.
If you’ve never heard of an outlier, it’s basically a data point which lies far from the normal distribution of the data. The below image is a good visual representation of a (sad) outlier.
The presence of outliers can throw your averages for a loop and give you inaccurate measurements, although mild outliers usually won’t impact the data too much. The outliers we culled were those more than $99.00 from the nearest data point.
I.e., we removed one course which sold for $1500.00 because its nearest data neighbor was only $1395.00.
As such, the minimum value in the data that we evaluated to give you averages was $5.00 and the maximum value was $1395.00.
Now, with that out of the way, let’s get to the good stuff.
What’s the average price for an online course?
The average sales price for courses in our dataset was $182.59, which is consistent with our earlier studies where the average course was $199.99 across multiple course providers.
However, the average may not be the best -- or at least, the only -- function that we should look at when evaluating this data. Instead, we should also consider the median.
Because our data distribution is so all over the place -- and we’ll dig into that a little bit more in a minute -- there are still a ton of milder outliers in our calculations.
This is all a very boring, technical way of saying that our median will give us a better idea of what the middle ground value for course prices is.
As it turns out, our median is $76.50.
But… what does that tell us and how is it so far from the average? To understand that, we’ll need to take one more foray into statistics.
We need to examine the central tendency, or standard deviation, of our data. This information will give us an idea of how closely distributed our data points are -- in other words, how near course sale prices are to one another.
It’s phenomenally high: 239.86, to be exact.
To give you an idea, most bell curves measure within three standard deviations.
In this model, 99.7% of the data falls within three standard deviations of the mean (average), while 95% falls within two standard deviations.
(I promise, we’re almost done).
In other words, I tried to make a graph of this, and it isn’t even a bell. It’s almost a broken taco.
Trying to visually convey just how astronomically large the current standard deviation is would be like trying to explain the difference between a gas station Slurpee and a pint of Cherry Garcia.
Sure, they’re technically in the same category -- frozen sugary treats -- but the difference between them is solar systems wide.
Here’s what I mean:
So this is all a very, very fancy way to say that the data is wildly in different directions, and although the average may not be a bad idea as a place to start, it fails to convey just how widespread the data is.
How should you price your course, then?
How to price your online course
If the average price -- $182.59 -- doesn’t have much statistical value for us due to the distribution, where do we go from here?
Let’s assume, at a minimum, that you want to at least price each course at $50.01 to $100.00. 18.76% of our total courses fell into this range, so it’s not an outlandish place to start for a new course creator.
Then, start thinking about the factors that impact the bottom line.
Like where you want your course to fall in the product demand matrix.
If you start your course pricing off in the $50.01-$100.00 range, your product will fall into the “mass market category.”
If you want to aim higher and try to hit that golden goose, your baseline pricing should fall into the $100.01-$150.00 range, instead.
But you can’t do that if you haven’t already built up an audience and a credible reputation.
Which leads you to this conundrum: if you price your course too high, you may not get enough sales to meet your desired profit goals or build your business so you can start pricing higher. (It might also put your products at an increased risk for digital product piracy -- ouch.)
But if you price it low so more people can buy from you, you may end up losing money when providing their customer support needs.
Such as in the below scenario: 28 customers sound great, but how much of the profits will you lose if you have to provide after-purchase support for those same customers?
What’s a solid place to start, then?
Begin with the following questions:
How much did the course cost you to produce? How much money will you need to make to recover the cost for the tools and time you devoted to creating your course?
At a minimum, you should aim to exceed your investment costs. But what if you want to reach for more than just low-profit margins?
If you aren’t sure how a profit margin is calculated, by the way, this is the quick rundown:
Here’s an example. Take David Hickman’s “Plan & Write A Novel In 90 Days (Or Less...)“ course, currently selling for $67.00.
Let’s say he sells 12 courses for a total revenue of $804.00 (12 x 67).
The cost to produce the course -- including his time and materials -- was $120.00. Since he only had to make the course once, we subtract his one-time expenditures from his total revenue to get the gross profit.
$804.00-$120.00=$684.00 (Gross Profit).
Now let’s add in marketing budget -- more about this later, too -- and say he spent $75.00 on marketing to those customers.
Take out that $75.00 from his gross profit and that gives us $609.00 before taxes.
Adding taxes into the mix at a rate of 10% ($60.09) leaves us with a net income total of $584.10.
So his profit margin calculation would look like this:
Convert it to a percentage (multiply by 100), and you get a very nice profit margin of 73%.
Here’s a quick worksheet for you to plug in your numbers and calculate your profit margin.