Version 3/15/06
Support Material: Hackers, Hits and Chats
Keyterms: amazon; blog; collaborative filtering; cookies; IP address; one-to-one marketing; permission-based marketing; personalization; referrer URL; scalable; spam; target audience; web analytics


Technology has allowed marketers to narrow their focus from broad target audiences based on demographics and psychographics to more narrowly focused customer groups based on buyer behaviour. This can lead to one-to-one marketing, with the clear understanding of the profitability of the individual consumer. Key aspects of technology that has enabled this shift include the use of databases, and communications technologies such as the internet, scripting languages that serve personalized content from the databases, cookies that enable the web server to identify the customer and web analytics to analyze the customers on the site. Technology has enabled marketers to come full-circle. To return to the times when it was possible to know everything about your customers when you ran a store for your local customers, and knew, when they walked into the door, what they were likely planning to purchase. Clearly this level of customer intimacy was not scalable and was lost with the growth of mass marketing and mass media.

Database Marketing

Database Marketing allows a company to create personalized marketing communications to individual customers, based on data about that customer in the company's database systems. The data will cross reference biographical data with purchase bahaviour data and potentially purchase behaviour of similar customers (collaborative filtering). It can also include lists purchased from outside vendors (for targeting new prospects). It is a form of direct marketing such as e-mail marketing (either permission-based or spam); web presentation (for example; or catalog marketing via direct mail.

Database marketing is highly scalable, such that the more data an organization has about its customers, the more useful that data can be in terms of making accurate predictions for future purchases, assuming sophisticated data mining tools. Smaller companies will find the technology needed for database marketing somewhat cost prohibitive.

Data mining, an integral aspect of database marketing is the field of exploring the data to determine patterns that allow companies to make marketing offers to appropriate sets of customers. Examples might include attempting to identify customers that are considering leaving the company and moving their business to a competitor (churn) before they actually make that decision to leave, and the decision becomes unrecoverable. Once appropriate customers are identified, an offer can then be made that is attractive enough to retain the customers' loyalty, or at least reduce the attrition rate.

While it might seem obvious that identifying your best customers and rewarding them is the appropriate result of database marketing (there are plenty of loyalty programs designed to do this), it is more important to identify customers who may be at risk of leaving, and keeping them in the fold. Consider what the company means to the customer rather than what the customer means to the company., in 2000, was in trouble for allegedly pursuing a price discrimination tactic that proposed lower prices for new customers, thus 'penalizing' loyal customers. Amazon's explanation was it was testing different price levels to understand the demand patterns.

source: Database Marketing Defined; Data Mining and Privacy: A conflict in the making?; Data Mining and Customer Relationships; Customer Acquisition and Data Mining; Web sites change prices based on customers' habits; Amazon's old customers 'pay more'

Web Analytics

Web Analytics explores the data that is available from those browsing your web-site. That data can be used for a variety of reasons, including web redesign and analysis in conjunction with other data sets to provide richer customer data. The types of data that can be gatherered include: Free tools are available to add to a site (for example you can add sitemeter to your blog); and web hosts usually offer a pretty comprehensive package for their users ( offers Clear Admit: SmarterStats.)

Google Analytics; WebTrends

logfiles versus page tagging

issues that needed resolving; use of caching etc. therefore page tagging with cookies works


Cookies, which receive much attention from privacy advocates, are for the most part, benigh, and improve the web experience for the web user. When a user accesses a web-site that uses cookies, the site will add a file to the user's client machine that comprises a unique number. This number thus identifies the user should the user return to the site. The cookie is also necessary to identify the user as he / she navigates the site. Without this form of identification the site is not able to determine the referrer page that someone came from within the site, which would disable transactions that require multiple pages. Cookies are critical to the personalization of the web-site as the unique identifier can be used to match content from the site's database in terms of presention (think of your Amazon experience.)

Third party cookies are more of a concern from a privacy standpoint. Examples of use include the DoubleClick advertising network. DoubleClick places a piece of code on each of its network web-sites (there are thousands of sites that participate) and is thus able to track a user's visits to multiple sites, thus building a behavioural profile that it can then use in order to serve up the appropriate advertisements. This ability to understand browser behaviour can present issues if the information is used inappropriately. DoubleClick was heavily criticized for its purchase of Abacus, which would allow it to combine this data with names and addresses etc.