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

## A Quick Refresher

Pricing is tough to get right. Ideally, we’d like to select a given price such that revenue is maximized (consider revenue as profit), holding all else constant.

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 max 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 $$P$$ 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. But what if there was a way to charge the reader who valued the book at$30 exactly $30 and the reader who value the book at$18 exactly $18? While we could raise the price of the book 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 accrued utility outweighs the initial cost.

### Standard Utility Curve (Reading a Book)

It's import 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 if doing so is better then 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 sort of boring. This is why book rentals (libraries) and book reselling are so popular. Why pay a fixed price for what is usually a single-use item? This rings 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 off 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:

PvP environments [in games] necessitate strategies that evolve in an evolutionary process. This means equilibrium in PvP environments is constantly reshuffled with each balance change; 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 with which it can correlate marginal cost (MC) to marginal benefit (MB). In the above examples, price was fixed. This made sense given that the utility curves flattened out. But the more the curve refuses to flatten, the most discorrelated MC to MB becomes as Time continues.

This 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 to a closer to their MB curves they were previously able to do so.

### Utility/Price Curve: MTX & F2P Games

Software as a service (Saas) is able to generate similar growing utility, but they only charged a fixed price in recurring intervals. Again, this suggests that subscriptions might make sense for games. Games, however, generate even more heterogeneous LTU (lifetime utility) then do many SaaS products. This suggests subscriptions are better than fixed prices in correlating MB and MC, but weaker then MTX systems. 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 as they are added. Look familiar? This is exactly how observe 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. Clearly, some users value say, Zoom, more than others. As Zoom usage increases, LTU does as well, but 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 gets in the cosmetics business - backgrounds were an amazing opportunity that never got capitalized on.

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

The dramatically different value propositions of standard goods and games necessitate different monetization schemes. This makes applying the monetization of tech companies less applicable to gaming, but perhaps SaaS as a service firms have something to learn from games.

Gaming Companies Aren’t Tech Companies!