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Research Services

 

 

Focus Groups:  8-12 people with defined characteristics gather together for a discussion on the marketing issues, led by a trained moderator.  This method works well in the fact-finding stage, for generating ideas and for evaluating products or concepts, which need to be experienced or discussed.  The information gathered is qualitative and not representative of the entire population.  Proper sample definition and selection is critical.

 

Great Lakes Marketing offers focus group moderation as part of our full-service marketing research capabilities.  Lori M. Dixon, PhD, is an experienced and skilled focus group moderator.  Dr. Dixon is available to discuss your qualitative marketing research needs with you and make appropriate recommendations to answer your marketing information needs.

 

 

Intercept Interviews:  Shoppers, attendees, or visitors with specified characteristics are randomly selected and asked to participate in the personal interview.  Interviewing stations can be established in malls, stores, expos, trade shows—anywhere the target market can be found.  This works well when evaluating products or concepts which need to be experienced, when the concepts are complicated and visual stimulus helps, when several ideas or factors are prioritized or evaluated and when the location draws a “hard-to-reach” group of people.  Large samples can be very insightful, but are not totally representative of the entire population.  Intercepts are preferable over focus groups if individual opinions or evaluations are desired.

 

 

Telephone Interviews:  Most research that is descriptive in nature and does not need visual aids can be conducted by telephone.  With proper sampling and callback attempts, telephone interviewing provides quality information from random samples.

 

 

Mail Research:  Mail surveys were considered to be less expensive than telephone interviews and were popular for a while.  However, the increased postage costs, need for multiple mailings, postage paid returns and other respondent incentives have made mail research more expensive than telephone research for many samples.  Mail research may be effective if the target audience is well defined and committed to the research, if respondents who are geographically dispersed must see or use products and if the information is difficult to obtain. Usually, successful mail studies are used in combination with other data collection techniques (i.e., as a follow-up to telephone or personal interviews).  Panels can be developed for repeated mail contacts and longitudinal or multi-wave research.

 

 

Combinations & Creative Solutions:  Most research projects require a combination of data collection techniques.  An example would be that of a phone-mail-phone survey (or phone-fax-phone) in which the participants are first recruited through phone, mailed (or faxed) the survey and later called again to retrieve the responses.  Put the Great Lakes Marketing experience to work for you to design the most insightful and helpful research project.

 

 

Child-resistant (CR) Package and Closure Evaluations:  The Consumer Product Safety Commission (CPSC) requires that any product sold in the United States that can be toxic to children, must be packaged in a child-resistant package.  These include medicines, household chemicals and utility lighters.  These packages must meet federal guidelines for child safety and adult friendliness.  Great Lakes Marketing is an approved testing facility for testing packages according to government protocol that must meet federal regulations.  

Unique Product and Service Evaluation:  Great Lakes Marketing has been able to develop research plans for products so unique that we were able to assist the client in assessing critical issues before the product or service was publicly initiated.  Our senior project directors are experienced at thinking “out of the box” when trying to anticipate reaction to a new product or service. These have led to in-depth interviews to determine product effectiveness, in-home product placement, field and in-house product testing.  One-on-one communication is critical between the client and the project manager in these projects.  Flexibility is built into the process so that adjustments in collecting and evaluating data can be made as needed.

 

 

Database Design:  Some of our clients require research that involves complex data return or they need the data to be presented in a manner that allows others to access and use it effectively.  We have been able to design databases to meet our clients’ varying needs.  Whether you need a large database to be simplified, easily updateable or accessible and understandable for general use, let our expertise go to work for you.

 

 

Mapping:  Mapping is an effective method to present a geographic picture of the data collected during your research.  It can be used to show product or service saturation, or areas that need more attention.  These maps can be correlated to your data to paint a picture of the customers in those areas. This information can aid in planning future marketing efforts.

 

 

Product Testing:  Opinion Panel is our own extensive database of potential respondents just waiting to try your product and give their opinion.  Product testing can be done by placing the product in homes, inviting respondents to our office or by taking the product into the field.  Whether your product is food, cosmetic, personal use, mechanical, electronic or something else, we can help you discover how the public will receive it before you go to the expense of mass production.  We will offer data that will guide you in effectively making needed changes to successfully market your product.

 

 

Customer Satisfaction Studies:  Whether it’s products or services, Great Lakes Marketing can help you to access customer satisfaction and its impact on your bottom line.  Great Lakes Marketing has a wide variety of client types who have used customer satisfaction studies. We have extensive experience in the specialized areas of automotive, consumer products, medical and governmental services.  Studies that are repeated on a regular basis can be trended.

 

 

Online Data Collection:  Designing data collection formats that can be used for on-line data collection is becoming more popular as the computer becomes more common in the home and workplace.  It is now considered a viable, effective and often a lower cost method for accessing respondents for some research.  Great Lakes Marketing can help you determine if this is the best method to use for your research and then we can design and disperse your on-line questionnaire.

 

 

Mystery Shops:  In order for a company to evaluate its progression in terms of customer service, employee performance and customer satisfaction, mystery shopping is an ideal format to accomplish internal quality control and to give insight to the company from an outsiders’ perspective.  Mystery shopping can be done in any type of industry through highly customized scripts, surveys or scenarios.  We help you create a comprehensive evaluation to meet your needs, which you can modify on demand, and we use trained interviewers to “shop” as anonymous customers in order to evaluate your company’s performance as objectively as possible.  This process usually takes between a few minutes to over an hour, depending on the industry and intention of the client, in order to gain both positive and negative feedback. 

 

Thinking through the Research Process

 

Define the Research Objectives

Think about:

What information is needed?

What questions need to be answered?

What changes need to be measured?

What actions need to be monitored?

 

Ask yourself:

Do I know enough to define this carefully or am I still trying to fine-tune the issues?

 

 

Define the Sample

Think about:

Who has the information?

Who makes the decisions?

Who influences the decisions?

 

Consider:

Where are these people?

Where and when should they be interviewed?

How should we contact them?

 

  

Sampling Error Estimates

Random samples are selected with the goal of representing the total population or universe.  However, there will always be some level of error when using a sample to represent a population.  The margin of error will vary with the sample size and the percentage breakdown of responses to a question. 

To use this table to find the margin of error for a particular question, group the responses into two categories (i.e., yes & no, satisfied & not satisfied, user & non-user, etc.).  Next, find the closest sample size across the top.  The margin of error is shown in the cell where they intersect.  These error estimates are based on a confidence level of 95% meaning that in 95 out of 100 samples, the range includes the true population proportion. 

For example, if in a sample of 100 people, 50% preferred Version One and 50% preferred Version Two, the margin of error would be +/- 9.8%.  When reporting the statistics for this example, you would say, “Based on our sample, we are 95% confident that between 40.2% and 59.8% of the population favors Version One.”

 

Sample Size

Proportion of Responses (P)

50

100

300

400

500

1000

 

 

 

 

 

 

 

10% or 90%

+/-8.3%

+/-5.9%

+/-3.4%

+/-2.9%

+/-2.6%

+/-1.9%

 

 

 

 

 

 

 

20% or 80%

+/-11.1%

+/-7.8%

+/-4.5%

+/-3.9%

+/-3.5%

+/-2.5%

 

 

 

 

 

 

 

30% or 70%

+/-12.7%

+/-9.0%

+/-5.2%

+/-4.5%

+/-4.0%

+/-2.8%

 

 

 

 

 

 

 

40% or 60%

+/-13.6%

+/-9.6%

+/-5.5%

+/-4.8%

+/-4.3%

+/-3.0%

 

 

 

 

 

 

 

50%

+/-13.9%

+/-9.8%

+/-5.7%

+/-4.9%

+/-4.4%

+/-3.1%

 

 

 

 

 

 

 

 

 

 

Where:

 

     

 

 

 

 

CI = the confidence interval

 

 

 

P = the sample proportion

 

 

 

n = the sample size

 

 

 

Z = the desired level of confidence*

 

 

 

 

 

 

 

 

 

 

The above table uses a 95% level of confidence

 

 

 

where Z = 1.96; alternatives are

 

 

 

for the 90% level of confidence, Z=1.65

 

 

 

for the 99% level of confidence, Z=2.58

 

 

             

Correction Factor for Small Population

When the sample represents a large percentage of the total population (about 10% or more), the sampling error is reduced by multiplying the estimated error by the following correction factor:

For example, if the sample represents 40% of the total population, the correction factor would be 0.77x (estimated error in the above table).

Helpful Hints

This table is only relevant for data collected using a random sample (i.e., all members of the population have an equal opportunity of being selected).

 To determine the appropriate sample size, use the 50% line from the table and the acceptable margin of error for the research.  (The 50% line of the table shows the maximum error for each sample size.)

 

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