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  • Reverse direction of WOM WOM is delivered from left to right Value is credited back from right to left
  • Transcript

    • 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)
      • M = Total number of items listed per year
      • Fee i = Insertion fee of item i
      • Com i = Final value fee of item i
      • I i = 1 if item i is sold; 0 otherwise
      • M depends on number of people in the community
      • Com i x I i increases with price or seller surplus
      Copyright © 2009 Teck-Hua Ho Revenue Levers
    • 5. S calability Principle Copyright © 2009 Teck-Hua Ho A key feature of the revenue model: Revenues increase linearly with M but costs do not increase with M .
    • 6. M atching 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
      • S calability, so that revenues grow at least as fast as costs.
      • M atching value appropriation with value creation.
      • A ccelerate diffusion, adoption, and upgrade purchases.
      • R elationship based ( i.e., facilitate and build on repeated interaction with customers where possible).
      • T otal 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)
      • M = Total number of items listed per year
      • Fee i = Insertion fee of item i
      • Com i = Final value fee of item i
      • I i = 1 if item i is sold; 0 otherwise
      • M depends on number of people in the community
      • Com i x I i increases with price or seller surplus
      Copyright © 2009 Teck-Hua Ho Revenue Levers
    • 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 Fee i
        • Encourage more pictures and promotion of items
      • Increase Com i
        • Increase average number of bidders / auction (so as to increase seller surplus)
        • Encourage high-priced items (e.g., electronics, cars)
      • Increase I i
        • 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)
      • M = Total number of items listed per year
      • Fee i = Insertion fee of item i
      • Com i = Final value fee of item i
      • I i = 1 if item i is sold; 0 otherwise
      • M depends on number of people in the community
      • Com i x I i increases with price or seller surplus
      Copyright © 2009 Teck-Hua Ho Revenue Levers
    • 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.
      http://news.bbc.co.uk/2/hi/technology/4238258.stm Copyright © 2009 Teck-Hua Ho
    • 14. eBay’s Revenue Model after 2005
      • M = Total number of items listed per year
      • Fee i = Insertion fee of item i
      • Com i = Final value fee of item i
      • I i = 1 if item i is sold; 0 otherwise
      • R i = Reserve price fee for item i
      • S j = Monthly subscription fee of storefront j
      • N = Total number of storefronts
      Copyright © 2009 Teck-Hua Ho Revenue Levers
    • 15. Move from Transaction to R elationship-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
      • S calability, so that revenues grow at least as fast as costs.
      • M atching value appropriation with value creation.
      • A ccelerate diffusion, adoption, and upgrade purchases.
      • R elationship based ( i.e., facilitate and build on repeated interaction with customers where possible).
      • T otal 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)
      • N = Total number of customers
      • P = Total number of products
      • n ij = Number of users in Customer i for Product j
      • P j,new = Purchase price of Product j
      • P j,Upgrade = Upgrade price of Product j
      • I ij, Upgrade = 1 if Customer i adopts the upgrade of Product j
      Copyright © 2009 Teck-Hua Ho Revenue Levers New Customers Existing Customers
    • 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
      Copyright © 2009 Teck-Hua Ho
    • 19. Autodesk’s Revenue Model (after 2003) Copyright © 2009 Teck-Hua Ho New Customers Existing Customers Existing Customers
    • 20. New Revenue Levers
      • I ij, Sub = 1 if Customer i subscribes to Product j
      • I ij, Renewal = 1 if Customer i renews the subscription for Product j
      • P j,Sub = Subscription fee of Product j
      • P j,Renewal = Renewal fee of Product j
      Copyright © 2009 Teck-Hua Ho
    • 21. SMART Principles
      • S calability, so that revenues grow at least as fast as costs.
      • M atching value appropriation with value creation.
      • A ccelerate diffusion, adoption, and upgrade purchases.
      • R elationship based ( i.e., facilitate and build on repeated interaction with customers where possible).
      • T otal 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
      • N = Total number of customers
      • IC i = Installation charge for customer i
      • C i = Cost of installation for customer i
      • RMR i = Recurring monthly revenue for customer i
      • T i = Life time of customer i
      Copyright © 2009 Teck-Hua Ho Revenue Levers Customer Life-time Value
    • 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) Copyright © 2009 Teck-Hua Ho The Rest of the World Suspects Prospects Inactive Customers “ Top” > $500 “ Big” $150 - $500 “ Medium” $50 - $150 “ Small” < $50 Recurring Monthly Revenue
    • 25. Security Alarm Company Copyright © 2009 Teck-Hua Ho 2005 Sample Size 2006 Sample Size RMR – Average ($) RMR – Maximum ($) 2122 2238 125 2065
    • 26. Customer Migration Matrix Copyright © 2009 Teck-Hua Ho 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
    • 27. Customer Migration Matrix Copyright © 2009 Teck-Hua Ho 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
    • 28. Average RMR by Segment Copyright © 2009 Teck-Hua Ho Top ( >$500) Big ( $200-$500) Medium ( $80-$199) Small ( <$80) $801 $304 $126 $48
    • 29. Loss in Revenue due to Retention Copyright © 2009 Teck-Hua Ho Total Loss in Customer Life-time Value = 50 months (average life-time) x $35,484 =$1.78m Transition Number of Transitions Loss in RMR / Transition ($) 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
    • 30. Customer Value Management Copyright © 2009 Teck-Hua Ho https://www.snacvm.com
    • 31. SMART Principles
      • S calability, so that revenues grow at least as fast as costs.
      • M atching value appropriation with value creation.
      • A ccelerate diffusion, adoption, and upgrade purchases.
      • R elationship based ( i.e., facilitate and build on repeated interaction with customers where possible).
      • T otal 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 Copyright © 2009 Teck-Hua Ho Customer Life-time Value = Customer Purchase Value + Customer Influence Value
    • 33. 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 Copyright © 2009 Teck-Hua Ho V V V
    • 34. Customer Influence Value t time Consider Bob: credit back s 1 s 2 s 3 each credit back credit back Bob’s influential value = I 1 + I 2 + I 3 Copyright © 2009 Teck-Hua Ho V V V
    • 35. Purchase Acceleration Copyright © 2009 Teck-Hua Ho No Purchase Acceleration Purchase Acceleration Increase% Size of “Targeted Sample” 0 4.2% - Total Life-time Customer Value 100 115.5 15.5%
    • 36. SMART Principles
      • S calability, so that revenues grow at least as fast as costs.
      • M atching value appropriation with value creation.
      • A ccelerate diffusion, adoption, and upgrade purchases.
      • R elationship based ( i.e., facilitate and build on repeated interaction with customers where possible).
      • T otal appropriated value ( i.e., focus on total customer value, including lifetime customer value and influencer value).
      Copyright © 2009 Teck-Hua Ho