A simple argument for investing in your pricing(cranberryblog.substack.com) |
A simple argument for investing in your pricing(cranberryblog.substack.com) |
For me, this is a sign of a healthy price setting culture within a company. If there are people who are willing to pay much more than me, I wouldn’t want the products priced at my level. Let these people part with their money first, making me relatively richer than them and enriching the company who can put the money towards creating even better products that I eventually can scoop up on the second hand market for the same price I’ll be able to resell it for. The alternative is to keep the prices down, effectively creating some kind of lottery with regard to who happen to check their e-mail when a new batch is released.
This might have been a bit of a rambling, but in the end, I just want to say that I, as a consumer, wish that more companies would try to maximize their profits when it comes to pricing and that they should go against the sentiment that it’s somehow greedy to do so.
Buying behavior seems to be so emotional and impulse-driven these days.
I'd change that very slightly. It's not their willingness to pay, but their cold, hard cash that signals how much they value the product. Many, many people will say they're willing to pay for a product before you build it, and they really are, but won't actually pay for it when it comes time to sign up because they either no longer have the need, or the product isn't actually a good fit, or they can't afford it, etc. You can't really believe any signal except the money going into your bank.
It means exactly that those people will pay, with nobody forcing them, if you offer the product without further constraints.
It's also an abstract value that can only be measured once the item is sold.
Willingness to pay is an economics term which means basically what you stated in your comment.
Don't do this. Grandfather your old customers. Of course, it depends on the kind of business. But in B2C, customers can be price-sensitize and they don't (rightly so) understand why they should pay more for the same value they receive from a product.
> Now let’s assume we increase average prices by just 10% without losing any customers.
I chuckled.
As well as the technical issues with having to build in a load of complexity to maintain various features on different customer accounts, at some point there will be things that will change but customers will not accept that.
Most of our customer completely understand that they are paying for a service, not a product. Just because their features don't change doesn't mean it is costing us nothing to run the service.
Price gouging is morally dubious just because they are sticky but when you are selling a value-add (we could be saving you X employees per year) then it is reasonable to charge an amount of money as the OP says that customers are not as price-sensitive as you think.
It also introduces a new level of complexity on many levels, e.g. rights and access management, product versioning and maintenance, customer support etc.
It is practiced in industry at Amazon and Microsoft among other places.
Price discrimination comes in three forms and is discussed in any textbook on industrial organization.
There is a lot of good theory AND empirical work for anyone interested in applying these techniques.
In relation to tech (and software in particular), can you point to some resources that would be useful to explore some of these concepts?
In principle, _any_ time that Amazon wants to make a decision about offering an in-house version of some product that is already sold in their stores this is the kind of thing they will do first (again, none of these estimates are public to my knowledge).
There are prominent applications in:
- automobiles (Berry, Levinsohn and Pakes (1995) - the originators of the technique),
- alcohol (Miravete, Seim and Thurk, (2018) - relevant especially to the case of a high-dimensional product space),
- the minivan (Petrin (2003) - relevant to studying a new product),
- breakfast cereal (Nevo (2003) - this is a surprisingly innovative and competitive market category!)
- radio stations (Sweeting (2013) - probably the current state of the art econometrically)
- studying vertically organized markets with unobserved prices (Villas-Boas (2007))
- (There are other applications beyond those listed here - demand estimation is a foundational issue for answering many, many, many economic questions.)
Depending on the specific features of the software demand estimation problem you are thinking about, you may find any of those references helpful.
Two very recent surveys have been published by four of the top people in this area:
1. Gandhi and Nevo: https://www.nber.org/papers/w29257
2. Berry and Haile: http://www.econ.yale.edu/~pah29/Foundations.pdf
Plus there is a now-standard Python implementation of the estimator:
However, if your customers are the product (advertising, affiliate marketing), then you should squeeze your advertisers more, not your customers. So many content creators ruin their hard work by going too hard with monetising their users.
(1) When pricing is hidden, this means in practice you have every sales rep trying to maximize pricing for the individual person. Meaning there are in fact millions of "pricing people" in companies around the world.
(2) When pricing is NOT hidden, pricing is rarely updated, which is a good thing. Ads, comparisons, press releases, etc all may reference pricing. Changing pricing on your existing customers really can cause churn (which for SAAS outweighs the typical margin gain).
(3) The author doesn't mention discounting, which is in fact playing with pricing, and something companies do a lot of.
(4) For transparent pricing, finding the right price doesn't really change that much. So if you only have a few products, investing in a full time person seems like maybe they would be really busy for the first 1-12 months then...do nothing? You really probably need new products coming out regularly to justify someone dedicated to the role.
I tend to discount it as I have never paid for something on spec.