The Art of the WordPress Startup: Part 3
Startup Pricing 101
This post is part 3 of a series on how to launch your startup on WordPress. Last time I talked in-depth about a common question first-time founders have (how they should deal with competitors), and this week we’ll answer another one startup founders often have:
How do I figure out what price to charge for my product?
So there are a few approaches often discussed in the blogosphere that you can take here. One approach is to use your “gut”, but that doesn’t make much sense, as you’ll typically over or under value your product one way or another and sell yourself short. How can you sell yourself short if you over value/price your product? We’ll get to that in a minute.
Another is to take a look at your competition and price yours somewhat close to their closest offering. But this will likely fall short as well. Why? Because your product will be perceived differently by the end user due to a number of factors. Maybe your design is better and hence your perceived value is higher. Maybe you’ve been featured in a ton of major publications and hence your homepage has the icons of all the major hot spots in your field, so you’ve established better social proof than your competitor and can therefore charge slightly more. Maybe your reputation on Twitter sucks and you can’t charge nearly as much because of that. The possibilities are endless.
The point is there are a ton of factors that determine perceived value to a potential customer and you are likely not a perfect clone of your closest competitor, so you will each be able to extract different prices, even if your products are very similar (we’ll assume your startup built on top of WordPress is not selling a pure commodity like petroleum). So what does that leave us with? Economic theory.
Remember that economics 101 class you skipped in college that had the subtitle “Intro to Microeconomics“? Whoops. Probably should’ve have shown up for that one. Oh well, I’ll save you taking night classes at community and bring you up to speed. It was one of my majors in undergrad and I did pretty well in it, so you’re in good hands. If you’re saying to yourself “I know what he’s going to say… supply & demand, I already know that” then you’re off base. Economics is more complicated than that. That’s why they offer a Nobel Prize in it.
When most people think of economics they think of what’s called macroeconomics. It deals with the general economy, with topics such as GDP, inflation, unemployment, international trade and more. It also deals with supply and demand but not in the way we’re worried about. What we want to try and understand here is price elasticity of demand, which is the measure of responsiveness of the quantity demanded for a good/service to a change in its price. Did I catch a niner in there? Say what?
To make things less intimidating, let’s first define a few key terms we’ll be using:
Price = What you’re charging for your product or service. This is the price you’ll be showing on your landing page and what customers will see on their credit card statements. Forget about profit and costs for the moment. We’re only concerned right now with figuring out how to find the price that will maximize our revenue/sales.
Elasticity = How changing one economic variable (in our case price) affects others (in our case quantity demanded, aka how many units you’ll sell).
Ceteris Paribus = Translated from latin as “with other things the same”. In other words, keeping all else equal or unchanged. Why is this important? Because if you’re going to test how different price points affect the amount of units you’ll sell, you can’t be changing other variables. In other words, don’t redesign your landing page the same day you try a new price point. You won’t be able to determine if the increase or decrease in sales was due to your change in price or design.
Law of Demand = States that as the price of a product increases, the quantity demanded will be reduced. Conversely, as the price of a product decreases, the quantity demanded will be increased. There are only 2 types of products that violate this law, Veblen and Giffen goods. An example of a Veblen good would be the Bugatti Veyron. Because it costs over a million dollars, more people want them because they’re harder to come by. Think extreme status symbol luxury products. An example of a Giffen good would be rice. As the price of this cheap staple food rises, people can no longer afford to consume more expensive non-staple foods alongside it (think Chicken/Beef/Pork/Seafood), so they end up buying more of it (in this case rice). Picture the dad in a household in rural Mongolia saying something along the lines of “Rice has gotten so expensive that we’re no longer going to have rice & chicken for dinner, we’re just going to have rice.”
**The pricing discussion here assumes your startup built on top of WordPress isn’t selling Bugattis and/or rice. You’re selling normal products which aren’t Veblen or Giffen goods, and hence adhere to the law of demand.
Alfred Marshall = The baller/shot-caller who came up with all this price elasticity of demand stuff. Had the Nobel Prize in economics been around back in his day, he probably would have locked it up around 1890.
Okay, so now that we understand the basics of economics, what do we do with this newfound information? It’s pretty simple. We want to find what’s called Optimal Pricing, which means finding the price that maximizes your revenue. If you clicked over and started sweating when you saw all those scary equations, you’re probably not alone. So let’s do this in baby steps.
Step 1: Make an estimate of the price elasticity of your product.
All we want to do here is figure out how sensitive our customers are to price changes in our product. At one end of the spectrum you have products with high elasticity, meaning consumers are very sensitive to price changes, and at the other end you have products with low elasticity which are sometimes referred to as inelastic. Let’s look at an example for each end of the spectrum, keeping in mind that most products fall somewhere in between.
Pizza is considered very elastic, meaning if you jack up the price you’ll sell a lot less. Here’s what the graph of price elasticity looks like for a slice of pizza. Notice the angle of the line is about 45 degrees…
So if the pizza shop owner tries to charge $3 per slice, they’ll only sell 1 slice, so revenue is $3. If they only charge $1, they’ll sell 9 slices and revenue will be $9. But neither of those prices maximizes revenue. In this case, the optimum price is between $1.50 and $1.75 a slice. Both yield the highest overall revenue at $10.50 (7 slices sold at $1.50 provides the same revenue as 6 slices sold at $1.75). Here at Pagely, we’re in the web hosting business, where customers are pretty price sensitive (high elasticity) according to research, since we’re likely in the “mature” phase.
Gasoline on the other hand is considered inelastic, meaning if you jack up the price you’ll sell almost the same amount. That’s because people still need it. Here’s what the graph of price elasticity looks like for a gallon of gas. Notice the line is much steeper here…
Notice that if the station owner charges $1.10/gallon, they’re going to sell a little over 5 gallons. If they jack it up to $1.90 (nearly double), they’re still going to sell 4 gallons. Now look back at the pizza graph above and figure out what happens to that poor soul if they try the same trick. Their demand plummets and they sell way less. That’s why sales of things like gasoline and medications remain pretty steady in a recession, whereas non-essentials like spa services and expensive restaurants watch their sales tank. People need some things more than others. Another inelastic product would be public transit fares. If NYC raises the ticket prices, people will still buy them because oftentimes they have no other way to get to work.
Here are the revenues derived at each price point for our gas station owner:
$2.50/gallon x 3 gallons = $7.50
$2.40/gallon x 3.25 gallons = $7.80
$2.30/gallon x 3.4 gallons = $7.82
$2.20/gallon x 3.6 gallons = $7.92
$1.90/gallon x 4 gallons = $7.60
$1.30/gallon x 5 gallons = $6.50
$1/gallon x 5.5 gallons = $5.50
*Station owner maximizes their revenue with a price of approximately $2.20 per gallon.
Now that you understand price elasticity of various products, you can probably make an estimate of which side of the spectrum your product falls. Do people absolutely need it? Will a change in price affect the number of units you sell by much? We don’t need to do any fancy equations here or solve for the actual coefficient, but we should understand how our potential customers will react to price changes and set our expectations accordingly.
Step 2: Now it’s time to do some real-world experimentation and testing.
The best thing to do here is to first run some A/B tests with a tool like Optimizely and figure out which type of landing page works best, given whatever prices you have set initially. So maybe design/layout A converts at 10% and design/layout B converts at 5%, so we know A is better and we now just want to figure out what price will maximize our revenue using design/layout A which we have decent confidence in. If you’re further along in your startup and have already done A/B testing, then that’s good news.
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Remember that term we defined above, ceteris paribus? This is where it comes into play. If you’re going to experiment with different price points to see which one maximizes revenue, you need to try and make sure you’re only playing with one variable at a time (in this case price). As you test various price points on your landing page, make sure you are keeping all else constant in your business as much as possible. That means no layout or design changes while testing, no pursuit of major press coverage, and no fiddling with your AdWords budget and bidding. Ideally you want to isolate as much as possible. Otherwise you’ll be confusing correlation with causation.
So take a period of X months (depending on how much traffic you get) and try adjusting your price for statistically significant periods of time. In other words, if your website gets 1000 visitors a day, you can likely get some good test data in a week at a certain price point. If your site gets 10 visitors a day, you may need to test for weeks or months at a certain price point to feel confident in your data. While testing various price points, take notes of any events that happen. Did some blogger happen to write about you during a particular week that was beyond your control and might have spiked your sales? Make a note of it so you remember to consider it when analyzing your data. If you have a subscription driven business, use something like Recurly to track your stats in greater detail so you know you’re using accurate data in the event your admin dashboard/tracking is less than awesome.
What else can I do to maximize my revenue besides finding the optimal price?
Make your product as inelastic as possible, meaning customers will be unable to live without it, so you can charge more without killing demand. Google and Apple have done this by creating entire ecosystems that revolve around their products. Are you an Apple user and have spent a ton of time building up your iTunes library and have finally gotten iCloud backup just the way you want it? Apple has just made their product more inelastic because you’re still going to want the next iPhone even if they jack up the price. In other words, make it so your customers cannot survive without your product/service. Here you are increasing the “stickiness” and “switching costs” of your service.
If you’re running a SaaS, like so many do, offer different types of plans at different price points that appeal to a variety of users. Let them pick which one suits them best. If Pagely only had one plan, we’d probably see a dip in signups. How many plans do you need? Most startups tend to go with a number between 2 and 5, and it varies by industry. Figure out how many customer “types” you have and then create a corresponding plan for each one.
Full Series – Click here to see all articles in this series.