A talk I gave on May 13, 2009. Talks about why virtual economies are different from real economies, and then talks a little about how to deal with virtual economies.
Twofish products are shown in some screenshots, but it's not a Twofish-centric talk.
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Virtual Worlds and Real Metrics:
1.
2. Virtual Worlds and Real Metrics:
Tangible Statistics about Imaginary
Goods
3. In recent years, virtual currencies, virtual economies, and
virtual goods have become a common part of the internet
landscape. However, while there is now widespread consensus
that virtual economies are an increasingly valid and fruitful
monetization strategy for internet applications, there are very
few management tools for virtual economies, and, aside from
a few obvious bromides (quot;Avoid hyperinflation!quot;), no agreed-
upon consensus as to the key metrics to use in doing so.
This talk will begin with some history (covering some early
ideas in measuring virtual economies) and then explore some
of the metrics that make sense for a virtual economy. We will
cover both how to increase profit in a virtual world and how to
detect interesting user behaviors and profiles through
economic measures. Throughout the talk, screenshots of
Twofish's analytics platform will be used to illustrate key
points.
4.
5. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
6. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
8. Bill leads the Twofish Elements product roadmap, platform development and
engineering organizations. Bill's love of economics started as an undergrad, where he
taught econometrics and was the recipient of a URECA grant in economic modeling
and continued throughout his grad school career in mathematics.
An active and vocal participant in the software development community, Bill has
published 2 books and more than 20 journal articles, and is a long-time board member
of SDForum. Bill has held various chief architect and executive engineering roles at
companies including Engage (acquired by Spark Networks), Echopass, and Hipbone
(acquired by Kana).
9.
10. This is not a Twofish Product Talk
• More about illustrating the problems than
talking about the (Twofish) solution
• Goal is to take a step back and talk bigger
picture / deeper than is usually the case
• Goal is also to be somewhat provocative
– “I would rather be vaguely correct than precisely
wrong” – John Maynard Keynes
11. My Employer is Not To Blame
• Twofish is a great company
– We make software to support virtual economies
(SaaS backend play)
– I’m the CTO
• You ain’t the customer, I ain’t here to sell you
nothing, and this is mostly my opinion
– “And besides, the wench is dead.” – Christopher
Marlowe.
12. Ask Questions
• This is going to be an idiosyncratic slice of
– The last 30 years in gaming
– Economic theory
– Software design
– Other stuff
• “The footnotes are not entirely without merit”
– G. Santayana
13. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
16. Habitat Really Did Pioneer Things
• Primitive Graphics
• But an economy
– You could buy items
• And people were people
– Communication between people mattered
– Communities formed
– Ethical debates over killing other people
– Accumulating items for status
– ….
17. … Avatars are hatched with 2000 Tokens in their bank account, and each day that they
login the receive another 100T. Avatars may acquire additional funds by engaging in
business, winning contests, finding buried treasure, and so on. They can spend their
Tokens on, among other things, various items that are for sale in vending machines
called Vendroids.
There are also Pawn Machines, which will buy objects back (at a discount, of course).
In order to make this automated economy a little more interesting, each Vendroid had
its own prices for the items in it. This was so that we could have local price variation
(i.e., a widget would cost a little less if you bought it at Jack's Place instead of The
Emporium). It turned out that in two Vendroids across town from each other were two
items for sale whose prices we had inadvertently set lower than what a Pawn Machine
would buy them back for: Dolls (for sale at 75T, hock for 100T) and Crystal Balls (for
sale at 18,000T, hock at 30,000T!). Naturally, a couple of people discovered this. One
night they took all their money, walked to the Doll Vendroid, bought as many Dolls as
they could, then took them across town and pawned them. By shuttling back and forth
between the Doll Vendroid and the Pawn Shop for hours, they amassed sufficient
funds to buy a Crystal Ball , whereupon they continued the process with Crystal Balls
and a couple orders of magnitude higher cash flow. The final result was at least three
Avatars with hundreds of thousands of Tokens each. We only discovered this the next
morning when our daily database status report said that the money supply had
quintupled overnight.
18. In the years since then …
• Vast expansion in graphical capability
• Vast reduction in barriers to building
• Major success stories:
– World of Warcraft
– Linden Labs
– Habbo Hotel
• Better gameplay, more sophisticated digital asset
systems, the emergence of gold farming, the
emergence of secondary market systems (player to
player commerce)
• But not a lot of change in the fundamentals of things
19. Key Terms
• Virtual Currency
• Digital Good
• Item
• Primary Market
• Secondary Market
20. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
21. Very Seductive Analogy
• At the “artifact level”, Virtual Economies and
“Real Economies” share some common
elements
– Currency – medium of exchange, unit of
account, store of value
• Real and virtual currencies are all of these
– Items and instances that get bought and sold
• Whether the asset is purely digital or purely
physical, there are still things being bought and sold.
• At a deeper level, the analogy is misleading
22. Difference: Circulation
• Real world: Money
doesn’t escape; it
circulates
• Virtual world: “Cash
in”, “cash out”, and the
idea of “sources” and
“sinks”
23. Virtual World Economic Circulation
Cash Cash
In Out
Vectors Transactions Vectors
(some player to player, mostly
player to world)
Other
Sinks
(simple case)
24. Virtual World Economic Circulation
Cash Cash
In Out
Vectors Transactions Vectors
(some player to player, mostly
player to world)
Other
Sinks
Gray Secondary Currency
Market Exchanges Exchanges
25.
26.
27. Difference: Types of Currencies
• Real world: currencies mostly
interchangeable, via foreign exchange
• Virtual world: “loyalty currencies”, “earned
currencies”, “reward currencies” and “paid
currencies”
• Foreign Exchange behaves very very
differently
28.
29. Difference: Control of Purchase Points
and Distribution
• Hard for people to trade virtual currencies and
items outside of virtual world
– “Gray markets” do exist, but lots of friction
• Means that you can actually have different
foreign exchange rates
– Based on bulk volumes
– Based on user demographics
30. Difference: Tangibility
• In real economies, most goods are subject to
laws of physics
– They’re in a place, cannot be transported easily.
• Up until very recently, most money was
subject to the laws of physics
• In virtual economies ….
31. Difference: Pricing Discrimination
• Real world:
– Location-based differentiation, coupon-based
differentiation, …
– But the cost of money is pretty similar (except rich
people can borrow at better rates)
• Virtual world:
– Arbitary criteria on all pricing
32. Difference: Scarcity
Scarcity (also called paucity) is the problem of
infinite human needs and wants, in a world of
finite resources. Society has insufficient
productive resources to fulfill those wants and
needs. Alternatively, scarcity implies that not
all of society's goals can be pursued at the
same time; trade-offs are made of one good
against others. In an influential 1932
essay, Lionel Robbins defined economics as
quot;the science which studies human behaviour
as a relationship between ends and scarce
means which have alternative uses.quot;
33. Difference: Opportunity Cost
Opportunity cost or economic opportunity
loss is the value of the next best alternative
foregone as the result of making a decision.[1]
Opportunity cost analysis is an important part
of a company's decision-making processes but
is not treated as an actual cost in any financial
statement.[2] The next best thing that a person
can engage in is referred to as the opportunity
cost of doing the best thing and ignoring the
next best thing to be done.
34. Difference: Comparative Advantage
In economics, comparative advantage refers to
the ability of a person or a country to produce
a particular good at a lower marginal cost and
opportunity cost than another person or
country. It is the ability to produce a product
most efficiently given all the other products
that could be produced.[1][2] It can be
contrasted with absolute advantage which
refers to the ability of a person or a country to
produce a particular good at a lower absolute
cost than another.
35. Famous Economists of the 1800’s
• Adam Smith: invisible hand, analogy of the pin
factory
• David Ricardo: comparative advantage, the
evolution of trading patterns and the
international economic order
• Karl Marx: the workers control the means of
production!
36. Big Important Question
• Virtual and Real Economies have the same
artifacts
– Means that the measurements you can make for
real economies can be made for virtual economies
– And the people are the same
• But Virtual and Real Economies have very
different fundamental underlying structures
• So what are the right metrics for Virtual
Economies?
37.
38.
39.
40.
41.
42. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
43. The Fundamental Question
• How do I measure the health of an economy?
• One answer is “an economy is healthy if people
are buying stuff”
• If the world is closed and all money is recycled,
then you can talk about “how many times a dollar
is used in one year (on average)”
– Note this assumes transactions are mostly
commensurable and involve physical money
• How do you calculate that?
44.
45. I have never met with any attempt to
determine in any country the average rapidity
of circulation, nor have I been able to think of
any means whatever of approaching the
investigation of the question, except in the
inverse way. If we knew the amount of
exchanges effected and the quantity of
currency used, we might get by division the
average numbers of times the currency is
turned over; but the data, as already
stated, are quite wanting.
Jevons, 1875
46.
47. Measuring Velocity of Money
• Tons of effort expended on this
• And lots and lots of recent newspaper articles
– The velocity of money slowed late last year
– The “multiplier” effect is a related statistic.
• Take GDP
• Divide by Money Supply
48.
49. Key Point
• This is one of the most analyzed macro-
economic statistics out there
• The original idea: try to figure out if people
are buying stuff, was good
• The execution was definitely colored by the
environment:
– How do you do that in 1875?
– Even now, how do you do that?
50. Outline
• Who Am I
• Virtual Worlds: A Primer
• Virtual Economies and Real Economies
• Making it Concrete: The Velocity of Money
• Moore’s Law Kicks Ass
51. Reminder: I’m not Unbiased
• I work for a company that does this for a living
55. Twofish Architecture
R900 Twofish Elements
OLTP
ETL defined
using Kettle
R900 Mondrian Highly Customized
OLAP (open source OLAP) Version of OpenI
56. The Point
• Perfect Data
– Twofish Elements is, essentially, a highly scalable accounting
system that tracks millions of accounts simultaneously
– We also store user demographic information and have a virtual
title system (“items”)
• WOW Hardware
– 128G of Ram with 4 cores is now around $10K
• The BI Revolution
– Pentaho is a couple million lines of code we didn’t have to write
• (and, of course, some clever people writing some very
clever code)
57. Velocity of Money Revisited
• “Single Account Coin Velocity”
– If I model a user’s account as a FIFO queue, how long
does it take before they start to spend money they
deposit today?
• I can compute this for each and every user in my
world
– For each and every currency they have
• And then I can aggregate by demographics (or
across the world)?
– What’s the velocity of money for women, aged 30 to
39, in California?
58. Sam Walton’s Dream
• Item Sales, broken down by
– User demographic
– Time
– Type of Item
– …..
59. Ben Bernanke’s Dream
• Accurate macroeconomic
statistics
(and then we can drill down by type of sink/source etcetera)
60.
61.
62.
63. Dave McClure’s Dream
• Automatically run tests;
adjust prices and exchange
rates to maximize revenue
????
(not available in this quarter)