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Agent Technology for e-Commerce

Chapter 4 of the e-Commerce series discusses the application of shopping agents in improving consumer buying behavior. It outlines the Consumer Buying Behavior (CBB) model, consisting of stages like need recognition, product and merchant brokering, negotiation, purchase, and evaluation. The text highlights the benefits of using shopping agents, such as saving time, comparing product specifications, and uncovering better deals. It also addresses the challenges of information overload, privacy concerns, and biases in recommendation systems, emphasizing the need for unbiased and personalized assistance in online shopping.

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Agent Technology for e-Commerce

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  1. Agent Technology for e-Commerce Chapter 4: Shopping Agents Maria Fasli http://cswww.essex.ac.uk/staff/mfasli/ATe-Commerce.htm

  2. Consumer Buying Behaviour Model • Consumer Buying Behaviour (CBB) theory provides a model that describes the actions and decisions involved in buying and selling goods and services • Most CBB models involve six stages: • Need recognition • Product brokering • Merchant brokering • Negotiation • Purchase and delivery • Service and evaluation • Agent technology can be potentially used in every stage

  3. Online shopping: The problem • Consumers’ attitudes towards online shopping have changed • To search for a product, a consumer can: • Visit specific vendors’ sites that she is aware of • Use standard search engines and keyword retrieval to identify potential vendors and products • In each site visited the consumer can search for a product, its price, specification and other attributes

  4. This approach has several shortcomings: • There may be hundreds of vendors selling the same or similar products – checking vendors requires time • Returned results through standard search technology may be biased • If more than one products are required there may be no single site that caters for all • When visiting a new vendor, the consumer needs to get acquainted with new interfaces: time-consuming and also hinders impulse shopping

  5. Vendors may allow users to sign up to receive alerts • Completing lengthy forms may be required which may also require the user to provide personal information – the user’s privacy is weakened • Such services are impersonal

  6. Using shopping agents • Users have more choice, but there are too many choices; information overload • Shopping agents or shopbots can enhance the users’ shopping experience by: • Helping them decide what to buy • Finding specifications and reviews for products • Comparing products, vendors and services according to user-defined criteria • Finding the best value products and services • Monitoring online shops for product availability, special offers and discounts and sending alerts

  7. Potential benefits For the individual user • Time savings • More vendors can be queried and better deals can be uncovered • User can have access to smaller vendors • Help them make educated decisions • Psychological burden-shifting

  8. For the marketplace • Shopping agents and reputation systems can help tackle fraud • Increased competition • Market efficiency • Smaller vendors can be visible Shopping agents can be used not only on retail markets, but also on business-to-business (B2B) markets

  9. Working for the user To be truly useful and work for the user they have to: • Be impartial i.e. provide unbiased information to the user • Be autonomous, proactively seek to help the user for instance by checking for products etc. • Preserve privacy when required, the user’s identity may have to be concealed to preserve her privacy • Offer personalized services to the user • Make comparisons based on multiple attributes

  10. How shopping agents work

  11. Similarly to meta-search engines: ‘screen-scraping’ • They parse HTML pages and look for specific information • They rely on regularities in the layout of web pages • Navigation regularity • Uniformity regularity • Vertical separation regularity

  12. Limitations and issues Current techniques for extracting information rely on syntax: • Although the information required is stored in machine-processable and well-structured format, agent developers have no access to this information • Heuristics are ad-hoc, difficult and time-consuming to develop and prone to errors • The resulting systems are cumbersome and vendor specific • New vendors cannot be discovered and queried at runtime • Only able to retrieve limited information and comparisons are usually made on price alone – vendors vendors do not like that, other attributes may be important (guarantee, service etc.) • The information retrieved may be inaccurate

  13. Shopping agents make commissions in three ways • For each hit made to the vendors site • For sales that result from clickthrough purchases • For a favourable placement on the shopping agent’s recommended lists • Recommendation offered may therefore be biased • There may be discrepancies between reported and listed prices due to commissions • Such shopping agents may create the false impression that the best deal has been found

  14. From the vendors’ perspective • Although shopping agents improve their visibility, they also put their products next to those of competitors • To be competitive a vendor may have to reduce its profit margins

  15. Shopping agents and Web services Web services can be used as gateways to the vendors’ web sites

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