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InSite Marketing Technology. Goran Nagradic. History. Three cofounders started InSite in February 1997 Glen Urban and John Little brought new ideas on virtual buying environments, trust and discrete-choice modeling
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InSite Marketing Technology GoranNagradic
History • Three cofounders started InSite in February 1997 • Glen Urban and John Little brought new ideas on virtual buying environments, trust and discrete-choice modeling • Jeffrey Stamen along with Urban and Little recruited StefaniaNappi to be the chief executive officer and president • The three cofounders invested a total of $450000 to fund the development of a prototype of a trust-based adviser
About the company • Nappi had two priorities: hire a strong team and develop a prototype • Company started small and frugally • Its first prototype became Trusted Advisor for only $100000, released in May 1997 • In 1998 InSite raised $1.5 million from angel investors
InSite’s product • InSite’s product attempts to reduce gap between shopping on the Web and shopping in a store • Initial target markets were any sales situation that involved a product with the multiple decision option and a desire for individualized service
Online retail vs. traditional retail • Key difference is that sales people build a personal relationship with the customer • They ask questions, listen to responses and observe the customer’s behavior • Customers react to answers, observe salesperson’s behavior, form opinion about the product, salesperson and the process • Any of these can strongly influence their decision
Online retail vs. traditional retail(cont’d) • On the Web consumers wonder whether the seller will deliver as promised • They can’t feel (sense) the product • Fear of giving the credit card information • If something goes wrong with the product who will fix that
InSite’s strategy and goal • The technology would combine research on trust cues, purchasing behavior, virtual buying environments and software capabilities • Goal was to blend the low cost of information service with the personal attention of a salesperson. • The system provides unbiased product information and uses a core engine to translate customer preferences into product recommendation
InSite’s strategy and goal (cont’d) • Advisor engine takes known information about the visitor and uses rule-based prediction to create a customized experience • The engine uses marketing segment predictions to infer information about the visitor without asking a lot of information • Advisor brings products to shoppers rather then requiring shoppers to find and distinguish between the products they want
InSite’s strategy and goal (cont’d) • Insite offers two performance levels for Trusted Advisor: • Implementing a fully-featured Trusted Advisor (requires about three months) • The buyer provides knowledge about the customers and InSite translates this knowledge into the Trusted Advisor
Pricing of Advisor • Initial license was $100000 plus monthly maintenance fee of $5000 • Typical engagement would costs $200000 to $300000 for the first year and $100000 for the year after
“Jill” • Insite’s first major customer, CompUSA, wanted an online advisor that would help customers buy notebook • Insite designed an advisor, named Jill, with all knowledge available 24/7 • “Everything is going perfect” – Nappi • In three months Jill was used 25000 times; CompUSA increase sales for 6 percent; 65 percent longer site visits; increase in customer satisfaction
Problems with sales • Customers are satisfied with status quo of the web for their products • Customers adopt other concepts • Customers do not perceive the benefits • Customers perceive high costs
Reaching end • Promising sales lead nowhere • 1999 InSite was reaching the end of its resources • Venture capitalist liked the idea but they were unwilling to invest without growing number of happy customers and potential buyer
Implementation plan • Make only Advisors where buyers provide information and knowledge about the customers • Lower the price for at least 10 percent • Design special Advisors for specific fields • Make less complex model for customers andoffer 5 years free maintenance • Entered the market too early
Implementation plan (cont’d) • Make Advisors to replace menus on the Web sitesfor example: Have couple of different Advisors on the same website; to first one you tell what do you want and Advisor brings you another one(specific for that section) just like in real store • Speech recognition – you would actually talk to them not write