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 "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

Many Sources of Leads

Leads Can Follow a Circuitous Path

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

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

Average Lead Costs Vary by Media

Some Major Categories Are More Expensive

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

Reflecting a Battle for Attention

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?

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

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?

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

With only some exceptions

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

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

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

Look Ahead Model Conclusions 1.Enter a website, observe page. 2.Update beliefs about site. 3.If expected value of continuing high enough, visit new page. Otherwise, leave. Basic model result: The “bar” starts low and keeps rising.

Additional Factors: Involvement & Repeat Visit

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.

Computing the Value of the Funnel Rates No notice rate (NNR)70.00% Click-through rate (CTR)0.75% Prospect conversion rate (PCR)3.00% Repeat buyer rate (RR)90.00% Offline induced buyer rate (OIB)5.00% Offline buy rate (OBR)30.00%

Wine Glass Plots

Web Chain Data: Impacts Impacts: Ad brand impact$0.005 Web site brand impact$0.38 Offline profit$15.35 Online profit$23.00 New customer lifetime value (LTV)$95.00

A Simple Web Chain Analyzer Inputs Outputs

Search Bidding Revisited: The Perspective of the Advertiser

Search engine referrals to eBay are divided between natural and paid implementations 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 NaturalPaid 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)

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

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. Types of search companies Search EnginesSearch DirectoriesSEO’sBid for placement

Types of search companies Search EnginesSearch DirectoriesSEO’sBid 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.

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

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

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

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

Two Stage Process Stage 1 Data Gives Best Position per Keyword

Stage 2: Select profitable keywords

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.

Errata: Table 5-4