Agent Technology for e-Commerce Chapter 4: Shopping Agents Maria Fasli .

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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How shopping agents work

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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

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Shopping agents and Web services

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