E-Commerce Hai Hoang 4/25/2005 Outline ► Definition ► Why use E-commerce? ► Current State of E-Commerce ► Barriers in Adopting E-Commerce ► Motivations for CBR ► Using CBR to Provide Intelligent Support ► Why database search is not good enough? ► Phases of Sales in E-commerce ► Demo ► Conclusion Definition ► E-Commerce exchange of: typically refers to the 1) information 2) goods 3) and services ► Through electronic networks Why use E-commerce? ► Can be summarized as providing “incentives” ► Incentives: Browse catalogs without leaving house or office (convenience) Shop anytime, anywhere Compare prices from different vendors (variety) Cheaper prices Direct from supplier without 3rd parties No Tax if store is out of state Oops, all from the customer’s perspective, - sellers also benefit from e-commerce too Why use E-Commerce? ► Seller: World-wide customers No need for a physical store Cheaper to setup a store Maintenance cost? (packaging cost? Example software) Hire less workers ► And a lot more – depending on the business Current State of E-Commerce ► Online sales represent 5.4% of all retail sales in 2004 ► By 2008, it has been estimated to only reach about 10%. ► With all the incentives listed on the previous two slides: Why is it only a small percentage of all retail sales? Barriers in Adopting E-Commerce ► What kind of barriers? ► Tannenbaum summarizes into 3 words: Confidence – security, privacy, liability Convenience – easy of access, use, purchase, and get support Content – variety of products and services ► Which one can CBR help to overcome? Make the it more convenient Motivations for CBR •“On the Internet, companies only have computers to represent them. They better be intelligent computers.” Chuck William, CEO Brightware •The answer CBR??? Motivations for CBR (cont.) ► Dell: I want a gaming computer that could support the latest game, ie Half-Life 2 ► Preferred System Configuration 2.4 GHz Processor 512MB RAM DirectX 9 capable graphics card 256mb Windows 2000/XP/ME/98 Internet Connection ► Example: Dell fails to provide the sale support (show example at dell.com) Using CBR to Provide Intelligent Support ► How can we use CBR? search, select, and support. ► Refine searching capabilities Traditional database queries is not powerful enough ► Reduce required domain knowledge ► Therefore, reduce customer support staff Why database search is not good enough? ► What’s wrong with a huge database with a search database search engine on top of it? Too many results ► Provided that the search engine is good. It could narrow down the search for you very well. What else could be wrong? It fails to provide sales support (tailored recommendations) ► Remember the Dell example??? Phases of Sales in E-commerce ►3 phases of sales Pre-sales Sales After-sales ► All 3 could use CBR to provide support Pre-sales ► Customer has an idea of what he wants to buy ► Customer attains information about products and services ► Traditional way is electronic catalogs and databases Pre-sales: presenting products ► Index & Ontologies Amazon.com ► Requirements Expedia.com based Pre-sales: Misses ► With index & onthologies Too many results Specific speaker might be listed in a different category ► With requirements based Typos What if there is a date close by the one specified? What about close by airports? Special deal for the specific destination? Pre-sales: Misses example ► Example at expedia.com (Flight search) (Last minute packages) Pre-sales: CBR example ► Analog ► Travel Devices Agency Last Minute Deals (no implementation yet) (DietoRecs) (Nut King) Analog Devices Example ► Analog Devices makes electronic parts ► Most of the calls to their support number is because they can’t find the desired parts by looking in the catalog. ► Solution: create an online store that allows engineers to find desired parts based on functionality using CBR Analog Devices Example ►A case is represented with 40 parameters (String, integer, symbols) Type, input/output voltage, size ► Parameters are divided into a few categories ► System creates a query based on these parameters, using a few or all ► www.analog.com for example of UI ► (Note the priority checkbox) AD: Similarities (discrete) ► similarities are calculated by applying local similarity measures. ► Note: table is asymmetric AD: Similarities (continuous) ► Represented ► Anything as a function instead of a table greater than query, 1, otherwise, it’s from 0 to .5 Travel Agency ► Interactive Expedia, Orbitz, Hotwire Nut King, DieToRecs (CBR) ► Interactive Last Minute Deals Somewhat available at those sites mentioned above CBR to recommend close matches Travel Agency (cont.) ► Last minute deals are sold as-is ► Used to be distributed with flyers ► Up to 200,000 deals sold in peak season ► could be represents as cases ► When user search for a destination, recommend similar deals Travel Agency (CBR impl.) ► Treat deals as cases with attributes ► Recommend deals with intelligence using CBR Search: 1.) January Response: No match at Blue Mountain 2.) Blue Mountain 3.) Skiing, Hotel 1.) January 2.) Bear’s Creek Suggest closest case 3.) Skiing, Hotel 4.) 1 day 4.) 1 day 5.) $50 - $100 5.) $89 Sales Phase Sales (CBR Cycle) • Might have to go through the cycle a few times before user accepts the proposed product. •Each time user’s evaluation refines the demand •Retain phase must not take place because a successful sale does not lead to a new product in the product base Negotiation During Sales ► During the negotiation process, the buyer and seller refine the problem description and the product description to solve the customer’s problem ► The seller should help the customer to make a decision not tell them when their requirements are fullfilled CBR in Negotiation ► Active or Passive Sales Agent Active – suggest a particular modification of a demand to the user Passive – Offer possible modifications to the user, the user pick what to modify ► Modification Products of the Demands vs the Ex free gifts or configurable products Sales ► Over or Under specification of customer’s demands Need to relax the demands Can see this at Nut King and DieToRecs After the Sales ► Support ► CBR in online help systems HP, Gateway, Dell, and 3com have been using CBR in their online support system ► The reason? Call-avoidance Demo ► DieToRecs http://eu-project.hgb.tiscover.at/dialogservlet ► Nut King http://itr.itc.it:8080/dev/jsp/language.do?action =english Conclusions ► E-Commerce is still only a small portion of the retail market – there is a lot of potential for growth ► CBR can be used with all 3 phases of the sales. ► Help to narrow down the search result ► Make intelligent suggestions ► Make online system behave more like human sales agents ► Provide intelligent support References ► ► ► ► ► ► ► ► Intelligent Sales Support with CBR. Wolfgang Wilke, Mario Lenz, Stefan Wess Experience Management for Electronic Ecommerce. Francesco Ricci http://ectrl.itc.it/home/home_people/ricci/ (last visited: April 20, 2005) (online e-commerce stat) http://retailindustry.about.com/od/seg_internet/a/bl_nrf052504.htm (online shopping benefits) http://wiki.media-culture.org.au/index.php/Online_Shopping__Benefits_for_Buyers (half-life 2 spec) http://www.ultimate-gamer.com/halflife2/hl2.htm (DieToRecs) http://eu-project.hgb.tiscover.at/dialogservlet (Nut King) http://itr.itc.it:8080/dev/jsp/language.do?action=english