agent technology for e-commerce chapter 4: shopping agents maria fasli
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Agent Technology for e-Commerce
Chapter 4: Shopping Agents
Maria Fasli
http://cswww.essex.ac.uk/staff/mfasli/ATe-Commerce.htm
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Shopping agents make commissions in three ways
(i) For each hit made to the vendors site
(ii) For sales that result from clickthrough purchases
(iii) 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
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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