1. MARKETING RESEARCH AND MARKETING INFORMATION SYSTEMS
Marketing Information Systems (MkIS)
Primary vs. secondary data
Advantages and disadvantages of each
Marketing research tools

2. Learning Objectives Identify the costs and benefits of research
Identify the uses of both primary and secondary market research
Identify the respective advantages and disadvantages of different primary research methods
Identify potential research method problems that can lead to misleading or incorrect conclusions.
Determine the proper sequence of research activities.

3. Marketing Research An “investment” to reduce uncertainty
Can help guide decisions on
Whether to enter
Product characteristics
Promotional strategy
Positioning
Must weigh costs and benefits of research
Money
Time spent
No perfect method—tradeoffs between methods

4. Marketing Information Systems (MkIS)
Set of procedures and methods for regular collection and analysis of information for marketing decisions
Databases (internal information—e.g., sales volumes)
Market research
Primary
Secondary

5. Data Mining
Processing of vast amounts of data to find relationships between variables—e.g.,
Items frequently purchased together  “strategic adjacencies” (items placed together in retail setting)
Seasonal patterns in sales
Customer segments

6. Some Primary Research Methods
Surveys
Experimentation
Observation
Focus groups
In-depth interviews
Projective techniques
Physiological Measures
Online research
Scanner data
Conjoint Analysis
Hybrid Methods
Sentiment Analysis

7. Primary Research Methods
Exploratory Methods
Observation (can be more definitive with larger sample sizes and focus on specific behavior)
In-depth interviews
Focus groups
Projective techniques
Precision Methods
Experiments
Surveys
Panel
Scanner data

8. Choosing a Primary Research Method
Can the respondent answer accurately? (What someone consciously believes may differ from “deeper” opinions; beliefs about hypothetical products may not be well developed.)
Does the question involve OPINIONS or BEHAVIOR?
OPINIONS
BEHAVIOR NO
Can the relevant behavior be observed in the customer’s natural environment?
PROJECTIVE
METHODS
YES
EXPLORATORY or PRECISION research?
YES NO
SCANNER DATA (e.g., brand choice, impact of advertising, previous purchases, competing brands, demographics)
EXPERIMENTATION (determine causality—e.g., impact of product design, advertising message)
EXPLORATORY
PRECISION
OBSERVATION (e.g., how long does the shopper spend? What does he or she look at? Is anyone else involved?)
PHYSIOLOGICAL (e.g., determine reactions, attention, arousal)
INDIVIDUAL INTERVIEWS
SURVEYS
FOCUS GROUPS
SENTIMENT ANALYSIS

9. Surveys Forms Planned questions
Mail (self-administered, single time)
Mail panel (self-administered, multiple surveys administered over time)
Telephone (from central location)
Mall Intercept
Computer/Internet
Planned questions
Open-ended
Closed-ended
Need large sample sizes for precise conclusions
Small samples will have very large standard errors and thus large margins of error
E.g., Presidential polls (with only two choices) require a little more than n=1000 to get results accurate to +/- 3%.
SURVEY COSTS:
USUALLY LOW

10. Some Overall Issues in Market Research?
Do people actually do what they say (and believe) they will do? Often not!
Is A actually causing B, or is B causing A, or is some third variable causing both? This is often difficult to sell!
How much data do we need to make precise conclusions? A sample of n=30 will usually not cut it! Larger sample sizes are usually needed to make reliable decisions!
Will respondents interpret our questions the way they were intended? Often not!

11. Characteristics of Some Problematic Questions
Difficult to answer—respondent may not have knowledge needed
Amounts spent annually on specific product categories may not be known
Sensitive (embarrassing)
Two in one—e.g., “On a scale from 1 to 10, how fast and reliable are Microsoft programs?”
Leading questions—giving the feeling of the “desired” response
“Do you agree that soft drinks with sugar are bad for you?”
Non-exhaustive question
Non-mutually exclusive answers

12. Continuum Questions
Questions rating the degree of a characteristic (e.g., agreement or product usage) tend to be more effective than binary “Yes/No” questions
E.g.,
Strongly Neither Strongly
Agree Agree Agree Nor Disagree Disagree
Disagree

13. Continuum Scales
Rather than asking binary (e.g., “Yes” vs. “No”) questions, it is usually better to ask about a matter of degree or extent
E.g., “On a scale from 1-10, with 1 being ‘Not all interested’ and 10 being ‘Extremely Interested,’ how interested are you in fashion?
Asking simply “Yes” or “No” on “Are you interested in fashion?” would result in people with very little actual interest potentially answering affirmatively

14. Some Areas Suited for Continuum Ratings
Interest
Purchase likelihood
Satisfaction/ Dissatisfaction
Brand loyalty
Price sensitivity
Knowledge
Experience
Involvement
Decision control
Frequency or level of use
Awareness
Information search
Personality traits
Variety seeking

15. Online Surveys Conditional branching—direct skip to relevant question
Quality of response
Time pressures
Willingness to write out answers or respond to multiple closed-ended questions
Willingness to read and follow instructions is limited
Reliability and browser compatibility issues

16. Conditional Branching
Traditional surveys: Have you bought a new car during the last six months? If not, please skip to Question 11.
Conditional branching: Respondent will be taken to the appropriate question according to answer
Customization of questions
E.g., consumer lists three brands  subsequent questions ask about these specific brands by name

17. Experimentation
Does it make a difference if subjects (i.e., consumers, people) are treated one way or another way in terms of some outcome (e.g., likelihood of purchase?)
Will consumers rate a red car as more exciting but a blue one as more reliable?
Are those who hear German (as opposed to French) music more likely to buy beer?
Will students who are told to expect an essay exam do better than those told to expect a multiple choice exam even if everyone ultimately takes a multiple choice exam?

18. Experimentation
Testing what people actually do rather than way they say or think they will do
Useful in trying to determine causation (e.g., does a product sell more if the packaging is red rather blue?)
Possible to
Control for factors that are not equal in real life (e.g., If those who pay restaurant checks with credit cards are more likely to be reimbursed by their employers, it is not clear if the credit use was the cause of the higher tip)
Test and rule out competing explanations (subject to some caveats)—e.g., does texting while driving cause accidents because (1) eyes are removed from the road, (2) attention is diverted to the conversation, or (3) a combination

19. Two Basic Types of Experiments
Between-subject: Different groups of people are treated the same except for the variable or variables manipulated
E.g., One group shops in simulated store in which a credit card logo is displayed; the other group shops in the same simulated store but the credit card logo is removed
Within-subject: The same individual is treated differently at different times (e.g., at time 1 is given cola drink that includes vanilla and one without at time 2)
Subjects are usually counter-balanced to rule out order effects (1/2 receives treatment A first and then B, the other half receives B, then A)

20. Experimentation
Subjects in different groups are usually treated differently
E.g., for some, “target” product is given better shelf space
E.g., some get coupon
Can help isolate causes
Subject is not biased by questions—does not know how others are treated
Everyone is treated the same way, so nothing is being manipulated for comparison
EXPERIMENT COSTS:
HIGH

21. My Simulated Store…
A shopper in the everyday low price condition…

22. Ash’s Instant Coffee Study
GROCERY SHOPPING LIST
Ground beef
Potatoes
Apples
Flour
Sugar
Laundry detergent
Instant coffee
6 cups of yogurt
Paper towels
Bananas
GROCERY SHOPPING LIST
Ground beef
Potatoes
Apples
Flour
Sugar
Laundry detergent
Ground coffee
6 cups of yogurt
Paper towels
Bananas
Respondents were asked to describe their impressions of a housewife based only on her shopping list. These shopping lists differ only on one item.

23. Definition
Confound: An illusion of one variable causing another because of correlation between two variables
E.g., does having more toys cause children to be more intelligent?

24. Some types of confounds
Actual cause
Illusory cause B
A appears to cause B but it is actually B that causes A
Examples:
Diversification and profitability. Diversified firms tend to have higher profit levels. This may be because more profitable firms need to find ways to re-invest profits rather than because diversification causes profitability
Sales of a brand of soda are higher during weeks of heavy advertising. However, advertising is allocated when the stakes are greatest (e.g., during holidays and summer months). Thus, anticipated sales actually cause advertising. A
You will NOT be asked to draw these diagrams on the exam or to explain the specifics of the different types of confounds.

25. Some types of confounds
Actual cause
Illusory cause
A appears to cause B but both A and B are actually caused by C
Examples:
On the average, the more toys a child has, the higher his or her IQ. Both the number of toys and IQ may be caused by family resources such as income (providing for better nutrition and better education)
Individuals taking anti-depressive medication have higher rates of suicide than the general population. This is because those who take anti-depressive medication are more likely to be depressed. In fact, individuals suffering from depression are less likely to commit suicide than those with depression who do not take medication.
On the average, students who sit in the front of the class end up with higher grades. However, students choose where they sit. B C A
You will NOT be asked to draw these diagrams on the exam or to explain the specifics of the different types of confounds.

26. Some types of confounds
Actual cause
Illusory cause
Correlation
A appears to cause B but both A is correlated with C, with C ultimately causing B
Examples:
Sales of laundry detergent are higher during weeks when the brand is advertised. However, when the brand is advertised, there is always a price promotion (temporary price reduction). Most of the sales increase results from the price discount with a much smaller portion coming from advertising. The deeper the discount, the greater the sales.
Members of fraternities and sororities on the average have higher GPAs than people not in the Greek system. There may be some benefits to Greek membership causing higher grades, but members of the Greek system also tend to come from more privileged backgrounds. B C A
You will NOT be asked to draw these diagrams on the exam or to explain the specifics of the different types of confounds.

27. Confounds What is cause, what is effect, and what is coincidence?
Correlation is not necessarily cause
“Lurking” factors may be real cause
Does sitting in front of the room cause higher grades?
Does Prozac cause suicide?
Do fish-heavy diets cause stomach cancer?
Does fraternity/sorority membership cause higher grades?

28. Confounds: The Bottom Line
Correlation ǂ cause!
One can often make a plausible—even compelling—hypothesis of causation based on the observed relationship (but a hypothesis is still an open question)
If one variable appears to cause another
Both may be caused by a different variable
The causation may be the other way around (B causes A rather than A causes B)
The variable that seems to cause the other may be correlated with the actual cause (A does not cause C, but a is correlated with B and B causes C)
Experiments can be used to test for causality (with certain caveats) by controlling for potentially confounding variables

29. Some other influences on the relationship between variables
Restricted range: One population includes only a portion of another or the sample includes only a small portion of the population range—e.g.,
High school GPA school is a limited predictor of college GPA since students with higher high school GPAs tend to get into more competitive colleges
Among residents of Rancho Palos Verdes, household income does not predict dental health. In society as a whole, many people have difficulty paying for quality dental care, but most residents of Rancho Palos Verdes are relatively affluent
“Diluting” variables: Variables not considered “drown out” much of the effect of the variable of interest—e.g.,
Income is a limited predictor of spending. Although a certain level of income (or wealth) is needed to buy certain things (necessary condition), income is not a sufficient condition. Many high income individuals are rather stingy and many lower income individuals live above their means.
Ethnicity is a limited predictor of food preferences. Many Caucasians, African-Americans, Latinos, and Native Americans like raw fish.

30. (DEPENDING ON CODING AND
Observation
Looking at consumes in the field—e.g.,
Searching for product category area
Number of products inspected and time spent on each
Apparent scrutiny of labels or other information
Involvement of others
Behavior under limiting circumstances (e.g., time constraints)
OBSERVATION COSTS:
LOW TO HIGH
(DEPENDING ON CODING AND
ANALYSIS NEEDED)

31. Taste Tests Not experiments unless “Triangle” Measure
Two or more groups of people are treated differently (e.g., get different food version) or
The same person is being treated differently at separate times (e.g., half the participants receive new formulation, then current; half the participants receive in the opposite order)
“Triangle” Measure
Each respondent is given three items: One current, one new, and one duplicate of either old or new
Asked to identify the one that is different and explain why

32. (ESPECIALLY FOR THE AMOUNT OF INFORMATION COLLECTED)
Focus Groups
Groups of 5-12 consumers assembled
Start out talking generally about context of product
Gradually “focus” in on actual product
MOST
APPROPRIATE
AS EARLY
STAGE METHOD
Usually NOT the best approach. Should NOT be chosen as default research method!
FOCUS GROUP COSTS:
HIGH
(ESPECIALLY FOR THE AMOUNT
OF INFORMATION COLLECTED)

33. Focus Groups: Potential Uses
Identifying possible issues of concern with a new product
Probing complex issues where different factors and issues may affect opinions
Probing differences in perspectives among different groups
Very preliminary pilot testing of ideas
Identifying the actual language used by customers
Note that follow-up with more precise research methods is essential before firm conclusions can be made

34. Focus Groups: Composition
Members of each focus group should generally be similar to each other in terms of factors affecting comfort in speaking openly (e.g., age, gender, socio-economic status)
If the target market crosses such variables, different focus groups should be run
It may be helpful to run focus groups—even with customers otherwise demographically similar—in different cities

35. Focus Groups: Dynamics
The facilitator should
Allow the focus groups members to talk as much as possible to get at their views and perceptions
Gently attempt to steer the group in the desired direction
Probe and ask for elaboration when interesting ideas are raised
The focus group may involve an activity (e.g., cooking a meal) and/or sampling a product

36. Focus Groups: Caveats
Even with ten focus groups each with ten members, the sample size is only 100
Because of social influence, the opinions expressed by different members are not independent
Issues identified in focus groups should examined with more powerful methods using larger sample sizes (e.g., surveys, scanner data, experiments)

37. REMINDER
Focus groups are most useful for identifying issues that should be studied in more detail with more precise methods
Due to the small sample size and social influence on individual responses, it is difficult to generalize much from focus groups

38. In-depth interviews Structured vs. unstructured interviews
Generalizing to other consumers
Biases
Subtle, inadvertent feedback
IN-DEPTH
INTERVIEW COSTS:
HIGH

39. Projective Techniques
Getting at motivations that may not be consciously known— “Tell a story about this picture.”
Measurement of attitudes consumers are unwilling to express
It is easier to admit something embarrassing about someone else
Consumer discusses what other consumer might think, feel, or do
PROJECTIVE METHODS COSTS:
USUALLY HIGH IF PERSONAL INTERVIEWS OR EXTENSIVEINTERPRETATION IS NEEDED

40. Physiological Measures
Consumer bodily responses are watched at various phases of advertisement or other marketing exposure
Tracking of
Eye movements
For areas of focus
For attention, involvement
Heart rate
Skin conductivity
Brain waves
State of mind
Attention
PHYSIOLOGICAL
METHODS COSTS:
HIGH

41. Consumers rate several “profiles” (combinations of features)
Conjoint Analysis: Determining the Relative Importance of Product Attributes
Consumers rate several “profiles” (combinations of features)
Statistical analysis is used to “decompose” ratings into preferences 17

42. Example Car #1 Car #2 Gas mileage: 30 mpg Gas mileage: 20 mpg
Price: $18,200
Safety record: Average
Performance High
Reliability Poor
How would you rate car #1 overall
on a scale from 1 (Very poor) to
7 (Excellent?)
Car #2
Gas mileage: mpg
Price: $15,200
Safety record: Excellent
Performance Poor
Reliability Excellent
How would you rate car #2 overall
on a scale from 1 (Very poor) to
7 (Excellent?)
Each subject will evaluate several (usually 16+) combinations. A statistical technique determines the importance of each feature. 18

43. Conjoint Analysis: Advantages
Reveals ultimate preferences of consumers when competing influences exist
Able to predict desirability of combinations not actually explored
Can estimate contribution of each factor and assess its cost effectiveness
Will consumers pay $ to reduce the weight of a laptop computer by 2 lbs? 19

44. Conjoint Analysis: Disadvantages
May be difficult for subjects to rate many combinations
May need a large number of subjects for accurate measurement/sufficient precision
Must identify relevant attributes and levels in advance
Subject must know about product category (attributes must be meaningful) 20

45. Types of scanner data
Supermarket club. This includes purchases by the specific customer when shopping at the respective chain (assuming that the customer presents his or her card). Purchases at other locations are not counted. Demographic information may be of limited accuracy. Shoppers are often motivated to join by large discounts (often 20-30%). This is also a method of price discrimination. Members may be given individualized coupons for possible products of interest. Only available for grocery products.
Scanner data panels. In some communities, people can sign up to be part of a “panel.” Purchases at all local retailers are included (e.g. supermarkets, gas stations, drug stores, convenience stores). For a given customer, the database also includes TV viewing and demographics. Only available for grocery products.
Aggregated retail sales records. Records of sales volumes of products by UPC may be available from an assortment of retailers. This information is NOT tied to individual customer data and purchase history. This is available for more types of products.

46. COSTS: HIGH START-UP COSTS; POSSIBLE WITH DEVELOPED
Scanner Panel Data
Panel members in test communities agree to
Swipe a card prior to each purchase
Have purchases matched to
Demographic profiles
Media/coupon exposure
Promotional status of competing brands
Past purchases
Problems:
Aggregation over household
Aggregation bias--averages of disparate segments obscure!
Only available for grocery and some drugstore products
COSTS: HIGH START-UP COSTS;
LOW VARIABLE COSTS
POSSIBLE WITH DEVELOPED
ALGORITHMS
USUALLY LOW

47. Scanner Data Panel Research (Some of these variables are available for supermarket club data)
Purchase on occasion: Yes, no
Time since previous purchase
Previous purchases
Current price
Previous price
Current promotional status
Previous promotional status
Current display status
Previous display status
Display status of competing brands
Promotional status of competing brands
Coupon used: Yes, no
Coupon available: Yes, no
Coupon available for other brands? Yes, no
Amount of coupon
No. of ads seen by shopper
Ads seen for competing brands
“Split cable”
RECORDED
PURCHASES
TELEVISION
EXPOSURE
HOUSEHOLD
FILE
DEMOGRAPHIC
INFORMATION
ANALYSIS
Family size
Occupation
Income
Home ownership

48. SCANNER DATA BASED METHODS OF SEGMENTATION
Price responsiveness
Price sensitivity (impact of current price on the likelihood of purchase and/or quantity purchased). The brand elasticity is greater than the product category elasticity.
Deal proneness (propensity to switch to a non-preferred brand when such a competing brand price promotes through sales, coupons, or other form of discount). [This is one form of limited brand loyalty]
Purchase acceleration (“stocking up” when an item is on deal—sale and/or coupon)
Non-price based brand switching
Variety seeking [Another form of limited brand loyalty]
Accommodation of preferences of different household members
Shopping practices
Purchase frequency (within product category) (as distinct from price responsiveness measures listed above)
Package size preference
Store and/or retail chain loyalty

49. Sentiment Analysis Making sense of online postings in social media
Twitter
Photo sites (e.g., Instagram)
Blogs
Facebook
Tracking of massive amounts of data by computer (for large sample size and powerful predictions)
Machine (Computer) Interpretation of postings based on
Specific words and combinations of words used
Language use (pronouns, active vs. passive voice)
Context
Indicators of sarcasm, irony
Hashtags as brand identifier and emotion/evaluation
Heavily proprietary specific methods (firms develop methods and keep these secret)

50. Sentiment Analysis: Some Functions and Tools
Association of brands common to posts
Identification of probable poster characteristics (e.g., male/female, age) by language use
Vocabulary use of different consumer groups
Identifying expressions by opinion leaders
As a source of influence on large numbers of other consumers
As “early warning” of opinions that may emerge among consumers in general

51. Some Complications in Sentiment Analysis
Detection of irony, sarcasm, and humor in the specific context
Emergence of slang:
New slang terms
Context-specific slang terms
Slang used by limited consumer subgroup
Aggregation of responses from different group (e.g., demographic groups, positive/negative to the brand) making for meaningless average responses unless adjusted for group effects
Change of meaning by context (e.g., a consumer goes to Starbucks to improve a negative mood; thus, the negative affect should not be attributed to the brand)
Interpretation of “pseudo-hashtags” invented to be funny and not to be used across postings (e.g., #tastedkindofbad)
Integration of photo or video information into interpretation, especially if text only makes sense in the context of the images

52. Sentiment Analysis: Cross-Cultural Issues
Language structure and meaning (e.g., vague or precise word meaning, sequence of words, ambiguity of implicit objects/subjects)
Homonyms (words with same spelling but different meaning)
Customs of product category usage (e.g., “candy bar” vs. “chocolate bar”)
Slang and word meaning in context
Focus on self vs. others

54. The complete handout is in the market research summary notes on the course web site.

55. Choosing a Primary Research Method
Can the respondent answer accurately? (What someone consciously believes may differ from “deeper” opinions; beliefs about hypothetical products may not be well developed.)
Does the question involve OPINIONS or BEHAVIOR?
OPINIONS
BEHAVIOR NO
Can the relevant behavior be observed in the customer’s natural environment?
PROJECTIVE
METHODS
YES
EXPLORATORY or PRECISION research?
YES NO
SCANNER DATA (e.g., brand choice, impact of advertising, previous purchases, competing brands, demographics)
EXPERIMENTATION (determine causality—e.g., impact of product design, advertising message)
EXPLORATORY
PRECISION
OBSERVATION (e.g., how long does the shopper spend? What does he or she look at? Is anyone else involved?)
PHYSIOLOGICAL (e.g., determine reactions, attention, arousal)
INDIVIDUAL INTERVIEWS
SURVEYS
FOCUS GROUPS
SENTIMENT ANALYSIS