1. Lecture 3 MARK2039 Winter 2006 George Brown College Wednesday 9-12

2. Boire Filler Group Recap What are the four stages of data mining and who are the stakeholders What are the four stages of data mining and who are the stakeholders Data mining measures and metrics Data mining measures and metrics –Mean –Median –Mode –Standard Deviation Why are these above Statistics important in evaluating numbers Why are these above Statistics important in evaluating numbers

3. Boire Filler Group Recap Is the Average or Mean Appropriate in deriving Insight about a group,segment or sample behaviour. Is the Average or Mean Appropriate in deriving Insight about a group,segment or sample behaviour. Why do we need to look at how numbers vary? Why do we need to look at how numbers vary? What are some of the measures used to assess variation? What are some of the measures used to assess variation?

4. Boire Filler GroupRecap 2 distributions above. What do they mean and you would interpret the results. Both distributions have the same median and mean

5. Boire Filler Group Recap What is the problem here?

6. Boire Filler GroupRecap Consider the following two distributions... Consider the following two distributions...

7. Boire Filler GroupRecap For a binomial distribution, such as response, we must use a different formula. For a binomial distribution, such as response, we must use a different formula.

8. Boire Filler Group Recap What are Indexes. What are Indexes. Give me some examples. Give me some examples. Why are they important in the marketing world? Why are they important in the marketing world? What is the most common one used in the marketing world? What is the most common one used in the marketing world?

9. Boire Filler Group Lift Lift represents a relative comparison between two numbers. It is a type of index. How is normally used? Lift represents a relative comparison between two numbers. It is a type of index. How is normally used? Typically, it represents the number of a particular of a particular group divided by the average.( X1/average). Typically, it represents the number of a particular of a particular group divided by the average.( X1/average). Example: Example:

10. Boire Filler Group Recap-Lift Use relative measures and not absolutes Use relative measures and not absolutes The notion of “lift” should be the marketer’s key determinant of success The notion of “lift” should be the marketer’s key determinant of success Example Campaign 1 Campaign 2 Strategy 1 3% Resp. Rate 23% Resp. Rate Strategy 2 1.5% Resp. Rate 21.5% Resp. Rate Difference 1.5% Resp. Rate What is the key learning here?

11. Boire Filler Group Assignment 2

12. Boire Filler Group Assignment 2

13. Boire Filler Group Assignment 2

14. Boire Filler Group Assignment 2

15. Boire Filler Group Evaluating test results In database marketing, marketers are constantly asked what to conclude from their testing results. In database marketing, marketers are constantly asked what to conclude from their testing results. For instance, are the results of one strategy significantly different than another strategy. For instance, are the results of one strategy significantly different than another strategy. Let’s take a look at some examples. Let’s take a look at some examples.

16. Boire Filler Group Evaluating Marketing Test Two groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Two groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude?

17. Boire Filler Group Evaluating Marketing Test To determine this, you need to do statistical testing which essentially comprises three factors: To determine this, you need to do statistical testing which essentially comprises three factors: –Confidence level that you want –Actual standard deviation based on the lower sample size –Response Rate Or performance Rate –For our purposes, we will use a 95% confidence interval which essentially translates into 2 standard deviations around the mean

18. Boire Filler Group Evaluating Marketing Test Calculate the following confidence intervals at 95% Calculate the following confidence intervals at 95% –1% with a std. deviation of.1% –2% with a std. Deviation of.05% –5% with a std. Deviation of.5% –5% with a std. Deviation of.3% Let’s get back to the problem Let’s get back to the problem

19. Boire Filler Group Evaluating Marketing Test Two groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Two groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude?

20. Boire Filler Group Evaluating Marketing Test Calculate the standard deviation first using the sample with the lower qty-Strategy B. Calculate the standard deviation first using the sample with the lower qty-Strategy B. –Sq. root of (.02X.98)/5000=.00198 –95% confidence interval=.02+2*.00198 and.02-2*.00198=.02+2*.00198 and.02-2*.00198=.01604<=.02<=.02396..01604<=.02<=.02396. –Based on this result, what can you conclude between Strategy A and Strategy B

21. Boire Filler Group Evaluating Marketing Test Results Two other groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Two other groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Strategy Sample Size Response Rate A 1000 5.00% B 2000 3% Suppose the A becomes 3.3%. What would you conclude?

22. Boire Filler Group Evaluating Marketing Test Calculate the standard deviation first using the sample with the lower qty-Strategy A. Calculate the standard deviation first using the sample with the lower qty-Strategy A. –Sq. root of (.05X.95)/1000=.00689 –95% confidence interval=.05+2*.00689 and.05-2*.00689=.05+2*.00689 and.05-2*.00689=.03622<=.05<=.06378..03622<=.05<=.06378. –Based on this result, what can you conclude between Strategy A and Strategy B

23. Boire Filler Group Evaluating Marketing Test Results Two other groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Two other groups of cells have been tested for different communication strategies. Results are as follows. What would you conclude? Strategy Sample Size Response Rate A 1000 5.00% B 2000 4.0% Suppose B becomes 4.0%. What would you conclude?

24. Boire Filler Group Evaluating Marketing Test Results Calculate the standard deviation first using the sample with the lower qty-Strategy A. Calculate the standard deviation first using the sample with the lower qty-Strategy A. –Sq. root of (.05X.95)/1000=.00689 –95% confidence interval=.05+2*.00689 and.05-2*.00689=.05+2*.00689 and.05-2*.00689=.03622<=.05<=.06378..03622<=.05<=.06378. –Based on this result, what can you conclude between Strategy A and Strategy B

25. Boire Filler Group Evaluating Marketing Test Results Having done several of these tests, what will cause your confidence range to narrow Having done several of these tests, what will cause your confidence range to narrow –Large sample size –Smaller response rates

26. Data Review of Data

27. Boire Filler Group Types Of Data/Format Character-Level Data Character-Level Data Numeric Data Numeric Data Date Date Give me some examples Give me some examples In Data Mining, what do we have to do with all data before building a solution In Data Mining, what do we have to do with all data before building a solution

28. Boire Filler Group Data Format Examples Gender Gender Income Income Spending Spending Birthdate Birthdate Customer type Customer type How would you use gender,customer type, and birthdate in a data mining exercise How would you use gender,customer type, and birthdate in a data mining exercise

29. Boire Filler Group Data Transformation Gender Variable Gender Variable –Male=1, non male=0 –Female=1,non female=0 –What happens to missing values here? Customer Type Variable Customer Type Variable –Gold member=1,non gold member=0 –Platinum member=1,non platinum member=0 –Etc.

30. Boire Filler Group Data Transformation Birthdate Birthdate –Convert birthdate to age –Extract birthyear from birthdate field and substract from current year(i.e.2005-1954) Date of last Spending Activity Date of last Spending Activity –Create recency of last spend –Create tenure variable –How would this be done.

31. Boire Filler GroupData Discrete vs. index vs. continuous Discrete vs. index vs. continuous Discrete Discrete –Yes/No –On/Off Convert above type data to 1,0 type scenario Convert above type data to 1,0 type scenario

32. Boire Filler GroupData Index Type Data Index Type Data Could convert each customer type to binary value. But what would be more valuable way to convert or transform this variable?

33. Boire Filler GroupData Continuous data Continuous data –What are some examples What does it mean when we say that data is continuous? What does it mean when we say that data is continuous?

34. Boire Filler Group Data Type Looking at data as we have in the last number of slides, we can create what we call data categories: Looking at data as we have in the last number of slides, we can create what we call data categories: –Nominal –Ordinal –Interval

35. Boire Filler Group Data Categories Nominal variables are variables where the values do not represent any real order or magnitude of value. Nominal variables are variables where the values do not represent any real order or magnitude of value. Examples: Examples: –Gender –Product Category –Promotion Category

36. Boire Filler Group Data Categories Ordinal Variables represent fields where the values have some order Ordinal Variables represent fields where the values have some order Good examples are: Good examples are: –index-type variables –Model rank –Etc.

37. Boire Filler Group Data Categories Interval Variables represent fields where the actual values indicate order but also magnitude. Interval Variables represent fields where the actual values indicate order but also magnitude. –Income –Spend –Model Score What data category is the most granular? What data category is the most granular? Which category might you typically expect to be more powerful in a data mining exercise? Which category might you typically expect to be more powerful in a data mining exercise?

38. Boire Filler Group Data Usefulness When is Data Useful? When is Data Useful? –Few Missing values –Variable does not consist primarily of one value –Non-Numeric Data consists of too many values which cannot be properly grouped into more meaningful categories

39. Boire Filler Group Examples-Analytical Perspective What fields are useful and why?

40. Boire Filler GroupExamples Closer look at income Closer look at gender

41. Boire Filler GroupExamples Closer Look at Customer Type Closer Look at Customer Type Closer look at Product Type

42. Boire Filler Group Examples What variables would be useful here What variables would be useful here What would be the number of unique variables What would be the number of unique variables

43. Boire Filler Group Examples What variables would be useful here What variables would be useful here

44. Boire Filler Group Examples-Marketing Perspective A mortgage company is conducting a campaign to its high value customers. One of the key characteristics of value is high income which is self-reported at time of application. A mortgage company is conducting a campaign to its high value customers. One of the key characteristics of value is high income which is self-reported at time of application. As a marketer, how will you use this information and what do you need to consider?

45. Boire Filler Group Examples-Marketing Perspective An insurance company is marketing an insurance product to people over the age of 60. Listed below is a report indicating the distribution of age. An insurance company is marketing an insurance product to people over the age of 60. Listed below is a report indicating the distribution of age. As a marketer, how will you use this information?

46. Boire Filler Group Examples-Marketing Perspective An retail company has over 1000 product SKU’s. After investigation, it has been determined that the 1 st digit represents a broader product category. You have been asked to design the product layout for all stores. An retail company has over 1000 product SKU’s. After investigation, it has been determined that the 1 st digit represents a broader product category. You have been asked to design the product layout for all stores. As a marketer, how will you use this information?

47. Boire Filler Group Examples-Marketing Perspective What can be done here, if anything and what else can we consider in terms of using gender and income information ?

48. Boire Filler Group Examples-Marketing Perspective You have postal code information for each customer. You are asked to design customer reports by province.How would you do this? You have postal code information for each customer. You are asked to design customer reports by province.How would you do this?

49. Boire Filler Group Examples-Data Mining Perspective You have the following variables and values You have the following variables and values –Gender: ’M’:Male ‘F’:Female –Age: ‘B’: <20M ‘F’: 20M-40M ‘R’:40M-60M ‘S’:60M-80M ‘T’:80M-100M ‘Z’: 100M+ What must be done here? What must be done here?