teck-hua ho copyright © 2009 teck-hua ho smart revenue model design teck ho uc, berkeley

Teck-Hua HoCopyright © 2009 Teck-Hua Ho

SMART Revenue Model Design

Teck HoUC, Berkeley

Teck-Hua Ho

Fundamental Functions of Business

Copyright © 2009 Teck-Hua Ho


Revenue Model Design

Examples of Revenue Model eBay Autodesk Bay Alarm

SMART Revenue Model Design


eBay’s Original Revenue Model (up to 2005)

M = Total number of items listed per year

Feei = Insertion fee of item i

Comi = Final value fee of item i

Ii = 1 if item i is sold; 0 otherwise

M depends on number of people in the community

Comi x Ii increases with price or seller surplus

M

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Revenue Levers


Scalability Principle

A key feature of the revenue model:Revenues increase linearly with M but costs do not increase with M.

Teck-Hua Ho

Matching Appropriated Value to Value Creation

Who are eBay’s customers? (Bidders? Buyers? Sellers?)

What does it mean for eBay to do a better job?

Does eBay get paid more for doing a better job?



SMART Principles

1. Scalability, so that revenues grow at least as fast as costs.

2. Matching value appropriation with value creation.

3. Accelerate diffusion, adoption, and upgrade purchases.

4. Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).

5. Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).









M

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Revenue Levers


Ways to Enhance eBay’s Revenue

Increase M Increase size of community, Enter new markets and product categories Increase turnover (e.g., reduce bidding duration, encourage setting of buyout

prices)

Increase Feei Encourage more pictures and promotion of items

Increase Comi Increase average number of bidders / auction (so as to increase seller surplus) Encourage high-priced items (e.g., electronics, cars)

Increase Ii Increase average number of bidders / auction so as to increase the probability

that the highest bid > reserve price Encourage a lower reserve price (e.g., the recent increase in insertion fee for

reserve price auction)


Ways to Increase Auction-off Rate

Fees to list an item for regular auctions, fees is a function of starting price for vehicles, a function of type of vehicles for real estate, a function of types of properties and listing type

Picture Service Fees—first picture free, additional picture or bigger picture incurs feesListing upgrade fees: various options to promote items

Final value fees for regular auction, charged when reserve met, at a function of the closing bid For vehicles, charged when the first bid over the reserve price is placed (regardless

of whether sale is finally made) For real estate, a fixed fee for land/time share where there is successful high bid on

the item and no fees for other type of real estates

Reservation Price Fees—charged only if item not sold, a function of reserve price

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Revenue Levers

Teck-Hua Ho

Acquisitions and Investments

In July, 1998, eBay acquired Cincinnati, OH based online auction site Up4Sale.com. In May, 1999, eBay acquired the online payment service Billpoint, which it shut down after

acquiring PayPal. In 1999, eBay acquired the auction house Butterfield & Butterfield, which it sold in 2002 to

Bonhams. In 1999, eBay acquired the auction house Alando for $43 million, which changed then to

eBay Germany. ebay aqcuired kruse auctions In June, 2000, eBay acquired Half.com for $318 million, which was later integrated with the

eBay Marketplace. In August, 2001, eBay acquired Mercado Libre, Lokau and iBazar, Latin American auction

sites. In July, 2002, eBay acquired PayPal, for $1.5 billion in stock. On January 31, 2003, eBay acquired CARad.com, an auction management service for car

dealers. On July 11, 2003 eBay Inc. acquired EachNet, a leading ecommerce company in China,

paying approximately $150 million in cash.


Teck-Hua Ho

Acquisitions and Investments

On June 22, 2004, eBay acquired all outstanding shares of Baazee.com, an Indian auction site for approximately US $50 million in cash, plus acquisition costs.

On August 13, 2004, eBay took a 25% stake in Craigslist by buying out an existing shareholder who was once a Craigslist employee.

In September 2004, eBay moved forward on its acquisition of Korean rival Internet Auction Co. (IAC), buying nearly 3 million shares of the Korean online trading company for 125,000 Korean won (about US$109) per share.

In November 2004, eBay acquired Marktplaats.nl for €225 million. This was a Dutch competitor which had an 80% market share in the Netherlands, by concentrating more on small ads than actual auctions.

On December 16, 2004, eBay acquired Rent.com for $415 million in cash (original deal was for $385 million of the amount in eBay stock plus $30 million in cash).

In May 2005, eBay acquired Gumtree, a network of UK local city classifieds sites. On May 18, 2005, eBay acquired the Spanish classifieds site Loquo. In June 2005, eBay acquired Shopping.com, an online comparison site for $635 million. At the end of June 2005, eBay acquired the German language classifieds site Opus Forum. In September 2005, eBay bought Skype, a VoIP company, for $2.6 billion in stock and cash.

http://news.bbc.co.uk/2/hi/technology/4238258.stm



eBay’s Revenue Model after 2005





Ri = Reserve price fee for item i

Sj = Monthly subscription fee of storefront jN = Total number of storefronts

N

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Revenue Levers

Teck-Hua Ho

Move from Transaction to Relationship-based Revenue

Encourage frequent sellers to open a storefront increases customer loyalty Increases number of items listed (especially more

expensive items) on eBay

Encourage sellers to switch from another auction platform (amazon.com) to eBay

Encourage existing storefronts to migrate to a more expensive storefront



SMART Principles







Autodesk’s Revenue Model (up to 2003)

N = Total number of customersP = Total number of products

nij = Number of users in Customer i for Product j

Pj,new = Purchase price of Product j

Pj,Upgrade = Upgrade price of Product j

Iij, Upgrade = 1 if Customer i adopts the upgrade of Product j

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Pn

Revenue Levers

New Customers

Existing Customers

Teck-Hua Ho

Challenges

Transaction-based rather than relationship-based

Probability of upgrade less than 1/3 and the investment in software upgrade is huge

High variability in revenue flow



Autodesk’s Revenue Model (after 2003)

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PnNew Customers

Existing Customers

Existing Customers


New Revenue Levers

Iij, Sub = 1 if Customer i subscribes to Product j

Iij, Renewal = 1 if Customer i renews the subscription for Product j

Pj,Sub = Subscription fee of Product j

Pj,Renewal = Renewal fee of Product j


SMART Principles







Bay Alarm Revenue Model

N = Total number of customers

ICi = Installation charge for customer i

Ci = Cost of installation for customer i

RMRi = Recurring monthly revenue for customer i

Ti = Life time of customer i

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ti

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RMRCIC LTV i

Revenue Levers

Customer Life-time Value

Teck-Hua Ho

Optimizing Life-time Value

Analyze how customer i’s life-time varies with demographics, chosen products, and payment methods

Tradeoff between IC and RMR

Focus on customer pyramid and migration

Buy and sell customers based on expected life-time value



Security Alarm Company (Commercial)

The Rest of the World

Suspects

Prospects

Inactive Customers

“Top”> $500

“Big” $150 - $500

“Medium”$50 - $150

“Small”< $50

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enue


Security Alarm Company

2005 Sample Size

2006Sample Size

RMR – Average($)

RMR – Maximum($)

2122 2238 125 2065


Customer Migration Matrix

Customers in 2005 Top Big Medium Small Inactive

Top 74 64 2 1 0 7

Big 251 16 197 4 0 34

Medium 517 0 32 401 3 81

Small 1280 0 2 65 1073 140

New Customers in 2006 478 7 14 170 287 0

Total Customers in 2006 87 247 641 1363 262


Customer Migration Matrix

Customers in 2005 Top Big Medium Small Inactive

Top 74 86.5% 2.7% 1.4% 0 9.5%

Big 251 6.4% 78.5% 1.6% 0 13.5%

Medium 517 0 6.2% 77.6% 0.6% 15.7%

Small 1280 0 0.2% 5.1% 83.8% 10.9%

New Customers in 2006 478 1.5% 2.9% 35.6% 60.0%

Total Customers in 2006 87 247 641 1363 262


Average RMR by Segment

Top(>$500)

Big($200-$500)

Medium($80-$199)

Small(<$80)

$801 $304 $126 $48


Loss in Revenue due to Retention

Transition Number of Transitions Loss in RMR / Transition($)

Total Loss in RMR($)

Top to Big 2 497 994

Top to Medium 1 675 675

Top to Small 0 753 0

Top to Inactive 7 801 5607

Big to Medium 4 178 712

Big to Small 0 256 0

Big to Inactive 34 304 10336

Medium to Small 3 78 234

Medium to Inactive 81 126 10206

Small to Inactive 140 48 6720

TOTAL 272 35484

Total Loss in Customer Life-time Value = 50 months (average life-time) x $35,484 =$1.78m


Customer Value Management

https://www.snacvm.com


SMART Principles







Customer Life-time Value Equation

Customer Life-time Value =

Customer Purchase Value + Customer Influence Value

Teck-Hua Ho

Customer Purchase Value

t time

Self-motivated:

Consider Bob:

=

Influenced by others: Bob’s purchase value =

credit back

is credited back to the person influenced him

Bob’s purchase value


V

V

V

Teck-Hua Ho

Customer Influence Value

t time

Consider Bob:

credit back

s1 s2 s3

each credit back

credit back

Bob’s influential value = I1 + I2 + I3


V

V

V

Teck-Hua Ho

Purchase Acceleration

No Purchase Acceleration

PurchaseAcceleration

Increase%

Size of “Targeted Sample”

0 4.2% -

Total Life-time Customer Value

100 115.5 15.5%



SMART Principles






teck-hua ho copyright © 2009 teck-hua ho smart revenue model design teck ho uc, berkeley

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