View stunning SlideShares in full-screen with the new iOS app!Introducing SlideShare for AndroidExplore all your favorite topics in the SlideShare appGet the SlideShare app to Save for Later — even offline
View stunning SlideShares in full-screen with the new Android app!View stunning SlideShares in full-screen with the new iOS app!
Data mining allows for the discovery of hidden patterns and relationships in large amounts of data.
Data mining uses powerful analytic technologies to quickly and thoroughly explore mountains of data, isolating the valuable, usable information — the business intelligence —
Ex. Data mining tells you which prospects are likely to become profitable customers and which are most likely to respond to your offer. ROI is increased by making offers to only those prospects likely to respond and become valuable customers.
Spyware is any technology that aids in gathering information about a person or organization without their knowledge. On the Internet (where it is sometimes called a spybot or tracking software ), spyware is programming that is put in someone's computer to secretly gather information about the user and relay it to advertisers or other interested parties. Often done via adware applications. Free spyware scan
Data mining refers to a wide range of techniques that look at underlying patterns or associations among elements within large data sets. These patterns are then used to form rules or guidelines for use in a wide range of marketing decisions. Ex. Insightful Miner demo*
Data mining tools can improve marketing management decisions such as:
segmentation and target marketing
improving sales force performance
customer relationship management (CRM)
and many others
CRISP-DM Figure: Phases of the CRISP-DM Process Model Cross Industry Standard Process for Data Mining: Project Overview
Through various algorithms , data mining software sorts through thousand of data points, organizes it, then summarizes complex relationships for the user.
Data mining software typically follows one of five different analytical approaches:
Forecasting via Trend Analysis, Reporting and OLAP
Reporting and Online Analytical Processing (OLAP)
Reporting (a.k.a. summary methods or baby stats) is one of the most basic, but extremely useful, techniques for data analysis.
Provides simple views of the data such as counts, sums, percentages, and averages.
Sample query: How many units did we sell last month?
OLAP (think multi-dimensional cross-tabulation) is useful because it provides “cubes” of “ reports” that can break down one variable by another.
Differs from traditional cross-tabs because it is interactive and you can “drill down” through the live reports to get more specific views of each cube (cell).
See SPSS example in class.
Traditional Cross-tab vs. OLAP Days per week * SUBHT Cross-tabulation Count 56 114 170 90 116 206 56 42 98 41 132 173 1 1 2 244 405 649 daily 2-3 times once Sunday 5 Total no yes SUBHT Total Days per week
Classification or profile generation uses data to develop profiles of different groups.
Can be used for segmenting and targeting, market evaluation, product management, etc.
Typically uses historical data to form rules that define groups. Those rules are then applied to new data to find similar groups.
Ex. Based on past results, a “hot prospect” is a person who has an advanced degree, earns $150K or more, has made three online purchases over the last month, and has purchased computer related equipment within the past year. Find person who fits that profile and you have a good prospect.