Chapter 4 Managing Marketing Information

Download Report

Transcript Chapter 4 Managing Marketing Information

Chapter 4
Managing Marketing Information
Professor Marshall
Queens College
Coca-Cola’s Marketing Blunder
In 1985, marketers thought they were listening to
their target market. They noticed that they were
losing market share to Pepsi and they conducted
taste tests to develop their new formula.
On April 23, 1985, Coca-Cola stopped producing
old Coke and created a new Coke with a
sweeter taste.
Coca-Cola
fouled up their research. They
Angry customers
panicked,
filling their
focused
only on Taste.
The company
ignored
basementsfeeling
with old
Cokethe
and
consumers’
about
oldthreatening
Coke.
lawsuits.
3 months later, Coca-Cola brought back the old
formula calling it Coca-Cola Clasic.
Luckily, Coca-Cola had quick reaction time.
The Importance of Marketing
Information
Companies need information about
their:
– Customer needs
– Marketing environment
– Competition
Marketing managers do not need
more information, they need better
information.
Marketing Information System
An MIS consists of people,
equipment, and procedures to gather,
sort, analyze, evaluate, and distribute
needed, timely, and accurate
information to marketing decision
makers.
The MIS helps managers to:
1. Assess Information Needs
2. Develop Needed Information
3. Distribute Information
Assessing Information Needs
A good MIS balances the information
users would like against what they really
need and what is feasible to offer.
Sometimes the company cannot provide
the needed information because it is not
available or due to MIS limitations.
Have to decide whether the benefits of
more information are worth the costs.
Developing Marketing Information
Internal Databases: Electronic collections of
information obtained from data sources within the
company.
–
Information in a database can come from many sources.
Operations tracks shipments and inventory, sales tracks
competitor activities, marketing has customer
demographics and buying behavior, customer service
contains information on customer satisfaction.
Marketing Intelligence: Systematic collection
and analysis of publicly available information
about competitors and developments in the
marketing environment.
–
Used to improve strategic decision making
Marketing Research: Systematic design,
collection, analysis, and reporting of data relevant
to a specific marketing situation facing an
organization.
–
Used to help understand customer purchase behavior
Customer Relationship Management
Many companies utilize CRM
–
–
–
Capture customer information from all sources
Analyze it in depth
Apply the results to build stronger
relationships.
Companies look for customer touch points
(every contact between company and customer).
CRM analysts develop data warehouses
(centralized database) and use data
mining (algorithms designed to detect
patterns in the data) techniques to find
information out about customers.
Marketing Research Process
Defining the
problem &
research
objectives
Developing the
research plan
for collecting
information
Implementing
the research
plan – collecting
& analyzing the
data
Interpreting &
reporting the
findings
Problem: Losing market share to Pepsi. We must research the taste preferences of
consumers.
We should collect taste preference information through blind taste tests.
Conduct blind taste tests in various settings aimed at various consumers
Data finds that consumers prefer the sweeter taste of Pepsi.
Based on the findings, Coca-Cola decides to produce a sweeter New Coke,
and remove the old Coke from its product line.
Defining Problem & Objectives
Exploratory Research:
–
Gather preliminary information that will help define
the problem and suggest hypotheses.
Descriptive Research:
–
Describes things (e.g., market potential for a
product, demographics, and attitudes).
Causal Research:
–
Tests hypotheses about cause-and-effect
relationships. Example: Would a 10% decrease in
tuition at a private college increase enrollment
enough to offset the decrease in tuition?
Developing the Research Plan
Includes:
–
–
–
Determining the exact information needed
Developing a plan for gathering it efficiently
Presenting the written plan to management
Outlines:
–
–
–
–
–
Sources of existing data
Specific research approaches
Contact methods
Sampling plans
Instruments for data collection
Developing the Research Plan:
Campbell Soup
Campbell wants to conduct research on how soup consumers would
react to the introduction of new bowl-shaped plastic containers
which would allow consumer to heat soup in the microwave without
adding anything and without a need for dishes.
They need to research the following information:
Demographic, economic and lifestyles of current soup consumers
Consumer usage patterns for soup (where, when, how much)
Retailer reactions to new packaging
Consumer attitudes toward new packaging
Forecasts of sales for new and old packages
Next Step: determine where/how to gather this information and all associated costs.
Present this in a written proposal.
Gathering Secondary Data
Information that already exists somewhere
–
–
–
Internal databases
Commercial data services: www.acneilson.com
(data on household purchasing), www.dnb.com
(information on companies)
Government sources: www.sec.gov (financial
data on US corporations), www.census.gov
Available more quickly and at a lower cost
than primary data.
Must be relevant, accurate, current, and
impartial.
See page 116 for more external information sources.
Primary Data Collection
Information collected for the specific
purpose at hand.
Must be relevant, accurate, current, and
unbiased.
Plan for Primary Data Collection Must
determine:
–
–
–
–
Research approach
Contact methods
Sampling plan
Research instruments
Developing the Research Plan:
Campbell Soup
They need to research the following
information:
Demographic, economic and lifestyles of
current soup consumers
Consumer usage patterns for soup
(where, when, how much)
Retailer reactions to new packaging
Consumer attitudes toward new
packaging
Forecasts of sales for new and old
packages
Secondary Data
Secondary Data
Primary Data
Primary Data
Secondary Data
Observational Research
The gathering of primary data by
observing relevant people, actions, and
situations.
Ethnographic research:
–
Observation in “natural environment”
Mechanical observation:
–
–
–
–
People meters – records tv shows watched
Checkout scanners – record shoppers’
purchases
Galvanometer – detects sweating
Eye Cameras – study respondents’ eye
movements
Survey Research
Most widely used method for primary data
collection.
Approach best suited for gathering
descriptive information.
Can gather information about people’s
knowledge, attitudes, preferences, or
buying behavior.
Survey Contact Methods
Personal can mean
individual interviewing or
focus groups (6-10 people
who talk about product)
Mail
Telephone Personal Online
Flexibility
Poor
Good
Excellent
Good
Qty of data that
can be collected
Control of
interviewer effects
Control of sample
Good
Fair
Excellent
Good
Excellent Fair
Poor
Fair
Fair
Excellent
Fair
Poor
Speed of data
collection
Response Rate
Poor
Excellent
Good
Excellent
Fair
Good
Good
Good
Cost
Good
Fair
Poor
Excellent
Choosing the Sample
Sample – segment of the population
selected to represent the population as a
whole.
Requires 3 Decisions:
–
Who is to be surveyed?
Sampling unit
–
How many people should be surveyed?
Sample size
–
How should the people in the sample be
chosen?
Sampling procedure
Types of Samples
Probability Sample
Simple Random Sample
Every member of the population has a
known and equal chance of selection.
Stratified Random
Sample
Cluster (area) Sample
Population is divided into groups (ex age
groups) and random samples are drawn
from each group.
Population is divided into groups based on
location and samples are drawn from the
groups.
Nonprobability Sample
Convenience Sample
Researcher selects the easiest population
members from which to obtain information.
Judgment Sample
Researcher uses his or her judgment to
select population members who are good
prospects.
Quota Sample
Researcher finds a prescribed number of
people in each of several categories.
Primary Data Collection
Questionnaires:
–
–
What questions to ask?
Form of each question?
Closed-ended – include all possible answers (multiple
choice)
Open-ended – allow respondents to answer in own words
–
–
Wording?
Ordering?
Likert Scale
One of the most popular closed-ended formats, widely used in survey
research, particularly in measuring attitudes, beliefs and opinions.
The basic idea here is to:
write the item as a declarative sentence and;
then provide a number of response options, or choices, that would
indicate varying degrees of agreement with, or endorsement of, that
sentence.
Example:
Three meals a day is essential to a healthy lifestyle.
1
2
Strongly Moderately
Disagree Disagree
3
Mildly
Disagree
4
5
6
Mildly Moderately Strongly
Agree Agree
Agree
Please note, in the above example, that the "item" to be evaluated
consists of a declarative sentence. Thus, it already states a 'position'
and 'direction' of attitude. The respondent is then asked to circle the
direction and extent (intensity) of his/her agreement (or
disagreement) with that "position" sentence.
Implementing the Research Plan
Collecting the data
–
Most expensive and subject to error
Processing the data
Analyzing the data
Analyzing the Data
Simple Tabulation – count the occurances
of each variable independently of other
variables
Cross Tabulation – divide the sample into
sub-groups to show how the variable
varies from one subgroup to another
Simple Tabulation
Answer Choice
Question 1
Question 2
Question 1
Question 2
1
5
19
2
8
7
3
10
4
4
11
2
5
14
21
6
16
11
Total Respondants
64
64
PERCENTAGE OF TOTAL
8% 13% 16% 17% 22% 25%
30% 11% 6% 3% 33% 17%
Question 1
1
2
3
4
5
6
1 = Strongly Disagree, 2 = Moderately Disagree, 3 = Mildly Disagree, 4 = Mildly Agree, 5 = Moderately Agree, 6 = Strongly Agree
Cross Tabulation
QUESTION 1
Answer Choice
1
2
3
4
5
6
Men
4
7
8
6
7
1
PERCENTAGE OF TOTAL 12% 21% 24% 18% 21% 3%
Women
1
1
2
5
7
15
PERCENTAGE OF TOTAL 3% 3% 6% 16% 23% 48%
Question 1 - MEN
Total Respondants
33
31
Question 1 - WOMEN
1
1
2
2
3
3
4
4
5
5
6
6
1 = Strongly Disagree, 2 = Moderately Disagree,
3 = Mildly Disagree, 4 = Mildly Agree, 5 = Moderately Agree, 6 = Strongly Agree
Interpreting and Reporting Findings
Interpret the findings
Draw conclusions
Report to management
Experimental Research
Tries to explain cause-and-effect relationships.
Involves:
–
–
–
–
selecting matched groups of subjects,
giving different treatments,
controlling unrelated factors, and
checking differences in group responses.
Example: before adding a new product, to its menu, Taco Bell might
use experiments to test the effect of sales on two different prices it
might charge.
Analyzing the Data
Hypothesis Testing
– Uses Regression Analysis to Interpret the
results
Exmaple: Taco Bell might take the data from the experiments designed to test the effect
of sales on two different prices.
The company would run a regression on the data to determine if the new price had a
significant effect on sales.
Original Price
New Price
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Taco Supreme Meal
Taco Supreme Meal
Sales at Old Price
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
200
179
154
320
228
207
189
289
182
221
198
178
245
189
167
183
200
196
118
149
$4.98
$5.48
Sales at New Price
190
170
146
376
217
197
180
275
173
210
188
169
233
180
159
174
221
186
112
142
Regression Output
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.967420566
R Square
0.935902551
Adjusted R Square
0.932341582
Standard Error
14.39127822
Observations
20
ANOVA
df
Regression
Residual
Total
Intercept
Sales at Old Price
1
18
19
SS
54432.857
3727.959999
58160.817
MS
F
Significance F
54432.857 262.8224086
3.4894E-12
207.1088888
Coefficients Standard Error
t Stat
P-value
-38.22687925
14.72791383 -2.595539307 0.018269864
1.167319034
0.07200429 16.21179844 3.4894E-12
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
-69.16910196 -7.28465654 -69.16910196 -7.28465654
1.016043518 1.318594551 1.016043518 1.318594551
Interpretation: we are 98% confident (1-p value) that there is a relationship between
old sales (x) and new sales (y) data.
To estimate new sales, we would formulate the following equation:
-38.23 + (1.17 * Sales at the Old Price)
If sales at the old price averaged 200, we would estimate new sales by:
-38.23 + (1.17 * 200) = 195.24
Making the Decision
Given Estimated Sales at the New Price,
is the price hike worth it?
Judging by our research estimates, we
would reduce sales by 5 if we implement
the new price.
We sold 200 at $4.98 = $996.00
The new price adds $0.50 per sale, so we
would sell: 195 at $5.48 = $1,069.90
Making the Decision
Assuming there are no other costs (or that
the other costs don’t outweight the
profits)…
We would increase revenue by: $73.90 if
we increase the price.
So – YES we should make Taco Supreme
Meals $5.48.
Video Case
Burke, Inc.
(9 minutes)
Applying Knowledge - Improving Decisions
Burke is one of the premier international research and consulting firms in the
world. For nearly seven decades, Burke has helped manufacturing and service
companies understand and accurately predict marketplace behavior. Burke's
employee owners add value to research and consulting assignments by
applying superior thinking to help clients solve business problems.
http://www.burke.com/about/
Thoughts
Can you name some new growing trends?
What products or services might be in high
demand to fit those trends?
What jobs will grow to suit those trends?
Video Case
Intel
(15 minutes)
http://www.capstonevideo.com/rpm_wvx/capstone_intel.wvx
Thoughts
Marketing Research was used at every
stage in developing the Intel brand.
– Deciding on an advertising theme and jingle
– Developing a product name
– Developing products geared toward the uses
of customers all over the globe