CHAPTER 4 MARKETING INFORMATION

Definition and Use of Information Databases in Marketing Types of Data Marketing Research Process

DEFINITION OF INFORMATION Data that is judged useful by a decision maker Buyer Seller Influencer

USE OF INFORMATION The “me” information age Information is power Information is not neutral Information can be used strategically

THE “ME” INFORMATION AGE “I can now work and communicate from anywhere to anywhere, with anything at anytime, and with anybody.” Cell Phones s Internet

STRATEGIC INFORMATION Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question

STRATEGIC INFORMATION Are we going in the right direction?

DATABASES IN MARKETING Scanning Data Customer Data Big Data

SCANNING DATA EXAMPLES Walmart Randalls Catalina

CUSTOMER DATABASE EXAMPLES Health Valley Foods Barchetti Retail Shop Bella Wedding Pictures

BIG DATA Sellers searching for useful information contained in large data bases

BIG DATA EXAMPLES Ceasars Entertainment Zynga United Parcel Service Richmond Police

TYPES OF DATA Secondary Internal Data Secondary External Data Primary Observation Data Primary Questioning Data

SECONDARY INTERNAL DATA Accounting Data Financial Data Sales Data Supply Chain Data

SECONDARY EXTERNAL DATA Census Data Web Courthouse Hoovers

PRIMARY OBSERVATION Observing something without any questioning or interviewing behavior

PRIMARY OBSERVATION EXAMPLES Retail price shopping Satellite images Observing kids play with toys Traffic counters

PRIMARY QUESTIONING DATA Gathering data through a variety of interviews and questions

PRIMARY QUESTIONING EXAMPLES Personal interviews Telephone interviews Self-questionnaires Focus group Interviews

FOCUS GROUP INTERVIEWS Advantages: – Inexpensive – Fast to collect data Disadvantages: – May not represent target market – Cannot measure sampling error

FOCUS GROUP EXAMPLES Interview focus groups in person Interview focus groups online Interview focus groups in a teleconference

MARKETING RESEARCH PROCESS WHAT INFORMATION IS NEEDED? DATA COLLECTION DATA ANALYSIS

MAJOR SAMPLE CHOICES Random sample Stratified sample Quota sample Convenient sample

RANDOM SAMPLE EXAMPLE All 3,000 Bauer students have an equal chance if being picked in a sample of 200 Bauer students

STRATIFIED EXAMPLE All 3,000 Bauer students are divided into subgroups like: Undergraduate vs. graduate Different majors All 3,000 students have an equal chance of being picked from the subgroups, which add up to 200 students.

QUOTA SAMPLE EXAMPLE All 3,000 Bauer students are divided into subgroups like: Undergraduate vs. graduate Different majors The 200 students picked in the sample are not randomly picked from the subgroups but by quotas.

CONVENIENT SAMPLE EXAMPLE All 3,000 Bauer students are eligible to be picked in the sample of 200 students. The 200 students picked in the sample are not randomly picked from the 3,000 Bauer students.

SAMPLING BIASES Collection Bias Response Bias Question Wording Bias

COLLECTION BIAS Frame error Non-contact Interviewer Error

RESPONSE BIAS Refusal to answer questions Respondent bias

QUESTION WORDING BIAS Ability to answer question Willingness to answer question Loaded question