Analysis of Quantitative vs Qualitative Research Tutorial 2019
This tutorial explains Quantitative vs Qualitative Research with best examples. Quantitative data are analyzed at the conclusion of the research while qualitative data are analyzed while research is conducted.
The data from quantitative research are in the form of numbers that can be totaled, averaged, compared and contrasted. The resulting statistics are used to describe consumer behavior or preference within a targeted population segment.
Management may not understand how the statistics were obtained, but they can easily understand the averages and percentages and, therefore, trust the resulting information.
In contrast, qualitative research results in verbal data and images including recordings, written words and sometimes photos or videos. These data cannot be statistically manipulated, compared and contrasted.
Rather than proving facts using statistics, the analysis of qualitative data has as its focus the search for meanings. This is because qualitative research is used to answer the question of ‘Why?’
The answer will always be more complicated to explain to management than just a percentage or average.
The art of qualitative research
Qualitative research, as with quantitative research, is conducted in order to answer a research question. However, a skilled qualitative researcher may find more in the data than just the answer to a research question. Quantitative research is usually conducted using a survey methodology.
This limits the responses of participants to the issues in the survey form. Because the subjects involved in qualitative research are allowed to provide any additional information they feel is important, there will be a wealth of data.
These data may provide new insights to help answer the research question. In fact, it may turn out that the subjects have an entirely different view of the solution to a problem or a new opportunity.
Because the research process may reveal unexpected ideas and opinions it is important that regular meetings are held between researchers and the management of a company during the research process.
These meetings will be to share the unexpected insights that have resulted from the research. This will give the company’s management the opportunity to discuss whether they wish to have these insights further explored by adjusting the research methodology.
The analysis of qualitative data is also unique because it starts without predetermined categories in which to place ideas or opinions.
Rather, new insights will reveal themselves as the data are repeatedly analyzed by researchers. The goal of such analysis is a full description of the attitudes, values, and opinions of consumers.
The Analysis Process of Quantitative vs Qualitative Research
Once the data are organized and transcribed researchers review the material by reading through it with no preconceived idea of what will be found.
Researchers will again examine the data after this initial review, all the while coding common concepts. Once this level of coding is complete, the researchers will again review the material to find any concepts that need to be broken down into more than one category.
They will then analyze these concepts and categories by questioning what relationship they have to the research question.
Some of the data resulting from the research might be lists that have been collected on large pieces of paper.
Focus groups commonly use this method so that everyone present can view the responses being provided to questions asked by the moderator. The lists are commonly written in marker pen in large print and then hung on walls around the room.
These lists must be taken down, labeled and dated. Each label should include the research question that resulted in the list of information. The date of the focus group and the name of the researcher should also be noted on each piece of paper.
Once these pieces of paper are back in the office, the data should be typed up. If the lists include additional notations, such as item numbering when participants have been asked to prioritize, this information must also be added to the typed list. Sometimes arrows or other visual notations will be on the paper.
If they cannot be typed they should be described in the typed document. This typed list cannot totally duplicate all the information contained on the original sheets and, therefore, these should be saved in case they are needed for analysis.
Written materials from any other projective techniques should also be collected. These may be ideas written on index cards, cartoons with speech bubbles or sentence completion forms. Drawings made by participants should also be organized and saved by having them scanned into a computer program.
These scanned drawings will also now be available to be added to the final report. Digital photographs that have been taken by participants can also be downloaded into the computer, both for analysis and for future use in the final report or presentation.
When all the material has been written down, the data from focus groups can be organized by research question. If more than one group was conducted, the information should also be organized by group. Projective data should be organized by technique. For example, all sentence completion forms and all drawings should be kept together.
Interview transcripts should be organized by research question. Intercept interviews must be organized by location and expert interviews by topic. Observational research forms are usually organized by the location where the observations took place.
Ethnographic research materials should be organized by a site visit, while the material produced by grounded theory research needs to be organized by topic
Organization of data
Focus groups organized by research question and group
Projective techniques organized by technique
Interviews organized by topic
Intercept interviews organized by location
Expert interviews organized by topic
Observational research organized by location
Ethnographic research organized by the online community
The art of transcribing recordings (Quantitative vs Qualitative Research)
Qualitative interviews and focus groups will both result in tape recordings that will need to be transcribed. If possible, a word-for-word transcription should be produced.
However, if there is a great deal of taped material this may not be economically feasible. A good transcript will allow a company to experience the research process as if they were there.
It is best if the researcher who moderated the focus groups or conducted the interviews listens to the tape before transcription. While they are busy conducting the research, it is always difficult for a researcher to retain all that is happening. Listening to the tape will refresh a researcher’s memory of what was said.
In addition, the tone of voice used and even the silences between speech can provide insights.
After listening to the tape, transcribing the material is the next step in the analysis process. While a researcher is listening to a tape, they can be typing up notes on the main points being made.
Once the transcription process starts, the researcher can pause the tape while they make notes on new insights or memories. For example, there may have been a focus group member who spoke rarely but followed the proceedings closely with evident interest.
This gives more weight to his or her opinions than if the researcher remembered that the focus group participant seemed bored and distracted. It is difficult for researchers to take notes on behavior during a focus group or interview, so these notes should be added to the transcript.
The same or different participants will frequently repeat information, and a researcher can quickly pick up patterns and develop a shorthand notation process.
Transcribing tapes is much more than just a technical task, which is why it is best if a researcher prepares a transcript personally. The goal of transcription isn’t a word-for-word perfect transcript.
Instead, while the transcription is taking place, a researcher should concentrate on recording information that addresses the research question. While the conversation may stray and other topics be discussed, these topic areas are important only in how they relate to the main research question.
For example, if the research concerns the cost of a product, such as cell phones, participants may start discussing where they like to shop.
A researcher will then analyze this conversation for its relevance to the research question on cost, by noting whether the stores mentioned are discount outlets or high priced specialty stores. Information on a great sale on shoes that was added by one participant can be ignored.
When transcribing a tape, it is not important to note the names of speakers as they do not need to be identified personally.
However, it is still important to attribute comments to individuals to determine if there is consistency in the comments they provide throughout the focus group. Instead of names, a researcher can add a code or a number to represent each speaker.
In addition, comments on the tone of voice or emotion can be added using the same system. One means of adding such detail is to type the transcript in a column format. The first column will have the words spoken during the session, whether the interview or focus group.
The second column will contain the researcher’s notes on who is speaking, their tone of voice and any other observations noticed by the researcher when the research was conducted.
The third column will be used for coding purposes. Because this column transcript will be referred to frequently during the analysis process, it is important to leave additional space where handwritten comments can be added.
Coding Qualitative Data
Once the transcriptions are complete, researchers should review all of the data. This review should be conducted with an open and relaxed frame of mind. At this stage of the analysis, researchers must let the data reveal insights rather than impose ideas that were formed while conducting the research.
While the impressions formed during the research are important and should be retained, it is also important for researchers to look at the data with fresh eyes. It might be that comments and ideas which were initially overlooked can now be seen as being important.
Once data have been transcribed and reviewed, researchers will begin to code. Coding is used to note the repetition of ideas, opinions or facts. The first coding will be conducted to examine the data for answers to the research question.
For example, the research question might have asked how a visit to the dentist could be made more pleasant. A focus group of clients would be asked for their ideas for improvements that could be made to a dental clinic.
A transcript would be coded for the times when any mention of the ideas for improvements was mentioned. These instances are coded so that researchers can then return to the information to analyze if many of the responses gave similar ideas or if any unique suggestions were provided.
The transcribed notes will then be analyzed again to code other topics that arose during the research. For example, besides discussing ideas for improvements, researchers might find that on multiple occasions trouble reaching the dental office due to a lack of convenient parking or public transportation options was mentioned.
Another issue discussed might have been the services now offered at a new, competing, dental office. By coding these data, researchers may find that it is this new competition that received the most mentions. Below is an example of how data are being collected from online sources.
The first step in the analysis of all of the written material is coding for the main concepts that appear in the transcripts. Researchers read through the documents to see if there are any concepts that are raised repeatedly.
If a study involved the reasons why students leave the university before completing their studies, the main concepts that might appear could be ‘money’, ‘studies too difficult’ and ‘unfriendly staff’.
However, a more surprising concept that might be discovered would be ‘got a good job offer’. This analysis takes skill, as the wording used in each individual comment may not directly describe the concept and it will certainly take more than one reading of the material by a researcher before all of the concepts become clear.
It is a researcher’s responsibility to notice the similarities in comments and that they may all belong to a single concept.
Categories (Quantitative vs Qualitative Research)
Once researchers have finished coding for concepts, they may find that some need to be further broken down into categories. These concepts and categories are important as they are the building blocks from which researchers will make their recommendations for action.
For example, many comments in a transcript may involve the concept of the price of a product. Several participants may state that they don’t buy a product unless it is on sale.
Other participants may state that they buy a competing product because it is cheaper, while some may state directly that the price of a product is too high. While all of these involve the price of a product, a researcher may decide they are too dissimilar and break them down into three categories: ‘don’t buy because can’t afford’, ‘competing product purchasers’ and ‘non-purchasers’.
The researcher may then make different recommendations for attracting each of the first two groups and recommend no action on the third.
Researchers can code transcripts using highlighting markers with a different color for each concept and category, or alternatively, the concept and category name can be noted in the margins of a document.
As researchers code, the material for the answer to a research question, each time a researcher comes across a statement that deals with the issue of the price being more than a consumer is willing to pay this will be coded.
However, with qualitative research, there may be other concepts that arise that are worth noting (which is one of the benefits of qualitative research). For example, in the discussion on price, a researcher might note that several consumers expressed how much they enjoyed the design of the product.
While the research question had not addressed design issues, this would still be useful information for management.
Using coding to develop recommendations
Once coding is completed, all material will be reviewed again to develop recommendations based on the coded concepts and categories. For example, a research question might have asked ‘Why do consumers not purchase automobiles produced by our company?’
The coded material may have revealed infrequent comments made on color, appearance and amount of chrome. All of these comments the researcher will code under one concept – ‘style’.
Other comments made about the cost of the automobile a researcher will code under the concept of ‘price’. Further analysis might now reveal that the concept of ‘price’ is actually two categories.
One involves comments on the cost of the automobile, while the researcher might find that a separate category is now needed for those comments that involve the cost of maintaining such an automobile, including comments about gas mileage, insurance and repair costs.
Based on this coding researchers might recommend that promotional material should address the reasonable cost of maintaining the vehicle and not just the low purchase price.
Software tools for coding (Quantitative vs Qualitative Research)
Software tools that assist in the analysis of qualitative data are now available. However, marketing researchers must decide if it is worth the money to purchase such software.
If a research process has only involved one or two focus groups or interviews, the time saved in using software may not justify its cost and the time it will take for researchers to learn to use it. In this case, researchers may decide to rely on hand coding and analysis.
If researchers conduct qualitative research on an ongoing basis or have a large qualitative research study planned, then it may be worth their while to purchase and use coding software.
While these software packages can save researchers the tedium of coding, they do not replace the analytical process of determining the concepts and analysis of the concepts and categories that result in recommendations.
A software package designed for qualitative research will help with the development of a system of coding and then applying the system to the transcribed text.
It will also allow researchers to add brief comments to the data. These comments might explain nonverbal behavior that a researcher had noticed while the comment was being made.
Researchers will also be able to link different codes between transcripts, memos, and notes on different focus groups, interviews, and projective techniques.
The software can also help in the preparation of final reports by displaying coded categories in a graph format. If there is a sufficient amount of data, once it is coded the number of responses that include a particular type of content can be quantified for management.
This process is started by a researcher selecting text in a transcript that belongs to a specific concept, which the researcher then names. Once this task is done the software will then search all the data files for identical text and code these occasions as the same concept.
For example, the comment that a product is ‘too expensive’ will be coded as belonging to the concept of ‘price’.
The software will search all the transcripts and other written material for similar comments. In addition, the software can search for additional phrases that have the same meaning. Terms such ‘costs too much’ and ‘not worth the price’ can be added to the same concept.
Computer-assisted qualitative data analysis software (CAQDAS) while not new, is becoming increasingly sophisticated. The more advanced programs can now analyze and code not only text but also audio files. The purpose of the software is to enable researchers to analyze across numerous files of different types to find common themes.
Analysis of Qualitative Data Content
After data have been organized, transcribed and coded, the next step in the process of analysis is to determine if there are any relationships between the concepts and categories.
The purpose of developing relationships is to generate new ideas to answer the research question. These new ideas will be the basis for making recommendations for action.
After all, management will want actionable recommendations from a study, not just analysis. A report that simply describes researchers’ impressions will not be considered useful enough to justify the cost of the research.
Possible recommendations might involve how to target new types of consumer segments, descriptions of the process of consumer behaviors, a comparison and contrast of consumer motivation, or a new research question of a relation between variables that will need to be verified by future quantitative research.
Coded qualitative research data can be analyzed for information on possible new market segments to target.
A company may be aware of how to market their product to their current demographic and geographic segments, but qualitative data might reveal entirely new psychographic segments of which that company was unaware.
These new segments will have been identified based on common values and attitudes that have been verbalized or displayed during the qualitative research process.
For example, a research focus group on a product for older consumers might have found that people aged 65–75 years old do not consider themselves as being older. Because they are still leading active lives, this segmentation category based on age may have no meaning for them.
Instead, they may identify themselves as ‘active adults’ who just happen to be retired or on their second career. They may also think that they have no attitudes in common with people in the traditional category called ‘senior citizens’.
Likewise, qualitative research data may uncover segments of individuals who identify with various types of hobbies. What they will all have in common is a specific interest, say in crafts, and will, therefore, identify themselves by this, for example as ‘crafters’.
As a result, researchers might recommend that a company commissioning research on this topic considers producing products aimed at this new segment.
Qualitative research might also uncover new usage categories. In discussions of food consumption, it might be found that food ordinarily consumed at breakfast is also enjoyed at other times of the day.
Based on a finding that cereal is also eaten at the office, researchers might recommend a new promotional campaign based on this usage.
Consumer behavior processes
Besides new market segments, qualitative research can provide insights into consumer behavior processes. A company that makes readymade dinner entrées may be interested in the meal preparation processes of today’s busy dual career families.
Analysis of ethnographic data might reveal that parents would like to have everyone sit down for meals together, but that children have their own dietary preferences.
Using this knowledge, researchers could recommend that a company produces prepackaged dinners with a choice of side dishes so that everyone can eat together and yet still have the food they each want.
If it is found that parents still want to have their families maintain a little formality when dining, researchers might then recommend that the packaging includes decorative paper napkins.
An observational study on how people drive their cars might find that drivers need cup holders that can keep their beverages hot or cold when they spend long periods of time in the car. In addition, observing children traveling in their car seats may have revealed a need for a small storage area for their food.
These are ideas that might not otherwise have been discovered in quantitative survey research. However, analyzing the data from qualitative research can reveal useful ideas such as these that can be recommended to companies.
Comparing and contrasting consumer traits
While researchers are analyzing data, they may note some differences in the consumer behavior process based on demographic or psychographic traits. For example, a qualitative research study might have been specifically designed to examine and compare the differences in cell phone usage for different age groups.
These types of differences will appear in qualitative data from focus groups, interviews or ethnographic studies.
In this case, researchers might perhaps find that women were using the photo feature to take pictures while shopping of possible purchases for their home that they can then view later.
Meanwhile, it may also be found that males were using their cell phone cameras to take candid photos of their friends. These are ideas that can be developed into recommendations.
Development of new research questions
Another recommendation that may result from an analysis of qualitative data is a new research question about the relationship between two variables. This research question cannot be said to be proven, based on qualitative research.
However, it might be so intriguing that the researchers recommend quantitative research be conducted to determine the answer to this question.
For example, qualitative research might find that the consumers who are nonusers of a product believe that the product is too expensive to operate. This fact could then be tested further with survey research.
The information provided by observational research will not be in a verbal format. Instead, the data will be in the form of notes on behavior, photos or video. Observation forms and notes must also be analyzed, but not by coding for words. Instead, researchers will be looking for unique or repeated behavior that has been noted on the forms or in the photos or videos.
Researchers can look for these data concerning the process of using a product, new ways of using a product, where consumers use a product and the mistakes they make when using a product – all of which may have been noted on the forms.
For example, observational research of consumers shopping at a clothing store can show how they travel through the store, which products they tend to buy first, and how long they spend in the store. If researchers notice that people seem to have a problem finding the fitting rooms, better signage may be recommended.
Often netnography research may reveal that people use a product in a way that was not originally intended by the company that designed that product. These insights can be used to make recommendations on the redesign of a product or the development of a totally new product.
For example, a netnography study may have been conducted on students living together in university-owned housing. Analysis of discussions on sites used by students may have found that students like to study while lying on their beds. From this study, it might be recommended that better lighting is provided above beds.
The most important step in the qualitative analysis process is the coding of the data. Both repeated and isolated incidents and comments are coded by theme and named as concepts. This can be done by physically marking the words and then distinguishing the type of comment by words or colors.
This coding will be used to build categories with common elements. There is now software that helps to make this task more manageable, but the ideas for the coding of concepts and categories must first come from researchers.
Analysis of coded data will include questioning the relationship between categories and looking for insights that can be interpreted to answer the research question. The interpretation might reveal information on new potential consumer segments.
It also might reveal information on consumers’ behavior processes. Consumers could thus be analyzed for an interpretation of traits. In addition, new research questions may be determined. Finally, the analysis of nonverbal ethnographic and observational data can be used.
Analyzing Numerical Data
Does Everyone Shop on Amazon?
In the United States, the answer is almost yes! Only 17 percent of the primary shoppers in American households have never bought a product on Amazon. How often do Americans shop on Amazon? Twenty-eight percent shop weekly, 25 percent one to three times a month and 30 percent less than once a month.
Who doesn’t shop? They tend to be older: with an average age of 57 for non-shoppers versus 49 for shoppers. In addition, they earn less, $45,700 to $62,800. The question is why not?
After the survey results were analyzed, additional interviews with nonusers of Amazon have conducted that uncovered three reasons why people do not use Amazon.
First, some people enjoy browsing in stores, Second, some people find a large number of offerings for a single product more irritating than helpful. Finally, there are people who do not use Amazon because it is too easy to use and therefore they spend too much money!
Question: How could these research findings be helpful as Amazon is designing its first physical stores called Amazon Go?
Measuring Differences (Quantitative vs Qualitative Research)
Quantitative marketing research methods analyze consumers’ current or future behavior which can be expressed using numbers or percentages. When analyzing the data from quantitative research, consumers’ physical characteristics such as gender, age, religion, ethnicity, income, education level, or even their height, hair color or weight, can be quantified.
In addition, consumers’ behavior can be quantified by the frequency of purchase, consistency of purchase, place of purchase or size of purchase.
Using statistical analysis researchers will explain behavior using numbers rather than words. Furthermore, if the sample for a population is sufficiently large and properly selected, researchers will be able to say with some certainty that the research findings are probably true for the total population.
Scales of measurement
While a computer will be used to tabulate the results of a survey, the findings will still need to be analyzed by the researcher. Before the methods of analysis can be discussed it is important to understand measurement scales, as the type of scale used in designing the answer will affect the type of statistical analysis used.
People use measurement scales on a daily basis. When consumers decide to purchase a rug for their bathroom floor, they may decide to use their own feet and pace out the floor space to be covered.
When they go to the store they can again measure off the space using their feet and find a rug that fits. Of course, it is simpler to use a measuring tape already marked off with standard units of measurement.
The nominal scale
The nominal scale is used for characteristics that can be defined as different states of being. There are only the two states and a research participant must be one or the other.
University graduate and non-university graduate are an example. A research participant can be one or the other, but not both. Nominal data are usually analyzed by simply counting the responses.
The report might also state that of the 100 participants, 78 did not graduate from the university while 22 did graduate. When analyzing the central tendency, the mode will be used.
Ordinal measurement scale
The ordinal scale is used when there is not just an absolute difference, but rather a degree of difference, such as preference. A question using the nominal scale would be ‘What type of pizza do you prefer?’
This question, using an ordinal scale, would ask consumers to rank order their favorite types of pizza. Analyzing these data would provide a ranking, such as participants’ favorite type of pizza topping is pepperoni, followed by olives and then sausage.
While this type of measure provides information on ranking, what it does not show is how much more popular pepperoni pizza is than olive or sausage. When analyzing the central tendency, the median will be used.
The Process of Quantitative Data Analysis
After conducting a survey, researchers will be faced with either a pile of survey forms or, if the survey was entered directly into a computer, an electronic file. Researchers must now begin the task of analyzing the data.
This process of data analysis will begin with a pre-analysis stage where researchers will review the data, including its validity, completeness, and accuracy. They will then code any open-ended questions and enter all the data into a computer software program.
Using an online form can save time at this stage because the data will already have been entered into a computer. Another advantage of online surveys is that researchers can monitor the data as they arrive.
However, the electronic file still needs to be reviewed for completeness and any responses to open-ended questions must be coded. This is also true of online forms that ask for complaints or suggestions.
After the pre-analysis, the next step in the statistical analysis is determining the frequency of responses. The analysis may be of a single variable, or the frequency of more than one variable could be cross-tabulated.
Once this has been completed, the data are analyzed for central tendency by calculating the mode, median or mean. Researchers will also want to know how widely the participants’ responses varied from each other, so dispersion will be examined by calculating standard deviation, range, and variance.
Finally, statistical tests will be performed to determine if differences in the data are due to chance or random error, or if such a difference has a statistical significance.
Statistical testing can include chi-square, t-test, ANOVA, correlation and regression. This statistical testing will be used to determine if the hypothesis is supported.
For example, the researchers may have hypothesized that more men than women attend the cinema. If the data show that men buy fewer theater tickets than women, statistical testing will confirm if this difference is significant enough for the alternative hypothesis to be supported. A study may contain more than one hypothesis as long as questions are written to address each.
Pre-analysis of survey data
Once survey research has been conducted, the first task confronting a marketing researcher is to review the questionnaire forms. After this review is completed, the researcher is ready to code any open-ended questions. The final step in the pre-analysis process is to enter the data into a computer software program.
Researchers may have taken great care in deciding upon the research question. In addition, the questionnaire form may have been painstakingly written and tested. However, unless the survey sample was very small with only a few participants, the actual conducting of the survey will have been out of the control of researchers.
For an administered survey form, assistants will have been hired to conduct the survey. Self-administered forms will have been completed without any help from researchers or assistants. People may start an online form, answer only two or three questions and then quit. Because of these facts, the survey forms must be checked for validity, completeness, and accuracy before the data are entered.
The issues that arise when validity is considered are whether the survey was actually conducted by an assistant and whether a participant was eligible for the survey. It is unfortunate but true that sometimes those people hired to conduct surveys may actually have completed the forms themselves.
This may be due to frustration, because of an inability to obtain the cooperation of potential participants, or it may be due to dishonesty. Whichever might be the case, all forms should be checked to see if it looks as if an assistant has completed them.
Clues would include answers that are extremely random or answers that are constantly duplicated. In addition, the demographic portion of a form should be checked to ensure that any eligibility requirements, such as age and education level, have been respected.
Not all survey forms will have every question answered and so should be checked for completeness. A form may be incomplete because a participant chose not to answer some of the questions or it may not have been completed because of time constraints.
In addition, the form may have consisted of more than one page and a participant may not have noticed additional questions on a second page. Researchers must then decide what percentage of completion is required for a form to be included in the study or for it to be discarded.
Lastly, forms must be checked for accuracy. Researchers must review the forms to determine if the answers can be read and understood. They should be able to easily distinguish which answers have been marked. In addition, the answers to open-ended questions should be able to be deciphered.
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Coding survey data
After checking for validity, completeness, and accuracy, the forms are ready for data entry. Since surveys are a form of quantitative research, the data need to be entered as numbers that can then be statistically analyzed. Close-ended questions should have been pre-coded on the survey form with the numbers that will be entered into the computer.
However, open-ended questions will require manual processing before they are ready to be entered into the computer. To accomplish this task, researchers should begin by listing all the answers that were given to an open-ended question and then consolidate the responses.
For example, if a question asked for reasons for shopping at Crossroads Mall, the responses might be consolidated into the groupings of ‘convenient location’, ‘variety of stores’, ‘parking’ and ‘special events’. Each grouping is then assigned a numerical code and it is this code that is entered into the computer.
If a survey is web-based, the data entry step is not required as the answers are entered automatically. Data entry for traditional paper survey forms can be performed by anyone with the skill to use a computer. A software package can be used for statistical analysis.
Data Analysis Using Descriptive Statistics
Frequency can be understood using the example of a survey question that asked why consumers shopped at Steve’s Sporting Goods store. The first issue faced by the researchers helping Steve is that not all of the 1,000 survey forms distributed may be usable as some of the participants may not have answered the question, while others may have attempted an answer but the mark they made is difficult to interpret.
In addition, some respondents may not have completed the questionnaire. As a result, of the 1,000 survey forms distributed perhaps only 950 will be useable. When the data are analyzed for one-way distribution (how many people responded to each potential answer to the question) it may be found that helpful service is the most frequent response.
This information will quickly inform Steve of the ranking of the responses, with helpful service being top, followed by best selection and then good prices. However, it is difficult when just reading the numbers to understand how much more important to the participants was service over the selection.
Adding a percentage to the table makes the relationship between the responses easier to grasp as most people can see the relationships between percentages more quickly than those between raw numbers.
The percentage is calculated from the total number of responses used (950) rather than the total number of respondents (1,000). The percentages show that helpful service is almost twice as important as the best selection.
The survey question asking consumers for their motivation for shopping at Steve’s could have been designed to allow for multiple responses. The question would have read ‘Which of these reasons are why you shop here?’ In this case, the numbers would look different as some people might tick more than one response.
Because the question allowed respondents to tick more than one answer, the total response is now 1,095. However, the percentage is still calculated on 950 respondents which is why when added together, the responses total more than 100 percent.
The term hypothesis is used when describing the scientific method. This is a process that attempts to determine if something is true. A hypothesis is simply a statement of fact that needs to be proved using statistics. After all, if there were no scientific method all that would be left is a person’s opinion or idea.
A business cannot spend money on developing a new product or starting a new marketing campaign based only on someone’s opinion that they will be successful! The cost of failure would be too great.
Of course, it is impossible to absolutely prove that the outcome will be successful. However, conducting research and then analyzing the results will help.
A hypothesis is a guess that is made by the company or individuals commissioning the research. Perhaps an academic publisher has come up with an idea for a new textbook that can be easily read on a smartphone. The question is whether they should spend the money to develop and introduce the product.
Qualitative research has indicated that many students would be interested in this product. However, the finance department of the company has stated that at least 20 percent of current student textbook purchases will need to purchase the new product to cover development costs and make it financially viable.
This first hypothesis is the null hypothesis and will be stated as what the company does not wish to be true. (The symbol H0 is used to designate the null hypothesis.)
Formulas for stating the hypotheses
H0: π = 0.20
H1: π = 0.20
The formula for calculating the standard error
= √π (1 −(π)/np
= √0.20 (1 − 0.20)/1100 = 0.010
Using this number as the standard error, the Z-score can be calculated.
Formula for calculating z-score
z = (p − πh)/p
2.0 = (0.20 − 0.22)/0.010
Steps in the analysis process
State the hypothesis
Conduct the research
Compare the measured value with the hypothesized value
Decide the necessary level of confidence
Choose a statistical test for significance
Calculate the test value
State a conclusion and any recommendations
The chi-square test is used for what is called ‘goodness-of-fit’ when analyzing frequencies of responses in a frequency table using cross-tabulation. Marketers often want to know if there is a relationship between a specific group of consumers and some preference for a product benefit.
Marketers also may want to know if men or women prefer the product in a smaller size bottle, or they may want to know if young consumers would prefer the product in a new color.
While these statements could be presented as hypotheses this is not necessary. In fact, when using chi-square all researchers need to do is think – the computer will handle the rest.
Using the example of the publishing company and the textbook, the company believes that men will be much more interested in the product than women. The researchers will use software to calculate a cross-tabulation of preference (yes or no) with gender (male or female).
The computer, based on the proportion of men to women in the sample, will calculate what the expected percentages would be if there was no difference in preference versus if gender makes a difference.
It would be simple to compare these numbers using percentages if the groups were all the same size. However, this is unlikely to be true.
A survey would be conducted to ask how many events were attended and then the mean for females and males would be calculated. It would be unlikely that the average would be exactly the same.
The t-test tells the researcher if the difference is significant to warrant action. ANOVA is a test that is similar but can handle more than two groups. For example, if the study on sporting event attendance wanted to determine the difference between first, second and third-year students.
Another way of examining data statistically is a correlation, which looks at how one variable affects another. Using the example from above, another question that might have been asked is the students’ address. A correlation could be run between attendance and distance from the stadium to see if it affected attendance.
If the question is whether the distance from the stadium and also a student’s academic standing affect attendance, multiple regression can be run. The analysis that will result will show if either, distance or academic standing, have a significant effect on attending sporting events.
1. Quantitative research produces statistical findings that, if the sample is sufficiently large and has been carefully chosen, can be used to support a null hypothesis.
The measurement scales that can be used are nominal, with two states of being, and ordinal, which also shows preference. In addition, interval scales provide a standard unit of measurement, and ratio, which has a given start and end point.
2. The process of qualitative data analysis starts with the pre-analysis of data including review, coding and data entry. The descriptive statistical analysis includes frequency, central tendency, and dispersion. The inferential analysis includes analysis of statistical significance used to test a hypothesis.
3. Frequency analysis provides a count of the frequency of responses. Cross-tabulation shows the number of responses along with at least one other variable. Central tendency analysis of the data includes the mode (or most frequent response), the median response and the mean (or average). Dispersion measurements include range, variance, and standard deviation.
Reasons for preparing a report
Researchers must prepare a thorough report as management may not be able to understand the research methodology or the analysis process without a clear explanation. Terms such as ‘stratified sample’, ‘projective techniques’ or ‘confidence level’ may have no meaning to those whose responsibility it is to make decisions based on the research.
Without an explanation of these terms, the data will either be meaningless or misunderstood. Marketing research is also used in fields other than just consumer marketing. For example, a study done on political issues may well have a reader who is familiar with political strategy but unfamiliar with research methodology.
The second reason for a written report is so that the knowledge that is obtained from the research continues to be available in the future. The research data and recommendations need to be maintained for both the marketing department and management.
All companies have personnel changes and it is particularly common for marketing professionals to change positions frequently.
Even the manager who commissioned the research may be promoted or leave the company. If there is no written report, the new manager will have no access to the knowledge that resulted from the research effort. In this case, duplicate research may be conducted.
Because the management of an organization will generally not have the time or inclination to involve themselves in all the details of the process, their report will provide a quick overview of the research process.
Management will usually want more information on any findings and recommendations. A shorter report that leaves out most of the technical details has the advantage of being less expensive both to write and reproduce.
In addition, researchers should remember that a shorter report is more likely to be read and understood. Because managers are busy with many responsibilities, a long report may be put aside to be read ‘later’ when there is more time.
Unfortunately, this ‘later’ (with ample free time for reading the report) may never arrive. Researchers working together with management from the beginning of the research process will prove advantageous for both.
Research + Management Goals = Success
Marketing research practice now emphasizes partnerships between researchers and management. Today researchers understand that their research must deliver more than numbers.
Research findings must translate into concrete benefits for companies by helping them achieve business goals. If not, management will not commission research again. Ten tips to ensure that the research findings are seen as useful by management are:
Align market research with the marketing plan
Link market research with business results
Link business activities with future business results
Integrate the voices of customers and employees into the strategy process
Link customer attitudes with customer behavior
Engage stakeholders in the research process
Define success measures
Track those measures
Create a process for driving insight
Create a process for driving improvements that produce action Question: How else can market researchers convince management that research is useful?
Findings and recommendations
It should not provide all the data that were compiled during the research process, instead, it should summarize the data that were used to develop the recommendations. Research always provides a wealth of information. However, providing all the detail at this point in the report will only confuse the reader.
For example, a survey might have been conducted to discover what activities consumers want to experience on a cruise ship. The research will have also asked survey respondents demographic information.
During the analysis stage, researchers discovered that the geographic location of consumers’ homes made no difference to preference.
This fact will be stated. However, there is now no need to present a detailed breakdown of the home location of each participant in the body of the report. These data can be added in the appendix.
The recommendations should directly address the research question and the research objectives. The goal of all research is that it proves useful and it doesn’t just sit on someone’s desk.
It’s All about the Implementation and it: Starts with the Report The marketing researchers should start thinking about the implementation even while they are preparing the report and presentation.
While the researchers have conducted the research, and have a deep understanding of what the findings mean, this is not true for the report’s audience. A way must be found for other people to understand the findings and internalize what they mean for the organization. Here are some ways to do so:
Always Start with the Why: Explain why the research was conducted and why the findings matter. If you don’t there is a good chance that the report will end up unread.
Provide a Story: Don’t only talk about data in the abstract. Use real examples. If the data were based on only statistical analysis, give hypothetical examples of typical customers to make the story real to the listener.
Use Diverse Media: Not everyone wants the same amount of information so provide long and short forms of the report. In addition, the report can be provided verbally, with an online video or be using infographics.
Crowdsource Implementation Ideas: Rather than give your opinion on what actions should be taken, give opportunities for everyone in the organization to provide their ideas. This can easily be done using social media.
Question: What social media could be used in an organization to get ideas for actions to be taken based on the research findings? Source: Jolls, 2015
The final section of the research report will provide the full data that were obtained during the research process. It will also include information that provides further details on the research sample and methodology.
For example, details on the research sampling method can be explained. If referrals were used, the organization and individuals contacted can be listed. Examples of research methodology such as survey forms, projective techniques or focus group scripts can also be included.
Writing a Professional Report
Using visual material
The research findings section will contain a wealth of detailed numerical data. A report writer should use visuals to assist readers in understanding the relationship between different sets of data.
For example, readers can quickly visualize the relationship if 46 percent of the respondents were female while 54 percent were male.
However, if part of the research question addressed the age of the survey respondents these demographic data can be quite detailed. For example, if 12 percent of the respondents who used the product were aged 18– 22, 16 percent were aged 23–29, 26 percent were aged 30–39, 23 percent were aged 40–49, 14 percent were aged 50–59 and 9 percent were 60 or older.
It is extremely difficult for readers to visualize quickly and see the relationship between these numbers. To assist readers, such detailed data can be presented in the form of tables, charts or graphs.
A table simply lists numbers in rows by categories. Individual numbers will still be discussed in the body of the text. In the example given above, the writer might include in the body of the report that the largest age group of product users was 30–39, at 26 percent, with 23 percent of the users aged 40–49.
The writer might then add that the smallest group was aged 60 or older, at 9 percent. This comparison thus makes the point that most users are middle-aged. The remaining numbers, while still relevant in showing the distribution, should not be discussed in the body of the report as it makes it too difficult to read.
A pie chart is a visual method to present raw numbers and their relationship as percentages of a whole. Pie charts are useful when representing numbers that make up a whole, such as the percentage of customers in different age groups.
The different sections of a pie chart should be shown in various colors or in shades of gray for each group. Using color to differentiate the sections makes a pie chart easier to read and use.
A line chart is designed to show changes in data over periods of time. Time is shown on the horizontal axis, while the numerical measurement is shown on the vertical axis. A line chart can show the percentage change in a product’s sales by any measurement of time, such as by the day, month, season or year.
The advantage of a line chart is that it can easily display movement in value over time for more than one variable. For example, a company may collect sales data for five different products all of which could be shown on the same line chart. This could then reveal if there is any relation between changes in sales figures.
People find it easier and faster to process visual information than text. Infographics are a way to take almost any data and present it in a pleasing visual format. They present both the numbers and an explanation of what the numbers mean.
They are not a substitute for a written report, but rather a way to get the interest of the reader who will then read on for more detail. There are many online sites that can be used to generate infographics. They can be used in both the written report and oral presentation.
An Oral Presentation
An oral presentation is an opportunity for researchers both to explain and to ‘sell’ to management any research findings and recommendations.
An oral presentation also allows researchers to provide a more effective description of the research methodology.
This is because during an oral presentation a presenter, by observing their audience, can become aware of when they are encountering difficulties and can explain any confusing details more fully.
In addition, a presenter can more clearly explain how report recommendations are related to any research findings. Finally, an oral presentation provides a means to clarify any misunderstandings about the research process.
Reasons for oral presentation
A clearer explanation of the methodology
An opportunity to explain the tie between research findings and recommendations
An opportunity to clarify misunderstandings
Presentations, just like written reports, must have a structure as it helps the audience anticipate, and concentrate on, information that is of particular interest. A structure also helps a presenter stay on topic.
No one would throw together a written report at the last minute as its poor organization would leave readers confused. It would be quite obvious to them that researchers had not taken time to present the material in a logical manner.
However, some people do throw presentations together at the last moment and believe that their audience will not notice. Unfortunately, a poorly prepared oral presentation will leave listeners just as confused as a poorly prepared written report.
A well-prepared presentation will have four major components: an introduction, methodology, findings and recommendations, and a conclusion.
It is important when planning a presentation that most time is devoted to the recommendations section. Please note how the time has been divided to ensure that all topics will be covered before the conclusion of the presentation. Not all sections are given equal time as not all have equal importance.
The presentation’s introduction should identify the researchers and the commissioning company and also explain how long the presentation will take. During the introduction, the presenter should inform the audience whether questions may be asked during the presentation or if the audience should keep their questions until the end.
The introduction should then very quickly state the research question and describe what information the presentation will contain. For example, in a 30-minute presentation, the introduction should only last about three minutes.
The section of the presentation on methodology is where the presenter will first state the research question and objectives. The presenter will then briefly inform the audience of how the research participants were selected. The presentation should not be used to describe the technical details of the sampling procedure.
If the audience is interested, the report will contain all the necessary information. The purpose of describing the sampling procedure during the presentation is simply to give credibility to the findings and recommendations.
The same holds true for the methodology, although more time should be spent on this topic so the audience will better understand how the findings were obtained.
At this point in the presentation, a sample survey form can be distributed, projective techniques can be displayed, or a short video clip from a focus group can be shown.
Findings and recommendations
The presenter should spend more time presenting the findings and recommendations. They can use visuals such as graphs to quickly show to the audience what has been learned from the research. The presentation should never try to explain all the findings, as there simply isn’t the time and the audience will get lost in the details.
In addition, it is the presenter’s responsibility to sift through all the findings to determine what is relevant for answering the research question. However, any findings that have an impact on the recommendations should be presented.
When Can Research be Considered Effective?
The answer to this question is clear to those market researchers who attended a seminar sponsored by Research Solutions, based in New Zealand. In their opinion, marketing researchers must ‘come out from behind their pie charts’ and become partners with the organization commissioning the research.
What does such a partnership mean? A true partnership was defined as exhibiting four factors:
1. The partnership must be based on trust. Of course, a good market researcher will produce accurate findings but management must also trust the recommendations made by researchers.
2. Management must be willing to risk making changes based on research findings. This risk-taking approach must start at the research proposal stage. If the research proposal is written to allow only a conservative research approach, no breakthrough findings can possibly result.
3. Researchers must be in contact not just with management and marketing but also with other departments throughout a company. This must be the case because the recommendations that result from the research will impact more than just the marketing department.
If these departments do not trust the marketing researchers, they are more likely to argue against taking action based on their recommendations.
4. Management must accept that research findings are based on consumers’ viewpoints, which can be surprising and sometimes uncomfortable for management to hear. It is not the responsibility of researchers to only bring good news.
Question: Which of these issues do you believe is the most critical in developing a partnership?
The conclusion to a presentation should be brief. The presenter should restate the research questions and the main recommendations. They should also thank the audience for their attention.
The presenter should allow adequate time to answer any questions. The audience should also be informed of who it is they can contact if they have any questions in the future.
PowerPoint is probably the best-known method of presenting visual information during oral presentations. However low-tech methods can also be used, including writing on a whiteboard, using flip charts and distributing handouts with relevant information and photographs of products or research participants.
They can be effective because the low-tech approach can seem more personal. Whiteboards and flipcharts can be used to draw attention to important facts.
If a surprising 78 percent of consumers surveyed were unaware of a company’s new promotional campaign, this number can be written out in large print in red on the board or paper. The number becomes a clearly drawn exclamation point for this fact.
Even if a presenter chooses to use PowerPoint during a presentation, it is still useful to use a low-tech method such as handouts with a summary or pertinent information.
This summary, which should only list the main findings and recommendations, serves two purposes. It can be used to reinforce what a presenter is explaining and it can also provide a place for an audience to write notes as they are listening.
Handouts can also be used that contain other material, such as maps of the study area or copies of the survey form or projective techniques.
Photographs of the product under discussion can also assist an audience in better understanding the relevance of data. These photographs can be used as displays around the room where a presentation is taking place.
High-tech presentation aids include the projection of an online source, videos, and PowerPoint. Using a PC and a projector, presenters can bring up on screen material that is online. For example, if the research involved the perception of a company’s image the home page of that company’s website can be shown.
Video clips of participants, perhaps in focus groups or as part of the observational research, can also be used during a presentation. The use of videos is becoming increasingly common when making research presentations as they will bring the material to life in ways that other material cannot.
Sometimes research studies have relied on videos to record events or behavior that are then analyzed. Of course, these studies should include some of the video clips in the presentation.
Marketing research is conducted to find answers to questions which will lead to recommendations for future action. This information is usually communicated through a written report and oral presentation.
Reasons for the written report include the need to explain the research methodology, to preserve the knowledge for future employees, to document the actionable ideas that resulted from the research and to provide clarification in case of future misunderstandings.
A researcher may wish to prepare reports of different lengths for other researchers, management, staff, and participants.
A research report will consist of an introduction that will identify those involved in the research and provide a brief overview of the contents. The methodology section of a report will explain the research question, the objectives, and the methodology.
The third section, which is the most important part of the report, will discuss the research findings and recommendations. The appendices will provide background information that will more fully explain the report’s contents.
A professional report is readable, interesting and concise. If this is not the case, the report will not be read and, therefore, the recommendations will not be implemented. Numerical data should be communicated using tables and charts. These will help readers visualize the relationship between groups of data.
An oral presentation is needed to explain the methodology, the relationship between the findings and the recommendation, and to provide an opportunity to clarify misunderstandings.
The presentation will include an introduction, methodology and findings, recommendations and a conclusion. A presentation should be interesting, organized and brief. Both low-tech and high-tech visuals should be used to better communicate information.