Marketing research and marketing information systems



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MARKETING RESEARCH AND MARKETING INFORMATION SYSTEMS

  • Marketing Information Systems (MkIS)
  • Primary vs. secondary data
    • Advantages and disadvantages of each
  • Marketing research tools

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.

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

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

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

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

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

Choosing a Primary Research Method

  • Does the question involve OPINIONS or BEHAVIOR?
  • Can the respondent answer accurately? (What someone consciously believes may differ from “deeper” opinions; beliefs about hypothetical products may not be well developed.)
  • OPINIONS
  • EXPLORATORY or PRECISION research?
  • YES
  • FOCUS GROUPS
  • SURVEYS
  • EXPLORATORY
  • PRECISION
  • BEHAVIOR
  • NO
  • PROJECTIVE
  • METHODS
  • 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)
  • PHYSIOLOGICAL (e.g., determine reactions, attention, arousal)
  • OBSERVATION (e.g., how long does the shopper spend? What does he or she look at? Is anyone else involved?)
  • Can the relevant behavior be observed in the customer’s natural environment?
  • NO
  • YES
  • SENTIMENT ANALYSIS

Surveys

  • Forms
    • 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

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

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.,
  • 5 4 3 2 1
  • Strongly Neither Strongly
  • Agree Agree Agree Nor Disagree Disagree
  • Disagree

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

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

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

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

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?

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

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)

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
  • EXPERIMENT COSTS:
  • HIGH
  • Everyone is treated the same way, so nothing is being manipulated for comparison

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.

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?

Some types of confounds

  • B
  • Actual cause
  • Illusory cause
  • A
  • 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.
  • You will NOT be asked to draw these diagrams on the exam or to explain the specifics of the different types of confounds.

Some types of confounds

  • B
  • Actual cause
  • Illusory cause
  • A
  • 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.
  • C

Some types of confounds

  • B
  • Actual cause
  • Illusory cause
  • Correlation
  • A
  • 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.
  • C

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?

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

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.

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)

Taste Tests

  • Not experiments unless
    • 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

Focus Groups

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

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

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

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

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)

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

In-depth interviews

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

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

Physiological Measures

  • Consumer bodily responses are watched at various phases of advertisement or other marketing exposure
  • Tracking of
    • Eye movements
    • Heart rate
    • Skin conductivity
    • Brain waves
      • State of mind
      • Attention
  • PHYSIOLOGICAL
  • METHODS COSTS:
  • HIGH

Online Research—Analysis of Customer Search Queries

  • Unmet demand—search for product not found on site
  • Message comprehension—comparison of search terms to media message
  • Consumer vocabulary
  • Feedback analysis
  • ONLINE SURVEY COSTS:
  • USUALLY LOW

Other Online Tools

  • “Click Stream Analysis:” Analysis of “clicking” path—how does the consumer get to a desired page or product?
  • Shopping cart analysis
  • COSTS: HIGH START-UP COSTS;
  • LOW VARIABLE COSTS
  • POSSIBLE WITH DEVELOPED
  • ALGORITHMS
  • USUALLY LOW
  • COSTS: HIGH START-UP COSTS;
  • LOW VARIABLE COSTS
  • POSSIBLE WITH DEVELOPED
  • ALGORITHMS
  • USUALLY LOW

Searching for Reports of Personal Experience

  • Sources
    • Blogs (blogsearch.google.com)
    • Photos (e.g., Flickr, Webshots, Picasaweb, Google image search)
    • Video (e.g., Youtube)
  • Cautions
    • May be “staged” or sensationalized
    • May represent what the writer or photographer wants to show
    • May be limited entries on certain “mundane” tasks such as dishwashing
  • Some issues
    • Joy, enjoyment
    • Decisions
    • Anxiety
    • Social setting and influence

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
  • Example
  • Car #1
  • Gas mileage: 30 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?)
  • 1 2 3 4 5 6 7
  • Car #2
  • Gas mileage: 20 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?)
  • 1 2 3 4 5 6 7
  • Each subject will evaluate several (usually 16+) combinations. A statistical technique determines the importance of each feature.

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 $500.00 to reduce the weight of a laptop computer by 2 lbs?

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)

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.

Scanner Panel Data

  • Panel members in test communities agree to
    • Swipe a card prior to each purchase
    • Have purchases matched to
  • 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

Scanner Data Panel Research (Some of these variables are available for supermarket club data)

  • TELEVISION
  • EXPOSURE
  • DEMOGRAPHIC
  • INFORMATION
  • ANALYSIS
  • RECORDED
  • PURCHASES
  • HOUSEHOLD
  • FILE
  • 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
  • Family size
  • Occupation
  • Family size
  • Income
  • Home ownership
  • No. of ads seen by shopper
  • Ads seen for competing brands
  • “Split cable”

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

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)

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

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

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

Choosing a Primary Research Method

  • Does the question involve OPINIONS or BEHAVIOR?
  • Can the respondent answer accurately? (What someone consciously believes may differ from “deeper” opinions; beliefs about hypothetical products may not be well developed.)
  • OPINIONS
  • EXPLORATORY or PRECISION research?
  • YES
  • FOCUS GROUPS
  • INDIVIDUAL INTERVIEWS
  • SURVEYS
  • EXPLORATORY
  • PRECISION
  • BEHAVIOR
  • NO
  • PROJECTIVE
  • METHODS
  • 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)
  • PHYSIOLOGICAL (e.g., determine reactions, attention, arousal)
  • OBSERVATION (e.g., how long does the shopper spend? What does he or she look at? Is anyone else involved?)
  • Can the relevant behavior be observed in the customer’s natural environment?
  • NO
  • YES
  • SENTIMENT ANALYSIS


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