Software Shopping Agents

ShopBots deliver on one of the great promises of electronic commerce and the Internet: a radical reduction in the cost of obtaining and distributing information. ShopBots can out-perform and out-inform even the most patient, determined consumers, for whom it would take hours to obtain far less coverage of available goods and services.

As the size of the World Wide Web grows, manual browsing for products and information becomes increasingly labor-intensive. You need a more effective method for shopping – you need a ShopBot.

What is a ShopBot?

The term is currently used for any Intelligent Agent or “Bot” that does automatic comparative price shopping on the Web. ShopBots automatically search the Internet to obtain information about prices, products, and services. They can provide one-click access to price and product information from numerous competing retailers, and they substantially reduce buyer search time. They provide a wider selection and greater availability, twenty-four hours a day, seven days a week.

ShopBots integrate Intelligent Agent technology, with databases of pricing and availability information provided by merchants from all around the world. Some compare more than 1,000,000 prices on 100,000 different products, and then they collate and sort the available information for the user, all within seconds. They provide consumers with easy online access to prices and descriptions of products and services. After only a few minutes visiting the site, the consumer is in a good position to make an informed choice before making a purchase.

One of the best features of some sites is that you can put “functionally similar” products side by side and easily compare characteristics and price. Some offer independent price comparisons and detailed product information both from online and traditional stores, all on the same site. In this way the consumer’s choice is greatly enhanced, and this has not been possible until now.

They also strip away many advertising and marketing elements by listing only summary information from both well-known, and lesser-known retailers. ShopBots therefore make it easier for consumers to locate and evaluate unbranded retailers, which makes it a great equalizer for Internet markets, putting small retailers on a more equal footing with their larger and more well known competitors. They are agents of economic change. ShopBots improve the process of obtaining information and they increase competition among sellers, therefore reducing the price of products and services. They create a future in which autonomous agents profoundly influence international markets.

How do you use a ShopBot?

Online shopping is easy. Just a click a couple times, type in basic information, and before you know it, your order is at your door. If you understand how to use a search engine, you can use a ShopBot. You type the name of a product that you are interested in, then the ShopBot seeks out merchants and prices, and returns a list. Most ShopBots are accessed by going to a website, and others are accessed through software that you need to download on your computer.

But, not all shopping ShopBots are created equal. A ShopBot’s specific technology is usually invisible to the user, who is simply presented with a list of online stores and prices. Some sites provide a more comprehensive set of services, including reviews of online stores, form-filling services, and buyer-feedback forums. Others let you negotiate with participating merchants for a better price.

How does it work?

ShopBot technology currently utilizes two different approaches for collecting data. The first approach periodically polls web sites and indexes their findings inside databases. When you access the ShopBot information is delivered quickly and presented as search results. A negative outcome of this method, however, is that the polled information may become dated.

The second approach uses technology that scans the Web in real time. Prices and in-stock information are more likely to reflect timely, accurate data. However, because the search is being undertaken in real time, search performance suffers. Without a third-party filter, the information returned also may be less reliable.

There are several types of ShopBot sites:

  1. Branded ShopBots are identified through a ShopBot website. A user goes directly to the ShopBot site, which has an easy, non-technical interface, and from there they launch a search.
  2. Portal ShopBots conduct searches under the disguise of a comparative shopper service for the major portals. They are found within the shopping channels of large portals.
  3. Retailer ShopBots conduct product searches on behalf of a user of a particular retailer web site, and they are marketed as a means to increase product offerings in their site, thereby attracting and satisfying more consumers.

And these can be sub-categorized by function:

  1. Product ShopBots recommend products based on past selections or constraints specified.
  2. Merchant ShopBots collect price and availability information.
  3. Negotiator ShopBots buy, sell, and bargain with other ShopBots based on user parameters. 

Many auction sites function as Negotiators. Users can automate their bidding by (secretly) setting the highest price they’re willing to pay within a certain time frame, then letting the software handle the interaction with other bidders. Users can either place each of their bids manually, or they can set up a bidding ShopBot to place their bids for them. Some sites encourage bidders to not only place an initial bid but also to set up “proxy bidding” in which any competing bid immediately will be met with a response up to the user’s maximum price.

Bidding services invite customers to send a price they would be willing to pay for a commodity service or good. The price competition is, however, constrained. There is no obvious way for consumers to learn what deals others have been able to secure, and the bidding services appear designed to discourage experimentation designed to find out the market-clearing price. Some require the consumer to commit to pay if the offer is accepted, and others do not, but they track the user’s behavior with a “reputation” number that goes up when a merchant’s acceptance of a bid results in a purchase and goes down when an accepted bid does not lead to a purchase. In this case, sellers will be more likely to respond to your requests if you have a high rating. The auction style creates an additional problem when you’re ready to commit to the purchase. We clicked on a link, only to find the auction over.

Conclusion

By examining current online usage patterns, it is evident that ShopBots represent added value for consumers and online merchants. Consumers are using the Internet for finding products and services, and ShopBots currently provide an efficient and informative way to search for these items. ShopBots also reduce the amount of search time for the consumer. Rather than searching three to five sites prior to making a purchase, consumers can simply insert their purchase specifications and let the ShopBot do the searching for them. When a buyer knows what they want, they value a ShopBot, because it provides a fast and efficient alternative to offline shopping. As time becomes more precious, ShopBots will become even more valuable.

Author: David Jurus