Pricing, especially for software products, is one of the biggest levers for increasing revenue through new and even current customers. It’s very important to get it right, and to experiment occasionally. (I know because I’ve done it for companies.) It involves a lot more than growth-hacking the pricing page.
For instance, some utility might save hundreds of hours and thousands of dollars over the course of its usage, which is tremendous value. Yet if the average user expects that it should cost no more than, say, twenty dollars, that's what they'll be ready to pay.
This is why anchoring is beneficial, it gives you the opportunity to tilt that expectation a little bit.
Is that "tricking the user"? Arguably, but since you can't know the value users will actually get out of your product, any claims in that regard will fall under "marketing BS" as well. Pick your bullshit wisely.
Most companies aren't actually all that efficient, they are very good at creating busywork. Lots of human factors are at play. Changing workflows is a tough sell.
Also, what's a "demonstrable" saving? Sure, I can sing the praises of my product, of course I will. I can bring testimonials. The person at the other side will not take it at face value.
They have a budget, they have an expectation of how much to spend. They can't just add my promised savings to their budget. Nobody is getting fired for wasting money on the purpose it was already budgeted for.
It is indeed highly subjective to the user. So, part of the job of marketing is, segment your market, decide which one is most lucrative, target them with pricing that optimizes the outcome for that segment, and then adjust the product packaging to give yourself the most flexibility to attempt to repeat the process with the next segment of customers.
You learn the value your users get from your offerings by talking to them.
From 10+ years of watching this conversation recur on HN and talking to people running businesses, it seems like probably one of the most common mistakes business owners here make is trying to target an overly broad group of customers, and setting a very low ceiling on their prices to make sure everyone in that group can afford the product. That never seems to work well. On the other hand: setting a price for your product that only works for customers who can put it to extremely lucrative use? That's a strategy I've seen succeed a bunch.
It all depends on your product and your company; you can win big with fixed (maybe low) prices and a huge, undifferentiated customer base, if the stars align. They seem not to most of the time.
That all implies that there is such a lucrative group that has the expectation to pay a handsome sum for your product. It implies that there is no competition that has already driven the price into the ground.
If your product is truly novel and there is no competition, better set a higher price. You can always go lower and see how much more revenue you can get. Over time however, competition will show up and put the price closer to cost, or even below cost. Users will no longer expect to pay the older prices, so they won't - no matter how much value they get.
Yes, "might":
> you can't know the value users will actually get out of your product
So the problem you have is that you think (but don't know) that your product is much more valuable to your users than they think it is (since they're only willing to pay $20 for it).
You're not going to fix that problem by hacking how your pricing is presented on a web page. Which is why people view trying to fix it by hacking how your pricing is presented on a web page as "tricking the user".
> This is why anchoring is beneficial, it gives you the opportunity to tilt that expectation a little bit.
If your program is actually worth thousands of dollars to the user, but they're only willing to pay $20 given their current knowledge, you don't want to tilt their expectations by "a little bit". You want to tilt their expectations by a couple of orders of magnitude. Which, as noted above, is not doable by hacking how your pricing is presented on a web page.
No, the problem is that whatever you think your product is worth is irrelevant. What matters is your costs, that puts the bottom on the price, unless you want to burn cash for growth. Your customers expectations are the ceiling.
Of course all your customers are not alike and maybe there's 10% that would pay so much more to outperform the other 90% in revenue. That's when upselling comes into play, or maybe you want to focus only on the 10% entirely.
> If your program is actually worth thousands of dollars to the user, but they're only willing to pay $20 given their current knowledge, you don't want to tilt their expectations by "a little bit". You want to tilt their expectations by a couple of orders of magnitude. Which, as noted above, is not doable by hacking how your pricing is presented on a web page.
It's not doable at all. Nobody who expects to pay $20 for something will shell out $200 for it, unless they have looked everywhere and figured that everyone else charges in the same ballpark, or that you are the only option and they really need your product.
Anchoring isn't magic, it's the same kind of trick that makes $9.99 appear substantially cheaper than $10.00. It'll give you a slight boost.
Ok, so in the situation you describe, what are your costs? If that's so important, why haven't you told us what it is?
> Your customers expectations are the ceiling.
Your customers' expectations are based on what they think the value of the product is to them, which is based on what they think the product can do for them. If your product is worth $1000 to a significant number of customers, it must be able to do valuable things for customers that products selling for $20 a unit just can't do. Tell your customers what those things are, and their expectations will change.
What is true is that the number of customers that can get $1000 of value from your product will be significantly less than the number that can get $20 of value from it. But it makes a big difference whether the first number is zero (or close enough to it to make no difference) or a significant fraction of the second number. Your hypothetical was that it's the latter.
If something saves me thousands of hours, I am not likely to both miss that fact and stay in business to be a customer for long.
Sellers have a harder problem figuring out what consumers value. The solutions to that are things like collecting useage data, eating your own dogfood or BYOC (be your own customer), outright feature requests, competitor's decisions ( which are market-proven value assignments) etc.
Also 0.xxx versions serve this purpose- it's partially a pre-market exploration of the value of features before a pricing / version segregation attempt is made .
There's just no way consumers doesn't know what they value when they use it or its not there.
There is a class of things which consumers dont' know they value because they've never had it to value in the first place (Pinterest, Instagram) but that's a different thing than assigning different values to different aggregates of established features.
Hmmmm... maybe.
That said, I would say that they are more often just a way for a company to price their products in a way that more accurately reflects the value to the purchaser.
The easiest example of this is anchoring. The difference in a pricing page that offers 100-220 and a page that offers 100-220-500 is typically very large, and that’s true even if no one selects the 500 option! Having that high end third option effectively gives folks the permission to select a more expensive option that probably has more utility for them and/or their organization.
You're assuming that just, you know, telling your customers about what extra features they get in the more expensive 220 option isn't enough to persuade the ones for whom it would genuinely add value to choose it.
Which means either you aren't communicating your features effectively (and you should fix that instead of worrying about hacking your pricing page) or you think your customers aren't capable of judging what's in their own best interest given accurate information, so you have to manipulate them for their own good. The GP, by saying "this is all about tricking people", is simply expressing what to me is highly justified skepticism about the latter position.
Not if nobody actually buys it, which was a premise of that particular example.
All of this is just effective communication.
In fact, considering that all we have available is the end result of the operation, I think the "effective communication" hypothesis is much stronger supported than the "tricking" hypothesis.
We have the result that more people bought the 220 option when the 500 option was offered.[
We do not know that still more people wouldn't have bought the 220 option if its features had been effectively communicated. If the 220 option really is a better deal for many customers, telling them so directly would seem to be a better strategy than hinting it to them by providing a 500 option that nobody actually buys. But this strategy was not even tried.
I don't see anywhere in the article where it tells how they tried telling customers the advantages of the 220 option and how it would be a better value for them.
That said, the more I have learned about psychology and behavioral economics/finance, the more I have come to understand that humans are fundamentally irrational (at least on a surface level). The more I use that as my operating assumption when modeling customer behavior, the more accurate my models have seemed to be.
On the surface, that seems to be a depressing assumption to make about humanity. What I have come to understand/believe is that the surface level irrationality of most customers is actually fairly rational once the whole person is taken into account — especially their psychological make up.
Using the 100-220-500 example, some people will rarely or never take the highest priced option of something. They use this as a (useful, imho) quick and dirty heuristic to avoid being or being seen as a spendthrift. You seem to be assuming that everyone has the heuristic of “what's in their own best interest given accurate information”, and my data over the decades is that this stance is relatively rare (<10% of a diverse group of people). To be fair, it is a more common amongst the pure/hardcore hyper-logical engineering crowd that are probably much more common in places like HN, but that is a very small percentage of most markets.
Note that “not being a spendthrift” is just one common heuristic. Another is “not being or being seen as cheap”. Another is “not being seen as different or rocking the boat” (this is why “most popular” works as a label on an option). Another is “being seen as rich” (some folks will just go in and buy the most expensive option as the default) or “being seen as significant” (patio11 has an example of his Japanese manager not being willing to take a smaller SAAS option because he didn’t want to present the label “freelancer” on an expense request).
The list goes on, and these are all very real heuristics that people use to make decisions — and they use these heuristics much more often than a holistic analysis of what is best for them or their organization.
Given the above, are these techniques “tricking people”? Maybe. I personally consider them to be tools that can be used responsibly or irresponsibly. An organization with rock solid ethics can use these techniques to hack their users brains to get them to more accurately do what is in the purchaser’s best interest. At least that is my opinion and my approach. YMMV.
While I agree that people are far from perfectly rational, I strongly disagree with the viewpoint you are taking here. You do not know what is in the purchaser's best interest. Only they do.
Remember that the maxim that humans are far from perfectly rational applies to you too. If you think you are hacking users brains in their own best interests, is that really true, or has your own brain figured out a fancy rationalization that lets you do what's in your best interests even if it harms others? My money is on the latter.
1. In many/most cases, there are a very limited set of user profiles that can be used to model purchaser behavior. A well-designed pricing scheme will accommodate these purchasers needs and wants. In some cases, a good pricing scheme will push the purchaser to be more analytic in matching their package with their actual needs (e.g., by not presenting them with an option that can satisfy a default heuristic that may not be useful in the specific purchasing context).
2. (See 2a for a succinct summary of this point. I am leaving this hear because it is a decent example.) In many cases, the consumer is price indifferent -- most or all of the options work for them, and the price (within a relatively wide range) will not make a difference in whether to purchase or not. In this case, it is in the provider's best interest to maximize the price. A simple example of this is the wine prices at my friend's winery. He makes a ridiculously good wine, with a very low tonnage per acre (leading to a very concentrated flavor), high quality french oak, etc. The amount of wine that they can make like this is limited by the terroir and the amount of land they own. Folks who are willing to buy wine of this quality are fairly price insensitive -- they just want a really good wine and (ideally) a really good story to go along with it. While his other wines are in the $20-$60 range, these top end estate wines are much higher (and should be even higher, imho). The folks who can pay $120 a bottle can pay $150 or $180, and that difference is insignificant to the purchasers. Their only top end is that they don't want to seem like they were ripped off, which basically means "not as high as their favorite hard-to-get wines". The extremely high margins on these wines make a real difference to my friend's bottom line.
2a. Let me try to summarize #2 better. Most cases of pricing have some sort of pricing asymmetry -- that is, the price within a wide range doesn't matter for one party, but it matters a lot, often on an existential level, for the other. Optimizing what the price-indifferent party pays is a reasonable and logical decision, imho.
3. Your are absolutely right that I have created a fancy rationalization for myself. I am both aware of that (and try my best to keep it in check), and I am OK with that -- it's a very human thing that allows us to live without falling into analysis paralysis.
4. Given #3, understanding why people make the decisions they do has literally been a lifelong mission for me. When I was in high school and early in college, I assumed that people were hyper-rational like I thought I was (I was not), and I assumed that all they needed was accurate information in order to make the "correct" choice. I cannot begin to tell you how wrong I was. What I have learned in behavioral psychology, behavioral economics/finance, and cognitive development has shown me that human needs and wants are shaped by a variety of factors. That said, the potential range of complex factors is actually fairly limited, but it is not as limited as "make a rational decision on the needs of the immediate context". Far from it. This is an area of specialty for me, and I consider it to be a very powerful specialty. I will admit that it gives me a massive unfair advantage in a lot of interactions. That said, I try my best to use my specialist knowledge responsibly. I don't always succeed, but I definitely try. When I am able to help people make better pricing decisions using my specialist knowledge, I do it with holistic good intent (whatever that means). I hope you can appreciate that not all sales and marketing actions are inherently evil, and an incredible amount of purchasing decisions happen in the realm of "price within a wide range does not matter for one party".
I hope you find this post informative. If you still think that price optimization is an elaborate scheme that tends to harm other people, then I am happy to agree to disagree and move on. That said, I hope my reply has shown that the issue has many layers of complexity that most people do not consider.
I find it very informative about how you determine what pricing scheme is in your best interest. I see nothing whatever that justifies your earlier claim that you somehow know what is in the purchaser's best interest.
To be clear: I have no problem whatever with a seller who tells me up front that he is out to get the best deal for himself that he can and that's all he cares about. If I choose to buy from such a seller, I know what I'm getting into and I might still choose to buy if I am getting a reasonable deal for myself. There is often plenty of room for a win-win between two parties who both are seeking to maximize their own self-interest and don't make any pretense about knowing what's best for the other party. That is basically what you are describing in most of your post.
What I have a problem with is statements like this:
> I assumed that all they needed was accurate information in order to make the "correct" choice. I cannot begin to tell you how wrong I was.
The problem I have is that this statement contradicts what you yourself describe in the rest of your post. When you say that there are situations where the customer is price indifferent, you are not saying that they are irrational. You are saying that, given their particular situation, they are rationally being price indifferent--because the price literally does not matter to them as much as other factors. (For example, customers who are willing to pay $150 or $180 for a bottle of wine instead of $120 are not being irrational in paying more--the difference in price is literally negligible to them in comparison with, for example, not having to take a lot of time to find a good bottle of wine.)
In other words, I think you would be more honest to just admit that you are getting the best deal for yourself as a seller that you can, and that you expect your customers to get the best deal for themselves that they can, rather than claiming that you somehow know better than they do what is in their best interest.
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1. A software company that most people here would recognize (and many use) asked me to find out why corporate/enterprise users weren't upgrading from the free and low-cost plans to the upper tiers. After extensive research and customer interviews, I identified five main benefits their enterprise users were getting from the platform.
The twist: Four of those five benefits were available on the free plan. And the "premium" features on the top plans were of no use to them. No wonder they weren't upgrading.
Soon after, the company overhauled their pricing plans to capture more value ($$) from the benefits they provide.
This was a major breakthrough for them and led to fantastic outcomes.
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2. Another software startup, smaller than the one above but still recognizable by a good fraction of HNers, was losing potential customers because their pricing tiers were based on # of servers. Because 1) EC2 and Docker were becoming a thing at the time, so pinning the price to "number of servers" resulted in some absurdly high quotes for not-so-large teams, and 2) the legacy/incumbent providers pinned their pricing to data volumes, so the people who wanted to switch found it hard to compare pricing and see that this company's plans were a better value.
We changed the pricing to be based on data volume and designed the tiers to be a bit lower than the big incumbents and to not encourage current customers to downgrade.
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And sure, while this was all going on there were designers and product marketers busying themselves with optimizing the pricing pages for conversions. However, a good outcome for them would be a 5–10% increase in signups, whereas the outcomes from the two examples above were measured in seven-figure increases in ARR and VC rounds.