Agent Technology for e-Commerce

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

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

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

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

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

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

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

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

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

How shopping agents work

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

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

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

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

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

Agent Technology for e-Commerce