Hah! I laughed at the description text of that graph meme. Interesting to hear what folks not only in the video game industry but the marketing sphere as a whole have to say about this kind of thing...
Great article, Ryan! A lot of great insights. If I may, I’d like to clarify something on forecasting for the readers, as someone who does it for a large publisher. And I make this clarification just so people know it’s not ALL made up numbers in a overly complicated spreadsheet 😁
There are different types of forecasts. Any forecast that happens before there is some kind of sales or engagement data coming in is pure “educated guess” work. It’s a mixture of benchmarking, like Ryan said, and ambition (aka this is what we want or need to sell). I would argue that the only true data point in existence for games that you can produce a reasonably accurate forecast around is pre-order data on a paid game, and if your paid game has any additional monetization component then you’ll only be able to predict the pre-order curve and launch week sales (since most of it will be base game and additional monetization will be minimal at that point). It’s quite hard to predict how a game will monetize above the base game, even if it’s similar to a game you’ve released before or another game on the market. And if you’re trying to forecast a game that is primarily or completely micro-transactions and DLC it’s insanely challenging, but engagement data (beta participants for example) helps a lot.
ALL THAT BEING SAID, if we’re talking about forecasting sales based on pre-order or engagement data like I mentioned above, that part of forecasting is the real deal and it’s what a ton of go-to-market and lifecycle planning is based on. The models are real and they are what you use to align expectations internally, such as with your sales and finance teams, and with partners, like PlayStation, Xbox, Steam, etc. There is also post-launch forecast events, like Black Friday sales and whatnot. Lots of fun 🙂
Hope this adds some more insight to the world of forecasting in video games!
Oh man, glad to hear the techniques I used as a one-person forecasting team for a large organization are industry standard (wait, am I glad about that?).
Any thoughts on how many wildly successful founders are out there that Graham didn’t name? And how many share those qualities he names but whose projects didn’t pop off?
The Graham blog post is crazy to me because everyone he named had already succeeded by Y Combinator’s standards, but later went on to exceed at levels literally unimaginable to pre-internet generations. Whatever Y Combinator thought AirBnB would be worth, I guarantee they never thought it be worth close to $100 billion.
I don’t know his writing process on that piece, but I have to imagine that on some level the 8 or 9 dudes he named were top of mind for him even before he put together that list of 5 qualities. Maybe he thought of those guys first and reverse engineered the list from them. The “Naughtiness” example in particular seems like it wouldn’t even make the list if it weren’t for Sam Altman. But that’s just speculation.
So I’m sure there are plenty of people with those qualities who failed, or who didn’t make the list. But the list probably emerged from the people listed, not the other way around. Just my guess. Would love to ask Paul.
Hah! I laughed at the description text of that graph meme. Interesting to hear what folks not only in the video game industry but the marketing sphere as a whole have to say about this kind of thing...
Great article as always!
Great article, Ryan! A lot of great insights. If I may, I’d like to clarify something on forecasting for the readers, as someone who does it for a large publisher. And I make this clarification just so people know it’s not ALL made up numbers in a overly complicated spreadsheet 😁
There are different types of forecasts. Any forecast that happens before there is some kind of sales or engagement data coming in is pure “educated guess” work. It’s a mixture of benchmarking, like Ryan said, and ambition (aka this is what we want or need to sell). I would argue that the only true data point in existence for games that you can produce a reasonably accurate forecast around is pre-order data on a paid game, and if your paid game has any additional monetization component then you’ll only be able to predict the pre-order curve and launch week sales (since most of it will be base game and additional monetization will be minimal at that point). It’s quite hard to predict how a game will monetize above the base game, even if it’s similar to a game you’ve released before or another game on the market. And if you’re trying to forecast a game that is primarily or completely micro-transactions and DLC it’s insanely challenging, but engagement data (beta participants for example) helps a lot.
ALL THAT BEING SAID, if we’re talking about forecasting sales based on pre-order or engagement data like I mentioned above, that part of forecasting is the real deal and it’s what a ton of go-to-market and lifecycle planning is based on. The models are real and they are what you use to align expectations internally, such as with your sales and finance teams, and with partners, like PlayStation, Xbox, Steam, etc. There is also post-launch forecast events, like Black Friday sales and whatnot. Lots of fun 🙂
Hope this adds some more insight to the world of forecasting in video games!
Action produces information. This idea floats on top of many pg essays, the tweet below is a good example.
https://x.com/andrewarruda/status/1798798393999020246
Oh man, glad to hear the techniques I used as a one-person forecasting team for a large organization are industry standard (wait, am I glad about that?).
Any thoughts on how many wildly successful founders are out there that Graham didn’t name? And how many share those qualities he names but whose projects didn’t pop off?
This was illuminating, thanks for writing!
The Graham blog post is crazy to me because everyone he named had already succeeded by Y Combinator’s standards, but later went on to exceed at levels literally unimaginable to pre-internet generations. Whatever Y Combinator thought AirBnB would be worth, I guarantee they never thought it be worth close to $100 billion.
I don’t know his writing process on that piece, but I have to imagine that on some level the 8 or 9 dudes he named were top of mind for him even before he put together that list of 5 qualities. Maybe he thought of those guys first and reverse engineered the list from them. The “Naughtiness” example in particular seems like it wouldn’t even make the list if it weren’t for Sam Altman. But that’s just speculation.
So I’m sure there are plenty of people with those qualities who failed, or who didn’t make the list. But the list probably emerged from the people listed, not the other way around. Just my guess. Would love to ask Paul.
Great read!