Transcript Lecture 10 Slides
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Lecture 10: Pricing Information Goods AEM 4160: Strategic Pricing Prof. Jura Liaukonyte 2
Lecture Plan:
HW3 Pricing Information Goods Network Externalities Information Laws Long Tail Required reading for next class: HBS case “Merck: Pricing Gardasil”
Laws of the Information Age
Moore ’ s Law Metcalfe ’ s Law Power Law
1. Moore
’
s Law
In 1965 Gordon Moore observed an exponential growth in the number of transistors per integrated circuit and predicted that this trend would continue What it means to us
today—computing power doubles
about every 18 to 24 months It is also common to cite Moore's Law to refer to the rapidly continuing advance in computing power per unit cost, because increase in transistor count is also a rough measure of computer processing power
1. Moore
’
s Law
Information Capacity Constraints (or lack thereof)
2015: 15 GB free space Future: trend towards unlimited space
(Remember
“
Your mailbox is full
”
? What was
that
about?)
2. Metcalfe's Law:
Metcalfe's Law: attributed to Robert Metcalfe, originator of Ethernet and founder of 3COM: The value of a network is proportional to the square of the number of nodes; So, as a network grows, the value of being connected to it grows exponentially, while the cost per user remains the same or even reduces.
2. Metcalfe
’
s Law
400 350 300 250 200 150 100 50 0 1 2 3 4 5 6 7 8 9 10 11 12
Size of network
13 14 15 16 17 18 19 20 Individual network value Community network value
The Network Effect
The usefulness of information products is often dependent on the number of other users of that technology. For example, e-mail is quite useless if there are only a few others that use e-mail. 10
2. Metcalfe
’
s Law
According to Metcalfe technology (
n
’ s Law, if there are technology, then the usefulness of that technology is proportional to the number of other users of that -1 in this case). The total value of the network of the technology is therefore proportional to the usefulness to all users, which is:
n
users of a
n
(
n
-1) =
n
2 –
n
.
11
2. Metcalfe
’
s Law
If
n n
is large, as it will be for most information products, then will be small relative to
n
2 and Metcalfe ’ s Law becomes:
The total value of the network of a technology is proportional to
n
2 12
2. Metcalfe
’
s Law
The more users of a technology there are, the more useful it becomes.
Examples: Facebook, E-mail MS Windows/MS Office 13
2. Metcalfe
’
s Law: Critique
Facebook’s IPO and valuation of a lot of tech companies is rationalized based on some variant of Metcalfe’s law of network effects However recent research suggests that it produces over-valuation The real value is closer to Zipf’s law: N*log N linguist George Zipf: in any system of resources, there exists declining value for each subsequent item.
14
2. Metcalfe’s Law Implications
INCREASE SWITCHING COSTS!
Investing to build an installed base through promotions and by offering up-front discounts. Designing the products and pricing to get customers to invest in technology, thereby raising their own switching costs. Maximizing the value of installed base by selling customers complementary products and by selling access to installed base.
2. Metcalfe’s Law Implications
“
Positive feedback makes the strong grow stronger
. . .
and the weak grow weaker.
” Examples of Battles: • QWERTY vs DVORAK • Betamax vs VHS • Blue Ray vs HD DVD
3. Power Law
On the Web a few pages have a huge number of other pages linking to them, and a very large number of pages have only a few pages linking to them. In short, the Web has many small elements, and few large ones.
Power Law
1000 900 800 700 600 500 400 300 200 100 0 1
Position of item in sequence
200 50 0 1200 1000 800 600 Relative popularity Search referrals Page views 400
The Long Tail
The internet vs. brick-and-mortar Nearly unlimited capacity Distribution and shelving costs approaching zero Global distribution channels A changing economy Popularity no longer has a monopoly on profitability Can generate significant revenues by selling small number of millions of niche products vs. selling millions of a small number of “ hits ”
The Long Tail
Wal-Mart vs. Rhapsody
Wal-Mart 39,000 songs on CDs in average store Must sell at least 100,000 copies of a CD to cover its retail overhead and make a sufficient profit Less than 1 percent of CDs sell that much Therefore, can carry only “ hits ” Itunes/Rhapsody/Spotify Millions of songs in archives Cost of storing one more song is essentially zero More streams each month beyond its top 10,000 than in the top 10,000 Therefore, no economic reason not to carry almost everything
Long Tail Examples: Travel
Netflix Long Tail
Long Tail: Good News for Consumers
Brynjolfsson, Hu, and Smith (2003): consumer surplus is 10x higher from access to increased product variety vs. access to lower prices in online stores Consumers as individuals Satisfaction of very narrow interests Mass customization as an alternative to mass-market fare
Pricing Information Goods: Differentiation of Products and Services
Strategies used: a) Mass Customization b) Differential Pricing c) Personalized Content d) Versioning
Versioning
Extremely low marginal costs rule out many traditional pricing strategies: the only viable option is to price the product according to how much value customer places on it. Individualized pricing is difficult, and the only practical way to do it is to sell different versions at different prices. The version the customer chooses will reveal the valuation she places on the product.
Versioning
Need to identify the necessary versions. Several dimensions to consider: time (or delay) of the product release hardcovers are released before paperback, movies are first shown at the cinema,
convenience
The more a customer needs information, the more freedom they’ll want in accessing it.
comprehensiveness
newspapers allow access to their recent articles, but charge for access to archives.
Versioning
Several dimensions to consider:.
annoyance
allowing some users to avoid seeing advertising,
speed
common among software makers, with different versions running at different speeds.
data processing
limit the capabilities or number of data that can be processed in different versions,
interface
from sophisticated to simple intuitive ones;
support
providing different levels of support for different products.
Optimal Number of Versions
The optimal number of versions of a product offered should be equal to the number of types of customers in the market.
But what happens if there is no obvious choice? Or if the number of types is huge.
A common choice is to have 2 versions: “Standard” and “enhanced/premium” However, recent behavioral research suggests that the optimal number is not two but three.
Extremeness aversion
Extremeness aversion: if the only two sizes of drink that you offer are the other.
small
and
large
, then some consumers will be on the margin between choosing one extreme or Some of these consumers will choose the
small
thereby reducing producer revenues.
version, Suppose the producer adds a ‘‘
jumbo
’’ version, and renames the sizes ‘‘
small
,’’ ‘‘
medium
,’’ and ‘‘
large
,’’ with the current version.
medium
being the same size as the previous
large
In this case, the medium size serves as a focal point for the indecisive: those who would have chosen small, end up compromising on medium, thereby increasing revenues
Evidence
Simonson and Tversky describe a marketing experiment in which two groups of consumers were asked to choose microwave ovens.
One group was offered a choice between two ovens: an Emerson priced at $109.99 and a Panasonic priced at $179.99.
The second group was offered three options: an Emerson priced at $109.99, a Panasonic priced at $179.99 plus a high-end Panasonic priced at $199.99
Implications
By offering the high-end oven, Panasonic increased its market share from 43% to 73%. More remarkably, the sales of the mid-priced Panasonic oven increased from 43% to 60% apparently because it was now the‘‘middle’’ choice.
Goldilocks effect
Adding a “premium” version to the product line actually boosts the sales of the mid-priced version. The newly-introduced premium version steals market share from the mid-range version, This is more than offset by the market share that the mid-range version gains at the expense of the low-end.
Note that this is purely the result of a cognitive bias – there is no objective rationale for such trading-up. The Goldilocks principle states that something must fall within certain margins, as opposed to reaching extremes.
A bit off topic. Wine!
Similarly, we see the goldilocks principle in place in restaurants that optimize the wine list Research shows that a lot of customers order second cheapest wine on the menu.
Restaurants tend to mark up the second cheapest wine the most (the largest margin of wines on the wine list)
Case: Freemium Pricing at Dropbox
Freemium Pricing Model
Concept Importance of Referral Offer limited access to a company’s service for free Charge for anything above Increasing the number of consumers is key for business success Free upgrades for referral increase the network size and revenue Industries using Freemium Apple’s App store – 2013: 77% of top 100 grossing Apps LinkedIn – 0.8% of users Evernote – 1% of users Spotify – 20% of users
Industry Overview
Global Market Value in 2011: $ 4bn Expected Value in 2018: $ 46bn What are value drivers in the industry?
What drives the price in the industry?
Direct Competitors Provider Microsoft Apple Google Amazon Platform SkyDrive iCloud Google Drive Simple Storage Price (per year per GB) $2 $2 $1.2
$.095
Google Drive 12% Actual Usage Others 17% Apple 33% Amazon 18% Dropbox 20%
What drives the prices?
How is Dropbox differentiated from its competitors?
DropBox
Overview Founded by Drew Houston and Arash Ferdowsi in 2007 Provides remote storage and file sharing, accessible online or as folder on your computer Total number of users: 200 million – 1.6 – 4 percent actually generate revenue The company targets both, private consumers and corporations Freemium pricing model Referral 500 MB storage for both sender and receiver Maximum of 16 GB Additional 2.8 million Referrals, which is a referral rate of 70 percent 12 percent conversion rate * *(individuals who install dropbox/individuals who click on the invitation link)
Approach
Problem 1.
2.
The cloud storage market was fragmented with small competitors Bureaucracy prevented business customers from purchasing cloud storage 3.
Consumers were not willing to pay for the service, as they have not adapted to the product at that time Approach 1.
2.
3.
Faster file backup and retrieval service – Combination between users’ own storage and remote storage (i.e. dropbox folder) Focus on individual consumers to avoid business bureaucracy Freemium Pricing Result 200 million users by November 2013 Valued at $ 4bn in 2013 After capturing individual consumers, focus on corporate customers
Market to Corporate Customers
Price Product Impact Corporate $800 per year for five users +$125 for each additional user Unlimited storage Administrative controls to manage documents Single-Sign-On option 14-day free trial period 40% of 400 million revenue 96-98 % use product for free Consumer Share (%) 100 90 80 70 60 50 40 30 20 10 0 Business Users all Paid Consumer Business Paid Consumer Business Unpaid