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

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

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

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

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

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

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

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

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

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

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

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

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 Copyright © 2009 Teck-Hua Ho

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

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

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

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 Copyright © 2009 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 Copyright © 2009 Teck-Hua Ho

Autodesk’s Revenue Model (after 2003) New Customers Existing Customers Existing Customers Copyright © 2009 Teck-Hua Ho

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

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

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

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

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

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

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

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

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

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

Customer Value Management https://www.snacvm.com Copyright © 2009 Teck-Hua Ho

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

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

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

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

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

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