Chapter 10 Flashcards
(35 cards)
5 steps to to the marketing research process
Define objectives and research needs Design research Data collection process Analyze and develop insight Action plan and implementation
Factors marketers want to know before embarking on a research project
Will research be useful?
Will it provide more than we already know?
Will it reduce uncertainty ?
Is top management commuted to the project?
Should marketing research project be large or small
Step 1 research process
What problem needs to be solved.
Remember it must be clearly defined since research is expensive!!
Step 2 research process
Design the research and Identify the data needed and determine research necessary to collect it
Step 3 research process
Collect the data which can be primary or secondary
Secondary data
Information that has been collected prior to research
Primary data
Collected to address specific research needs
Example of secondary data
Mcdonalds going to ACNielson for data on ingredient price sales figures and growth
Example of primary data
Survey from Mcdonalds on its performance asked to its customers
Step 4 research process
Analyze the data and develop insights generate meaningful info
Data
Raw numbers or factual information that on their own provide little insight
Information
Results from organizing analyzing and interpreting data
Step 5 research process
Action plan/ implementation
Analyst presents results to decision makers
Drawbacks of secondary data
Not specific or timely enough to solve manufacturers needs May not be relevant to question at hand
Syndicated data
Is secondary data which I available for a fee ample ACNielson provides sales of foods for a ll types of stores
Scanner data
Obtained at checkout countries through UPC code
Panel data
Collected from a group of consumers organized into panels over time ( focuses on individual store chain etc)
Data warehouse
Cache of customer information and purchase history
Data mining
Uses statistical analysis tools to uncover previously unknown patterns in data or relationships among variables
Churn
Number of participants who discontinue use of a service divided by average number of total participants
Qualitative data
Used to understand interest through broad open ended responses more informal than quantitative research
Examples obese ration, social media in depth interviews focus groups etc
Quantitative data
Structured responses good for statistics provides info needed to confirm insights and generate hypothesis
Example scanner data panel data specific experiments
In depth interviews
Trained researchers ask questions listen to and record the answers and pose additional questions to clarify on a particular issue
Focus group interviews
8 to 12 people come together for intensive discussion
