Business Sales Expert System

Intro As the Internet becomes more accessible, it is important to build more sophisticated systems on the web. These sophisticated web systems are often referred to as ‘lightweight’ systems. Web systems generally use dhtml, xml, javascript, php, coldfusion and other scripting languages.

Business Sales The goal of this project was to create a rule based system for sales people. The system is meant to help sales people show customers more relevant items, hoping to expedite the sale. We used a Jewelry Point of Sales System as our starting point. This helped restrict our domain space.

Asynchronous Javascript and XML (AJAX) For this project we used AJAX to develop the system and create a robust interface for making the recommendations. AJAX is a unique combination of Javascript and XML, allowing web pages to be dynamically changed without refreshing the page. Example:

Step 1 First we must select a customer from the database. For this project, I was able to get a sanitized version of the Jewelry System’s database. The database contains sales history, but minimal customer information. To Sanitize the database we shortened all the last names to 3 characters long and removed all personal information.

Step 2 Our rules are based on the customer’s sales history and what the customer has been recommended before. After selecting the customer we look at the customer’s sales history and select the types of Jewelry items they usually shop for. For example, if they usually shop for bracelets and necklaces, we will recommend items in those categories. In this step we extract the category types, metal types and price range the customer usually purchases within.

Step 3 We then take a Cross Product of Category Types and Metal Types, giving us a wider range of items to show the customer. We also make sure to show the customer things they haven’t seen in the last 3 months. 3 months was chosen based on the average frequency of customers to this Jewelry store.

Not Interested If the customer is not interested in the items shown, all they need to do is click on the ‘not interested’ button and new items will appear. These items populate the page following the same price, category and metal type restrictions as the beginning. At this point, if there are not more items within the specific search, the price range is widened by 25% on each end. This will continue to update until there are no more items to show.

Conclusion It has become clear to me that web systems are going to become a large force in the future of computer systems. Therefore, It is important to incorporate Artificial Intelligent techniques into them as early as possible. I hope to continue working with this system and create more rules to make the system an Expert. The site is hosted at username: 718 Password: project