In the opening of the interview, Speaker A asks Speaker B to name the company whose pricing and packaging they most admire. Speaker B, who works full‑time in pricing, responds that they are very detail‑oriented and "nitpicky" about pricing, implying a deep expertise that will shape the forthcoming discussion.
What's the company that comes to mind for you whose pricing and packaging you most admire?
Yeah, well, I spend all my time in pricing actually, so I'm kind of nitpicky.
I figured you would have a very high point. I was curious to see who would rise to this.
No, it's true. Honestly, I've been asked that question before and I always struggle to find someone who I like everything about their pricing, but I will call out one company that I really like the way that they did their metric. Their price metric. Algolia is a company that provides search functionality that you can plug into websites or internal tools and so forth. It helps you search for things and find things. And it's very smart. It'll actually, it'll kind of read between the lines of what you're searching for and find other things that you might be interested in. So there's a lot of great stuff there. It's an interesting company. People would be, probably get a lot of from looking up, but they changed their pricing a few years ago. They clearly wanted to go to a usage-based model. Which a lot of companies were doing at the time, and of course still are today. And I guess the obvious metric that you would think of for them if they wanted to price in a usage-based way is number of searches, right? Because it's a search-based product. When you search for something, you get the value out of it, at least presumably that makes sense. However, if you think about searches, it falls into a lot of the pitfalls that a lot of usage-based metrics fall into, right? Which is one, it's very difficult for you to be able to predict how many searches that you have. And it's actually not as value-aligned as you might think, because if you go on Google these days, right, and let's say you wanted to search for dog, right? You wanted to search for pictures of dogs or something. You type D and that's a search, and then you type O and that's another search, and then you type G and that's another search. So you've actually done 3 searches within that piece. So were all those 3 searches valuable to you, right? Was it, do you know like how many long the text string on average is gonna be of the things that you're gonna search for? Probably not. And those are both frictionful things when you're a customer trying to buy. Think, A, I don't know what my searches are gonna look like, and B, they're probably not all valuable, so I don't want to pay for them. And there's also issues with searching in that it's not a guarantee that the amount of searches that you do is gonna go up over time. You know, you'd usually want that within a price metric. You want it to increase. So that you can charge the customer more year over year as they get more value from it. But if your search algorithm gets better over time, then people might need fewer searches to get what they want to, right? Because most of the times when you're searching, you don't just do one search, you search for something, you don't quite find what you're looking for, you do something else and so on and so forth. Algolia came up with this really cool metric, which I think they call search requests. And the idea is it's not every single search is a search, it's every search within a certain sort of period of time. So that they're obviously connected counts as one search. It's like having a search session. So they kind of, they massage out all of that non-value-based stuff and just make it so that it just is the search. And that way, you know, that probably will go over time because it is just thinking about just those times that you're searching for something, not the sort of the number of searches that ultimately get you to what you want. So I thought that was a really clever way of getting to getting the thing that you want from your metric as opposed to just taking the sort of the strict technical definition and getting into a bad place with your pricing strategy.
