1. SMART Revenue Model Design Teck Ho UC, Berkeley
Copyright © 2009 Teck-Hua Ho

2. Fundamental Functions of Business
Value Creation Value Appropriation
Copyright © 2009 Teck-Hua Ho

3. Revenue Model Design Examples of Revenue Model
eBay
Autodesk
Bay Alarm
SMART Revenue Model Design
Copyright © 2009 Teck-Hua Ho

4. eBay’s Original Revenue Model (up to 2005)
Revenue Levers
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
Copyright © 2009 Teck-Hua Ho

5. Scalability Principle
A key feature of the revenue model:
Revenues increase linearly with M but
costs do not increase with M.
Copyright © 2009 Teck-Hua Ho

6. 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?
Copyright © 2009 Teck-Hua Ho

7. SMART Principles
Scalability, so that revenues grow at least as fast as costs.
Matching value appropriation with value creation.
Accelerate diffusion, adoption, and upgrade purchases.
Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).
Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).
Copyright © 2009 Teck-Hua Ho

8. eBay’s Original Revenue Model (up to 2005)
Revenue Levers
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
Copyright © 2009 Teck-Hua Ho

9. 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)
Copyright © 2009 Teck-Hua Ho

10. 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 fees
Listing 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
Copyright © 2009 Teck-Hua Ho

11. eBay’s Original Revenue Model (up to 2005)
Revenue Levers
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
Copyright © 2009 Teck-Hua Ho

12. 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.
Copyright © 2009 Teck-Hua Ho

13. 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.
Copyright © 2009 Teck-Hua Ho

14. eBay’s Revenue Model after 2005
Revenue Levers
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
Ri = Reserve price fee for item i
Sj = Monthly subscription fee of storefront j
N = Total number of storefronts
Copyright © 2009 Teck-Hua Ho

15. 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
Copyright © 2009 Teck-Hua Ho

16. SMART Principles
Scalability, so that revenues grow at least as fast as costs.
Matching value appropriation with value creation.
Accelerate diffusion, adoption, and upgrade purchases.
Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).
Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).
Copyright © 2009 Teck-Hua Ho

17. Autodesk’s Revenue Model (up to 2003)
New Customers
Existing Customers
Revenue Levers
N = Total number of customers
P = 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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18. 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
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19. Autodesk’s Revenue Model (after 2003)
New Customers
Existing Customers
Existing Customers
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20. 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
Copyright © 2009 Teck-Hua Ho

21. SMART Principles
Scalability, so that revenues grow at least as fast as costs.
Matching value appropriation with value creation.
Accelerate diffusion, adoption, and upgrade purchases.
Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).
Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).
Copyright © 2009 Teck-Hua Ho

22. Bay Alarm Revenue Model
Customer Life-time Value
Revenue Levers
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
Copyright © 2009 Teck-Hua Ho

23. 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
Copyright © 2009 Teck-Hua Ho

24. Security Alarm Company (Commercial)
“Top”
> $500
“Big” $150 - $500
“Medium” $50 - $150
“Small”
< $50
Recurring Monthly Revenue
Inactive Customers
Prospects
Suspects
The Rest of the World
Copyright © 2009 Teck-Hua Ho

25. Security Alarm Company
2005 Sample Size
2006 Sample Size
RMR – Average ($)
RMR – Maximum ($)
2122
2238
125
2065
Copyright © 2009 Teck-Hua Ho

26. Customer Migration Matrix
Customers in 2005
Top
Big
Medium
Small
Inactive 74 64 2 1 7
251 16
197 4 34
517 32
401 3 81
1280 65
1073
140
New Customers in 2006
478 14
170
287
Total Customers in 2006 87
247
641
1363
262
Copyright © 2009 Teck-Hua Ho

27. Customer Migration Matrix
Customers in 2005
Top
Big
Medium
Small
Inactive 74
86.5%
2.7%
1.4%
9.5%
251
6.4%
78.5%
1.6%
13.5%
517
6.2%
77.6%
0.6%
15.7%
1280
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
Copyright © 2009 Teck-Hua Ho

28. Average RMR by Segment Top (>$500) Big ($200-$500)
Medium ($80-$199)
Small (<$80)
$801
$304
$126
$48
Copyright © 2009 Teck-Hua Ho

29. 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
Top to Small
753
Top to Inactive 7
801
5607
Big to Medium 4
178
712
Big to Small
256
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
Copyright © 2009 Teck-Hua Ho

30. Customer Value Management
Copyright © 2009 Teck-Hua Ho

31. SMART Principles
Scalability, so that revenues grow at least as fast as costs.
Matching value appropriation with value creation.
Accelerate diffusion, adoption, and upgrade purchases.
Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).
Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).
Copyright © 2009 Teck-Hua Ho

32. Customer Life-time Value Equation=
Customer Purchase Value + Customer Influence Value
Copyright © 2009 Teck-Hua Ho

33. Customer Purchase Value
Consider Bob:
credit back t
time
Self-motivated:
Bob’s purchase value = V
Influenced by others:
Bob’s purchase value = V
is credited back to the person influenced him V
Copyright © 2009 Teck-Hua Ho

34. Customer Influence Value
Consider Bob: t s1 s2 s3
time
credit back V
each credit back V
Reverse direction of WOM
WOM is delivered from left to right
Value is credited back from right to left
credit back V
Bob’s influential value
= I1 + I2 + I3
Copyright © 2009 Teck-Hua Ho

35. Purchase Acceleration
No Purchase
Acceleration
Purchase
Increase%
Size of “Targeted Sample”
4.2% -
Total Life-time Customer Value
100
115.5
15.5%
Copyright © 2009 Teck-Hua Ho

36. SMART Principles
Scalability, so that revenues grow at least as fast as costs.
Matching value appropriation with value creation.
Accelerate diffusion, adoption, and upgrade purchases.
Relationship based (i.e., facilitate and build on repeated interaction with customers where possible).
Total appropriated value (i.e., focus on total customer value, including lifetime customer value and influencer value).
Copyright © 2009 Teck-Hua Ho