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Topics for Today

Topics for Today. Customer leads What to learn from web site visits? Web chain analysis of visits Visitor perspective Web site perspective Acquiring customers through search Industry structure How much to bid?. Online Business Relies on Leads.

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Topics for Today

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  1. Topics for Today • Customer leads • What to learn from web site visits? • Web chain analysis of visits • Visitor perspective • Web site perspective • Acquiring customers through search • Industry structure • How much to bid?

  2. Online Business Relies on Leads "Just give me some leads that don't come out of a phone book, huh, you give me something hotter than that and I can close it. It's just a streak. I'm gonna turn it around." Shelly in Glen Gary Glen Ross

  3. Many Sources of Leads

  4. Leads Can Follow a Circuitous Path

  5. Not Always Responding Online Ingenio sells ads that lead to a phone call – but still tracked by the system.

  6. Good Leads are Illusive These relatively high conversion rates imply only 1 purchaser out of 1,000 impressions.

  7. Average Lead Costs Vary by Media

  8. Some Major Categories Are More Expensive

  9. Some Online Leads are VERY Expensive Overture keyword: “peritoneal mesothelioma”

  10. Reflecting a Battle for Attention

  11. Reflecting High Potential Profitability • Sources of High Lead Values (Shelly’s hot leads) • High conversion rates • High customer lifetime value • Back of the envelope for p. mesothelioma. • Formula?

  12. All of Which Makes Understanding Web Use Valuable • How web visits evolve. • Duration • Explanation • Quantifying a web chain & results. • Search economics

  13. Web Site Visit Decisions • Our Becker activity model allocates time between activities (the “macro problem”) • Visitors repeatedly solve: “Should I stay or should I go” at a site (the “micro problem”) • Most web site visits are very short. • One more click, or try new site?

  14. Web site visits are short The Length of Visits on the Xerox Company Web Site, in page views. Source: Huberman and Lukose

  15. With only some exceptions

  16. How Visitors Browse Has Implications for Site Design and Site Economics • Is it best to view visitors as “economic agents” or “mechanical channel changers” when browsing? • Implications for • Site design • Customer acquisition costs • Strength of revealed preference information

  17. The “Random Surfer” Model • A user has a constant probability q of continuing at a site (may change between sites, time of day, location of usage). • Web site visit lengths are random draws. Implication -> Passive browsing

  18. The “Look Ahead” Model • A web site visit is a dynamically evolving sample trying to solve a problem. • Visitors strategically evaluate the value of continuing a visit or going elsewhere. Implication -> Active browsing

  19. Look Ahead Model Conclusions • Enter a website, observe page. • Update beliefs about site. • If expected value of continuing high enough, visit new page. Otherwise, leave. • Basic model result: The “bar” starts low and keeps rising.

  20. Additional Factors: Involvement & Repeat Visit

  21. Either Model Produces Benefits to the Site • Exposure to information Leads to Actions • Actions have quantifiable benefits • Branding • Registration • Purchase • New customer • Repeat buying Customer funnel has steep drop off.

  22. Computing the Value of the Funnel

  23. Wine Glass Plots

  24. Web Chain Data: Impacts

  25. A Simple Web Chain Analyzer Inputs Outputs

  26. Search Bidding Revisited: The Perspective of the Advertiser

  27. Search engine referrals to eBay are divided between natural and paid implementations Natural Paid • Free • eBay URLs “picked up” by search engine crawlers that index the web • Less control over what is included and how it is presented • Less ability to be tracked • Can be optimized through meta-tagging and other methods, though algorithms and methods used to index differs by search engine and changes over time • Two primary methods for paying for search marketing: • Pay for inclusion (e.g. Inktomi, Looksmart) • Pay for placement (e.g. Google, Overture) • Execution differs by partner: • Within results (e.g. Overture, Inktomi) • Alongside results (e.g. Google)

  28. Search Landscape Search Model Description Companies Search engines Crawl the web and present the search results based on algorithm Google, AltaVista, FAST, Inktomi Search directories Looksmart, Open Directory Human edited directories of web sites SEOs Be1st, Gateway Traffic,Traffic Boss Companies that optimize web pages for inclusion in search engine results Bid-for-placement Sites where advertisers bid for advertising placements and placement within search results Overture, Google, FindWhat,Sprinks

  29. Types of search companies Search Engines Search Directories SEO’s Bid for placement • Search engine optimization companies (SEO’s) develop optimized “mirror” web pages in order to get “picked up” by search engines and included in search indexes. • These listings/web pages ultimately attract traffic that is redirected to eBay, and the SEO’s get paid based on activity generated on eBay from this traffic.

  30. Types of search companies Search Engines Search Directories SEO’s Bid for placement • With cost-per-click, bid-for-placement programs, advertisers bid for higher placement in search results. • Google and Overture have CPC bid-for- placement programs. • Here, we see an eBay listing for “wedding cards” syndicated from Overture on Lycos Search.

  31. Sources of keyword queries for paid search marketing efforts • Top searched terms on eBay • Top searched terms on search sites • Category managers (top products, brands, etc.) • Keyword suggestion tools (i.e. Overture search suggestion tool) • eBay search engine referral logs • Keyword dictionary from eBay listings in database

  32. Keyword Dictionary • Daily snapshot of site supply • Enables partners to more effectively drive demand • Helps in prioritization of new keywords to include in search marketing campaigns

  33. Imagine You Sell Fuel Pumps • What position to bid for? • How much to bid? • How to develop the data?

  34. Recall that Max Bids doesn’t necessarily equal actual price Cost per action actual price conversion rate

  35. Two Stage Process Stage 1 Data Gives Best Position per Keyword

  36. Stage 2: Select profitable keywords

  37. Summary • Leads are the key concept for recruiting online traffic, • Lead value is driven by: • Value of ultimate customers • Conversion rates • Alternative sources of traffic • Negotiation power & risk sharing.

  38. Errata: Table 5-4

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