In-Round Progression is the Biggest Game Design Innovation in a Decade

Battle Royale and Roguelike are remaking game progression before our eyes. Popularized in earnest during the rise (and eventual pruning) of the MOBA genre, in-round progression mandates players accrue vertical power in the context of a single round.

MOBA sessions start with players farming in-round currency to spend on items that persist until the round or particular game is over. In addition to in-round currency, players earn XP that levels up characters for the round duration. Many teams secure victory by out-farming currency and XP relative to the opposing team; eSports commentators are fond of displaying progression charts during casts. A single XP chart becomes the scoreboard of the game and a big predictor of victory.

In-round progression completely alters the salary profile game designers pay players. If we think of rewarding player action with progression as a wage rate, in-round progression radically alters the incentives. Instead of optimizing for the long-run, in-round progression presents a 30-60min time horizon to players.

Continue reading “In-Round Progression is the Biggest Game Design Innovation in a Decade”

Why I’m a Supply-Side Game Economist

Robert Mundell often remarked getting to tier 100 in the Battle Pass is harder than getting a Nobel Prize

Game monetization discussions tend to focus on what to monetize broadly (gameplay or cosmetics) as well as how to price it. As someone might imagine, these are crucial and foundational discussions to have. So naturally, therefore, it makes sense to invest a lot of human capital into optimizing them. Increasingly, however, I’ve become convinced that just making lots of stuff trumps all other optimizations. Instead of being an afterthought, supply-side considerations deserve to be front and center.

Continue reading “Why I’m a Supply-Side Game Economist”

“Community” Leads Us Astray

A few months back, a member of Biden’s campaign team appeared on CNN. The team member describes how the campaign managed to stay politically center: staying off social media. I tweeted at the time this was great advice for game devs.

The vocal members of any community tend to dominate the feedback. And as we know, this minority is not representative of the whole. Most anyone I’ve talked to will freely admit this, but we commonly ignore it when referring to the “community” of a game. For example, job postings for Community Managers emphasize social media management. 

Continue reading ““Community” Leads Us Astray”

The Creator Economy is for Anyone but not Everyone

Ladies and gents. Israel Kirzner, the Avatar.

UGC platforms have hailed the rise of the Creator Economy™. Roblox, TikTok, and Youtube have democratized the creation of content, abstracting the costs of getting content to market. But we’ve assumed UGC cuts out content gatekeepers in favor of entrepreneurs. Everyone gets a warm glow when “the little guy wins”. And by all means, this appears to be true! Creators can single handily craft and distribute TikTok videos in seconds, not days or months. The barriers to Roblox creation are higher, but it’s a far cry from the rigamarole of traditional game publishing. The effects of UGC are profound: despite easing requirements with Early Access, Steam hosts 50,000 games to Roblox’s 40 million. It’s such a gap I made this handy chart to underscore the difference:

Continue reading “The Creator Economy is for Anyone but not Everyone”

Is There An Actual Case for Cyberpunk’s Delay?

Cyperpunk 2077 launched and it turns out the PS4 and Xbox One versions of the game were riddled with bugs. This has lead to an avalanche of omniscient pundits declaring “I told ya so!”. My personally favorite roast in this Miyamoto meme.

A delayed game is eventually good, but a rushed game is forever bad."  Shigeru Miyamoto - iFunny :) | Words of wisdom, Super funny memes, Funny  memes
Was Miyamoto around for the Wii U though?

Rushing development feeds into narratives around greedy firms. “If only they didn’t want so much money!” Much of this banter is comprised of cheap shots devoid of making real claims about what CDPR should have done. Should the game have been delayed an additional 4 months? 6 months? And if so, why? If the board really didn’t understand the scope of the bugs then the question turns to the organizational design CDPR. What organizational breakdowns led the lack of information the board had about the bugs in game. Were QA leaders not empowered to speak up or not trusted?

These are much tougher questions to answer. After all, as Pixar is fond of saying, “[Games] don’t get finished, they just get released”. The key question is when to release. There will always be bugs and there will always be new features to add. Ultimately, release timing is a cost/benefit decision. Relative to the additional development cost what increase in sales would we expect from a delay? Do we have ever higher margins from a 4 or 6 month delay? To be clear, Cyberpunk is already outselling all other CDPR games, hardley “one of the most visible disasters in the history of video games“. What further increase would analysts expect with what additional delay?

Why Do Only Product Managers Write About Games?

I recently came across this Tweet:

The article’s writer, Ran Mo, is a Lead Product Manager at EA according to his Linkedin while the quote Tweeter is a fellow product manager. Dive a bit deeper and the retweets are all from fellow VCs or product people (guess there’s something to this).

This isn’t exactly uncommon. The Deconstructor of Fun podcast is hosted by three Product Managers and guests frequently come from a similar ilk.  A scroll through the last 20 DoF blog boosts a breakdown dominated by PMs.

DoF Posts by Job Discipline

Thanks for making it exceeding difficult to order by count Google Sheets!

Games are at the cleavage of art and science, so why are PMs the only ones with something to say about it? The alternative voices we do have, Eric Seufert (UA), Alexandre Macmillan (Analytics), and Javier Barnes (Design), only take a couple of sentences of digestion to realize the dramatically different way they frame and discuss problems. Their pieces tend to have more backbone or a strong theory that underlies an empirical observation. I’m a fan of this approach.

PMs are driven by their social caste, mainly moving up it. Networking is crucial to this, an insight that seems to go over the head of analysts and designers (at our own peril). The PM hierarchy is reflected in the “up or out mentality” re-enforced at tech and gaming firms. A scroll through PM Linkedin and you’ll see the following ladder:

But is a manager or regional director the higher title?

None of these motivations discredit, in any way, the strength of the ideas expressed by PMs. Or the fact they actually take the time to express them. But it does help explain why they can feel hollow at times, trying to fit a socio-political mold rather than a genuine expression. This is reflected in how many game PMs will depart for higher paying tech PM jobs in the Valley or to fellow gaming firms for title bumps. And there’s nothing necessarily wrong with that.

 If I had a plea, it would be for all game disciplines to write vigorously. Write everything you know to be true and let’s hash it out. The game craft is too important to be dominated by one discipline. We should all be thinking hard about these problems.

Game Companies Are Not Tech Companies Part IV: MB = MC

Part I
Part II
Part III

“It’s a me-a!” Mr.Utility himself. This was in his will actually.

A Quick Refresher

Pricing is tough to get right. Ideally, we’d like to select a price that maximizes profit, holding all else constant.

Slopes not drawn to scale
In the above example, we consider a single price \( P \) but we can expand this to consider the set of prices or price set that define a game or service \(P_s:{\{P_1, P_2…P_x}\}\).Again, we want to pick the set of prices that maximize revenue.

Many goods or services operate under a single fixed price. For instance, a book might cost $18—everyone who values the book $18 and above purchases it. \( revenue = n * P \) where \(n\) is the number of readers who value it $18 and above and PP is price. Simple enough, right?

Let’s add consumer surplus to the story. In the example below, this is the shaded yellow area. Some readers value the book at $30 and thus are the most profitable in the transaction ($30 – $18 = $12 economic profit). The other readers made out, but perhaps not as well.

Consumer Surplus | Intelligent Economist

Imagine, however, that we could charge two different prices to two different segments of readers. Say one reader valued the book at $18 and another who valued the book at $30. The trick is to ensure that the good is non-tradeable; otherwise, the customer who faces a lower price could resell to the higher-priced customer and pocket the difference.

While we could raise the book’s price to $30, we’d lose out on the $18 reader. The problem of price discrimination, the one described above, is fundamental to understanding entertainment business models.

Our Case

The consumer surplus model struggles to capture time. After paying a fixed price for the book, the reader chooses to consume it (is anyone surprised?). The reader continues to accrue utility from this consumption – the enjoyment of reading the book outweighs other activities. At some point (but not always), the accumulated utility outweighs the initial cost.

Standard Utility Curve (Reading a Book)

Let’s pretend utility accrues linearly.

It’s important to note: the reader is not “in the hole” when we see red in the above graph. The book is a sunk cost; the reader should only consume it better when it’s better than engaging in other activities. But if we extend this graph to include more Time, the curve kinks immensely.

Utility Curves: Books

There are incredibly steep diminishing returns to reading a book a second time. It’s boring. Deep diminishing returns explain why book rentals (libraries) and book reselling are so popular. Why pay a fixed price for what is usually a single-use item? Steep diminishing returns ring true for movies as well. Of all films you’ve watched, what percent have you seen a second or third time? 1%? 5%? Subscriptions and rentals make sense for this form of entertainment. But what if, instead of flattening, the utility curve grew? Enter gaming.

Utility Curves: Games & Books/Movies

Games have a unique resistance to diminishing returns. As described in Part III:

The genius of PvP (Player v Player) environments is how they necessitate the emergence of a meta-game. PvP environments resemble game theory models where it has been shown strategies evolve in an evolutionary process. In mathematics, Player vs. Environment (PvE) resembles optimization where strategies are static – one and done. Each balance change reshuffles Equilibrium in PvP environments; the search for dominant strategies in an ever-shifting equilibrium is the game itself.

The strategic evolutionary process is a near limitless piece of content to consume.

MB = MC

The efficiency of any monetization or pricing system is the degree to which it can correlate marginal cost (MC) to marginal benefit (MB). In the above examples, we fixed the price. Fixing the price makes sense, given that the utility curves flattened out. But the more the curve refuses to flatten, the most decorrelated MC to MB becomes as Time continues.

The above gets us to the emergence of DLC and MTX. Players were playing PvP titles for hundreds, if not thousands of hours. MC failed to catch up. DLC map packs like those in Call of Duty and Battlefield helped MC catch up (and grow MB!) in fixed intervals, but the correlation was still weak as Time persisted.

MTX solved for the explosion in the marginal benefit multiplayer games were providing. Unlimited or greatly exaggerated spend caps allowed players to spend closer to their MB curves than they were previously able to do so.

Utility/Price Curve: MTX & F2P Games

Price = Accrued Revenue

Software as a service (Saas) can generate similar growing utility, but they only charged a fixed price in recurring intervals. Again, this suggests that subscriptions might make sense for games. Subscriptions are better than fixed prices in correlating MB and MC, given that SaaS generates recurring homogenous LTU returns. Games, however, generate heterogeneous LTU (lifetime utility) than do many SaaS products.

We can model the heterogeneity as such:

As we consider the total Lifetime Utility generated by a standard good or game, we add up an individual’s LTU from lowest to highest LTU. If everyone valued a standard good the same, LTU would be linear. If a few players valued a game at a relativity extreme LTU, you would see a bowed curve – the high LTUs skyrocket total LTU upon addition. Look familiar? A bowed LTU curve correlates to observed LTVs in F2P games.

Does Tech leave too much LTU on the Table?

But that’s not to say all non-video games have a linear Total LTU curve. Some users value, say, Zoom more than others. As Zoom usage increases, LTU does as well, but the price does not. Zoom, therefore, fails to capture a great deal of LTU from high usage customers. MTX theory could offer a hand.

Zoom does offer tiered pricing for organizations with a higher price charged for additional features, but this doesn’t capture the high LTU users within an organization. Perhaps Zoom should get in the cosmetics business – backgrounds were a fantastic opportunity that never capitalized on.

Even at the organizational offering level, Zoom could create an additional tier that offered other features to high usage customers in the tier. Multi-track cloud recording, for instance, generates incredible value for Podcasters but costs nothing further.

The dramatically different value propositions of standard goods and games necessitate other monetization schemes. Different content economics make applying the monetization of tech companies less applicable to gaming. Instead, SaaS firms have something to learn from games.

Gaming Companies Are Not Tech Companies!

Game Companies Are Not Tech Companies Part III: The Content Problem

Part I
Part II

The only Content Problem worth saving. Do it, Reed!

So maybe game companies aren’t tech companies. As much as game companies seem to borrow from tech firms, tech firms run a bigger deficit in borrowing from games. If Netflix, a subscription service with over 10,000 movies and TV shows, has its biggest competitor in a single game, Fortnite, then perhaps there’s more for tech to learn from games. And how games deal with The Content Problem is its defining characteristic. Of all forms of entertainment, games present the most compelling answer to the problem.

The Content Problem

The fundamental axiom of economics is unlimited needs and wants and only limited means to fulfill them. The parallel for entertainment might consider that core content demand nearly always outstrips supply. For example, large swaths of Game of Thrones and Harry Potter fans are underserved by a couple of books, movies, and TV seasons. Executives try to fill the void with licensing: Harry Potter backpacks, Game of Thrones beer, etc. But filling the core content demands are impossible: it takes far more than 1 hour to produce 1 hour of Game of Thrones, while the same is not valid for games.

Consider the following:

The content consumed in a game like Overwatch or Clash Royale is the pursuit of strategy equilibrium and/or mastery of mechanics. A new unit in Clash Royale changes how players organize their decks, even if they don’t use the unit directly (they must counter it). The new units provide hundreds of new hours of content to consume relative to the near 1 man-week of labor to produce the new unit. Therefore, the marginal content output of a given member of the 16 people (!) Clash Royale team is astronomical.

Furthermore:

The genius of PvP (Player v Player) environments is how they necessitate the emergence of a meta-game. PvP environments resemble game theory models where it has been shown strategies evolve in an evolutionary process. In mathematics, Player vs. Environment (PvE) resembles optimization where strategies are static – one and done. Each balance change reshuffles Equilibrium in PvP environments; the search for dominant strategies in an ever-shifting equilibrium is the game itself.

The marginal product of labor for a given game developer completely outclasses a given producer on a movie or TV show by virtue of the medium, not the individual. Unlike games where assets are infinitely replicable, films and TV face fixed constraints: Emilia Clarke or David Benioff can only be in a single place at a given time. They must also eat, sleep, socialize (sigh). Meanwhile, Captain Price faces no such constraints. There’s no more Game of Thrones to consume after the last episode cuts to black while there’s always another hour of Fortnite to play. How can Netflix and others adapt to the reality of these mediums?

The most straightforward strategy is a content arms race. Netflix continues to spend over $17B  a year on original content while scooping up oodles of back catalog content. Of course, viewers must be interested in this content to be “effective,” and the recommendation engine plays a vital role in this. But the last episode of Stranger Things shows that the recommendation engine cannot fill the void while operating on the same indifference curve. The “more bodies” strategy to solving the content problem is expensive to execute and, as we’ll see in part 4, struggles to achieve Marginal Cost = Marginal Benefit.

Reality TV is a response: it needs fewer writers, editors, and CG to produce a given hour of content. Shows like The Amazing Race, Big Brother, and Survivor can do 20+ seasons of 22+ episodes, while Game of Thrones struggles with seven seasons of 10 episodes despite having so many more crew members. Netflix’s speed of investment here is breathtaking. But the addressable audience is more limited in scope than traditional dramas. Netflix needs a bolder evolution to combat games: TV-as-a-service.

The forgotten genre of soap opera TV provides a near-perfect blueprint. For those unfamiliar, soap operas are near year-round weekly serialized television shows. The unrelenting pace has resulted in popular series like General Hospital having 14,000+ episodes over 57 years. Netflix needs to invest in moving performances to a similar format: year-round production with weekly releases heavily. There’s always another piece of content to consume right around the corner while the back-catalog for a given show continually expands for newcomers. In many ways, this mirrors match-3 level production. The number one reason why players churn from match-3 is a lack of new levels, and a glance at community pages confirms this.

Sugar Rush or something, right?

King mitigates content churn using an increasing difficulty curve such that it takes players longer to reach content exhaustion as they progress through levels. Another strategy is also possible, however: branching narratives. Reality TV faces no such option.

Increasingly, Hollywood is shooting movies back-to-back. It’s cheaper to continue production rather than stop and go. Why not do something similar to produce more content? In this case, shoot multiple perspectives in a given series simultaneously. Lord of the Rings production operated similarly with two production crews but with a singular end product. Game of Thrones also operated with two film crews, but the end product was a single episode. Why not dedicate an hour to each perspective rather than splice the two in a single episode? A multi-perspective production multiplies a 10 episode season to 30 while holding down cost. Netflix can’t solve The Content Problem, but it can mitigate it.

Interestingly, Youtube has solved most of this problem via a two-sided marketplace. The smattering of volume helps the supply-side problem even if a particular creator has a finite number of videos (remember, you can still play a given game for an unlimited amount of time without “running out” of content). Youtube has encouraged users to subscribe to many different creators, accounting for regular release cadence.

Diminishing returns for linear content are incredibly steep; few users will watch a film or movie more than once. Increasing and prolonging the LTV of a viewer is most elastic with more content: a costly proposition. To compete with games, TV, and movies need far more supplies. If technology and business models can change innovative products rather than be a vehicle for them, now has never been a better time to explore changes in storytelling.

Part IV