BI Survey Report Relevent Info(Sem 3)

8/6/2019 BI Survey Report Relevent Info(Sem 3)

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1. Introduction to the survey

This introductory section will usually contain a contents page, a credits page, anexecutive summary, and background data on the survey.

Preliminary pageso Executive summary. Many reports have a one-page "executive summary"

at the beginning, so readers can get an idea of what·s in the report.o Contents page. An alternative is to write an annotated contents page,

with headings in the style of newspaper headlines: a one -line sumary ofthe results shown in each section.

Who is responsible for the report:o the organization that commissioned the survey - and why it was

commissioned.o the main contact person in that organizationo the organization that did the researcho any other organizations involved in any subcontracting

o the chief researchero and the person who wrote the report.

Give addresses and contact details as well as names. Are you thinking "thatseems like a lot - why bother?" The answer is that reports are often used yearslater, when a follow-up survey is done. The more informati on provided in theoriginal report, the easier it is to contact the people involved. This is veryhelpful when a follow-up survey is being planned.

Background data:o Dates - which can include the dates of the fieldwork, the date the report

was completed (and any other relevant dates).o The geographical area covered by the survey - with a map, if possible.o Standards (of ethics and data quality) followed in the conduct of the

survey - such as the ESOMAR Code of Conduct.o Definition of the population.

o Exclusions from the sample (e.g. children under a certain age, or peoplenot living in private households).

o How the sample was selected.o References to other relevant documents, such as census data - but if

there are a lot of references, they usually go at the end of the report.

If there is anything else that refers to the survey as a whole, it should be mentioned in

this preliminary section. Next, you need to go through each question separately...

2. Write about each question in turn

Cover each question asked in the survey - about 2 pages per question is usually enough.Avoid covering one question across more than one page opening. Control variables(such as time, date, and place of survey) should be included as if they are questions.



Q uestions should be covered in the most logical order for the hypotheses - often (butnot necessarily) the same order as the questionnaire.

For each question, write about each of these 5 points:

1. Who was asked?

2. How many people were asked?3. What was the question?4. What type of responses were gathered?5. Summary of responses.6.

The examples below show how it can be done. 2.1. Who was asked? Were all respondents asked the question, or only some - if only some, who? 2.2. How many people were asked? This is the sample size for that question: the numbe r of respondents who answeredthat question - often less than the entire sample size of the survey.

2.3. What was the question? Here, write the exact wording of the question. Any special instructions thatinterviewers were given, on how to ask this question, should also be given.

2.4. What type of responses was gathered? This means the format of the response type (if not obvious from the results). In otherwords, were respondents asked to choose from a list of possible answers ("multiplechoice"), or was the question open-ended (letting respondents give an answer in their

own words, or supply their own numbers. How many answers were respondentsallowed to give: only one, as many as they wanted, or some in -between number?

If open-ended, were the answers then combined by coding? If "other" answers weresought in addition to the multiple -choice answers, list any "others" mentioned by atleast 1% of the sample.

2.5. Summary of responses Different people understand data in different ways, so it's best to provide the responsesummary in four different formats: as a verbal summary, a verbal explanation, a table,and a graph. The responses to each question normally fill two pages: one opening of a

report - such as with words on one page, and a table and/or graph on t he facing page.If there's not much detail, one page is sometimes enough.

The verbal summary is like a headline, expressing the main finding from tha question.One sentence is enough. This is followed by a more detailed verbal explanation of theresults, both describing them in words, and also commenting on them.

For the frequency table - which can often be combined with a graph - the formatdepends on the type of answers that were given to this question. At the foot or top of



the table, show the total raw numbers and the total % (usually 100%). For questionsthat allow multiple answers, show two percentages: % of respondents and % of answers.It's best to copy and paste a table from the statistical software into your wordprocessor file, to avoid numeric errors - removing unnecessary elements later.

If more than about 1% of respondents who were eligible to answer this question did

not answer, here provide any reasons why this might have happened.

There are three main types of question, and the responses to e ach are displayeddifferently. These are (1) multiple -choice (but single-answer) questions, (2) multiple-answer questions, and (3) open-ended questions. Now for some examples of eachtype...



Multiple-choice question For multiple-choice question: list the frequency distribution of answers for thequestion, showing both raw numbers and %. List the frequency distribution, showingboth raw numbers and percentages. If the sample was less than about 200, list wholepercentages, e.g. 15%. If more than about 200, give percentages with one decimalpoint, e.g. 15.1%.

Example 1: Single-answer question. Notice how the raw numbers are in a different type

style from the percentages. Gender of respondent.

Base: all respondents

Gender No. %

Male 87 48

Female 94 52

Total 181 100

Example 2: Multiple-answer question. Note simple bar graph on right of percentages.

Q 14. Base: all respondents (n=181)

"At which of these times did you listen to radio yesterday?"

Time of radio listening:Monday

No. % *

00-04h 2 1 |

04-06h 2 1 |

06-08h 45 25 |||||||||||||

08-10h 20 11 ||||||

10-12h 7 4 ||

12-14h 7 4 ||

14-16h 13 7 ||||

16-18h 36 20 ||||||||||

18-20h 33 19 ||||||||||

20-22h 45 25 |||||||||||||

22-24h 17 9 |||||

* Total > 100%, because of multiple answers.



Numeric questions: group responses For numeric questions with more than about 10 different responses, the responses canbe grouped. E.g. if you ask respondents their exact age, the frequency distribution canshow 5-year age groups: 15-19, 20-24, 25-29, and so on, up to "65 or over". The finalcombined category should have fewer respondents than the previous category - e.g. if3% were aged 60-64 and 4% were 65 or over, then the 5 -year groupings should go to

65-69. The principle here is to have a small number in the "X or over" grouping.

Example 3: This table has grouped ages that were gathered as individual years, compared

the survey results with the census data, and shown the difference. The table was followed

by a comment on the reasons for the difference, and how much those differences might

affect the survey results. Because the main purpose of the table was to compare the

sample with the population, it did not include raw numbers, which would have made the

presentation confusing.

Base = all people (606 of them answered)

Q .16 "What is your age?"(grouped in 5-year bands)

Survey%

Census%

Diffference%

15 to 19 years 13 19 -6

20 to 24 11 14 -3

25 to 29 15 13 +2

30 to 34 15 10 +5

35 to 39 10 9 +1

40 to 44 10 8 +2

45 to 59 9 6 +3

50 to 54 8 6 +2

55 and over 10 15 -5

Total 100% 100%

Open-ended questions

For open-ended questions, present coded responses (plus maybe full text in appendix)

if there are only a few possible answers, these can be listed as for a multiple-response question.

But if many different answers are given (more than about 20) they need to be coded and grouped.

The codes need to be explained, so that readers of the report can interpret the question well.

When the sample size is small, it is often best to have a minimal number of grouping, and report all

the answers in an appendix.

Example: 4 In this case, the hypothesis related to noticing live programs, hence the

highlighting. Other responses were of less interest for the research. Notice that when a

question allows multiple answers, the percentage is ambiguous (% of people or % of

answers?) so you need to state what the percentage is based on.



Changes noticed on provincial radio

Ha Nam % of

respondents

Live programs 58

Other program changes 20

Non-program factors (e.g. hours, reception) 29

Total > 100% because of multiple answers

Base: all who noticed changes n=138

Verbal summary

A verbal summary should show the main highlights from the table. Don't overdo it: if readers want

all the details, they can read them in the table. One paragraph is often enough, and half a page is

plenty, even for a complex table. Here's an example of a verbal summary - based on the above

table.

When asked what changes thay had noticed on provincial radio in the last 6 months, 138

people (76% of the total sample) mentioned at least one type of change. 58% of these

mentioned the introduction of live programs. 20% mentioned changes to programs, other

than live programming, and 29% mentioned changes that were not program-related - such

as broadcast hours or quality of reception. These percentages add to 107%, because a few

people mentioned more than one type of change.

Take care not to confuse frequency of response (what surveys measure) with othe factors. Thus in

the above example it would be wrong to write "Live programs were the most popular change." Just

because live programs were more noticeable doesn't mean they were more popular - which might

imply more liked. After you've written a summary, get somebody else to read it and see if they can

misinterpret it. If they can, rewrite it!

If you have any other data (e.g. from a census or previous surveys) related to that question,

mention it in the summary. Also discuss any problems that occurred with that question - e.g.

ambiguous wording.

Graph the results

A graph of that frequency distribution can also be useful - but not essential. Bear in mind that

graphs take a lot of space in a report. If you include a graph, make sure everything is clearly

labelled, including axes, units, and values. Give it a heading that summarizes the findings in one

line, and is related to the topic of the study - e.g. in the above example not "Changes noticed on

provincial radio" but something like "Live programming was the change most noticed."

The best graph format to use is generally the horizontal bar chart, with one line per frequency. Pie

charts take too much space, and histograms don't have enough space for labels, if there are more

than a few different answers. Don't use colour graphs if your report will be photocopied in black

and white - or use patterns as well as colours to distinguish the bars in your graphs.



Significance testing

Which hypotheses (or sub-hypotheses) apply to this question? If the hypotheses can be tested by

knowing only the frequency response, do a significance test (usually chi-squared for categorical

data, or a t-test for numeric data) and report the results. Usually you need quote only the t or chi-

squared figure, the degrees of freedom, and the probability of the outcome. If the P figure is less

than .05 it can be regarded as significant.

Cross-tabulate relevant pairs of questions

Most questions don't have much meaning on their own, so you need to cross-tabulate them with

other questions. Each cross-tab will test a major or minor hypothesis. Don't try to cross-tab each

question with ever other - only the ones that either (a) you have hypotheses for, or (b) you want to

make a demographic comparison for. If the answers to a cross-tab are not statistically significant,

report them only if this is an important hypothesis. Otherwise, just report that the different wasn't

significant - e.g. "Q uestion 3 produced no significant differences at the .05 level for different sexes,

age groups, or geographical areas."

When putting tables into a report, remember than you can only squeeze about 8 columns across apage, and about 50 rows down. If there are too many different answers, you'll need to recode the

question to reduce the number of columns (or, sometimes, rows).

Here's an over-simplified guide to which statistical test to use:

If both questions are categorical, use the chi squared test.

If one question is categorical and the other is numeric, use a means comparison (F test, or

one-way anova).

If there are two categorical values being tabulated against the numeric variable (e.g.

comparing the income of men and women), use a t-test.

Also do a graph, showing how the means vary for each category.

If both questions are numeric, do a regression analysis to find out how much the answer to

one question can predict the answer to the other.

Also do a graph: a scattergram or (if there are not many different values) a bubble chart.

Example 5: Recognize this? It's just Example 3, with two more columns of data. That's all a

cross-tab is. However it's more important with a cross-tab to make sure that readers

cannot misinterpret the percentages. The normal convention is that percentages add to

100 downwards. If they add across - (usually done to fit the table onto a single page, as in

Example 6, below) you must show this very clearly - as Example 6 does.

Changes noticed on provincial radio Ha Nam Q uang Nam Vinh Long

% of respondents in that province

Live programs 58 61 76

Other program changes 20 32 21

Non-program factors (e.g. hours, reception) 29 20 15

Total ... >100%, because of multiple answers

Base: all who noticed changes n=138 n=132 n=161



Chi-squared = 22.74 (10 degrees of freedom).Significance of differences = .008 **

Groups of questions

Sometimes, a group of questions can be combined - for either of two reasons:

a set of questions asked to produce a particular score on some combined variable - e.g.

Snyder's self-monitoring scale. When questions have been grouped in this way, a combined

score should be shown. (This is done by computing a new, combined variable, in the

statistical software, and reporting on that new variable.)

Grouping questions without a summary scale, to enable easier comparison of results.

Combined table and summary

Report the findings as for simple frequencies above: a table and a verbal summary of it. When a

question is part of a grouped set, less detail is needed for each question. You can report on the

whole set together - but you will still need to discuss each individual question briefly.

One combined graph

Instead of having a graph for each question, produce one graph comparing all the questions. A

horizontal bar graph (for categorical questions) or area graph (for numeric questions) is often the

clearest way to present the data.

Use scale averages to compare questions

Another way to compare a grouped set of questions is to calculate averages for scales - e.g. for a

Likert scale with 5 possible answers, coded 1 to 5, calculate the mean for each question and

produce a graph of the means. (If the frequency distribution for each question in thegroup follows

the same pattern - but if some questions have very different distributions - e.g. if most questions

have about 20% saying "totally agree" but one question has 50%, report on that question separately.

Make sure not to include missing values in scale averages - e.g. if respondents are using a 1 to 5

scale, and "don't know" is coded 6, exclude those 6s from the calculation of averages.

Correlations

When a group of questions has the same format and the same set of answers, it's often useful to

calculate a correlation matrix. However with more than about 20 question in such a set, a

correlation matrix becomes very difficult to read. In that case, a factor analysis or cluster analysis

might be better than presenting a simple correlation matrix. i don't recommend presenting

correlation data unless your readers have some knowledge of statistics. Correlations are easily

misunderstood, and almost nobody understands factor analysis. Cluster analysis is easier - you can

just say "answers to these questions go together."

Example 6 - a table from a group of questions. This table combines the answers from 8

related questions, making it easy to compare which types of program are most and least

listened to. Always include a Total column (usually 100%, as here) so that readers can see

what the percentages mean, and in which direction they add up. The percentages are

based on the number who answered each question. Notice that the sample sizes are in a

different type, again to avoid confusion.



Respondents who answered Yes to question 1 (148 of them) were asked question 6:

"How often do you listen to [type of program] on LTVR? - Daily, weekly, monthly, or never?"

Type of Program Daily Weekly Monthly Never Total Sample

Phone-inprogramme

41% 31% 12% 18% 100% 147

Advertisement 87 9 4 0 100% 147

News bulletin 91 7 2 0 100 % 145

Current affairsdiscussion

39 46 15 2 100% 146

Deathannouncement

52 38 2 8 100% 120

Music, reggae 70 26 2 2 100% 145

Health program 25 52 19 4 100% 146

Music, Arabicstyle

38 36 13 13 100 % 141

Example 7 - A cross-tab from a group of questions. This has one question in each column

and one answer in each row -generally the easiest format to read. This time the totals are

not shown, because they would make no sense. Sample sizes in each area are shown as "n="

to avoid confusion with the other figures, which are all percentages.

Q .18 (Sample = all respondents )

"Which of these media do you use at least once a week? TV? Radio? Print?"

Media used weekly Banjarmasin%

Pekanbaru%

Jakarta%

TV 84 59 81

Radio 84 92 74

Print 57 45 64

Total > 100% because of multiple answers

Sample size n=151 n=185 n=181



Conclusions, maybe recommendations, and appendixes

When all this is done, you'll have reported on each question separately, with a page or two per

question. Then you'll have had reports on grouped questions. When somebody reads a report like

this, they feel swamped with data. So you need to summarize it, and explain how each question fits

with the others, and come to some overall conclusions.

At the end you should write several pages of conclusions for people who've just read (or skimmed)

the whole report, summarizing what you think are the main findings of the survey. If it·s relevant

to add recommendations, they can go here. However, there·s no point in writing recommendations

without giving reasons for them - otherwise the readers don·t act on them.

Finally, there can be appendixes. It's good practice to include a copy of the questionnaire - even

though you have already given the wording of each question individually. The appendixes may also

include tables related to sample selection, instructions to interviewers, and so on. Sometimes

there's so much appendix material that it can be produced as a separate volume - the existence of

which should be mentioned in the first volume. The advantage of the two-volume report is that

because fewer people are interested in the technical details, fewer copies of the second volumecan be produced.

Another way of saving paper is to produce both a full survey report (with few copies distributed)

and a short summary report, with many copies distributed. The disadvantage of the latter approach

is that it means writing two separate reports, which costs more, and takes longer. Thus writing a

summary report is usually justifiable only if the expected readership is large - say 100 or more.

If your readers all have internet connections, you can save paper (at your end) by emailing the

report to them. A few suggestions, if you do this:

(1) Graphs are usually in colour, but if readers don't have colour printers, graphs can be hard to

interpret. So unless you know that all your readers have colour printers, make sure that your graphs

will be legible when printed in black and white.

(2) Emailed reports often get emailed onto others, who you (the writer of the report) don't know

about. After we discovered that somebody had changed a crucial figure in one of our emailed

reports, to make his department come out better, we started distributing reports in PDF format,

which readers can't change.

If you are interested in writing research reports we suggest you seriously consider our book Know

your Audience - A Practical Guide to Media Research (revised 2007), which provides a

comprehensive and usable guide to all aspects of audience research including how to write and use

research findings and reports. This book is available as a 384 page PDF document for just 10 Euros,

US $15 or AUD $15. Click here to learn more about the book.



Reporting Survey Results

When your survey and analysis has been completed, the final step in the survey process is to present

your findings, which involves the creation of a research report. This report should include a background

of why you conducted the survey, a breakdown of the results, and conclusions and recommendations

supported by this material. This is one of the most important aspects of your survey research as it is the

key in communicating your findings to those who can make decisions to take action on those results.

eSurveysPro results can be displayed right from the software, or your data and graphics can easily be

exported to a variety of applications like Excel, Word and PowerPoint. For a more powerful report, you

should include descriptive text along with your charts, tables, and graphs to give added visual impact.

Provide a background

Before you start working on the details of your report, you need to explain the general background of

your survey research. If you will be presenting the findings to your audience (the decision-makers), you

will need to make the basis for your research clear, including what objectives were established, and the

conclusions drawn from your findings.

Introduction to the survey research

List the factors that motivated you to conduct this research in the first place. By stating the reasons

behind the research, your audience will have a better understanding of why the survey was conducted

and the importance of the findings.

Identify research objectives

Itemize the goals and objectives you set out to achieve. Before you constructed your survey, you had a

plan as to the information you needed to get from your respondents. Once you had those goals in mind,

your survey questions were chosen. Did your respondent's answers give you the information you sought

after when you designed the survey? Make a list of the objectives you set out when you started, those

objectives that were met and those that were not, and any other information relating to the planning

process.

Explain the data collection process

Specify how your data was captured. For the purposes of this article, we are referring to a survey for

collecting the data. But be specific as what type of survey you used - online, telephone, or paper-based.

Also consider who and how many it was sent to, and how the analysis was conducted.

Describe your findings

Explain findings discovered in your research, especially facts that were important, unusual, or surprising.

Briefly highlight some of the key points that were uncovered in your results. More detail will be revealed

later in the presentation.



Finalize your thoughts and make recommendations

Summarize findings in concise statements so that an action plan can be created. Your conclusions and

recommendations should be based on the data that you have gathered. It is from these final statements

that management will make their decisions on how to take action on a given situation.

Structure your report

The background information of your survey research may need to be fine-tuned into a structured report

format for a polished presentation. Survey research reports typically have the following components:

title page, table of contents, executive summary, methodology, findings, survey conclusions, and

recommendations.

Title Page

State the focus of your research. The title should what the report is about, for example, "Customer

Satisfaction in the European Market." Also include the names of who prepared the report, to whom it will

be presented, and the date the report is to be presented.

Table of Contents

List the sections in your report. Here is where you give a high-level overview of the topics to be

discussed, in the order they are presented in the report. Depending on the length of your report, you

should consider including a listing of all charts and graphs so that your audience can quickly locate them.

Executive Summary

Summarize the major findings up front. Listed at the beginning of your report, this short list of survey

findings, conclusions, and recommendations is helpful. The key word here is "short" so no more than a

few complete sentences, which may be bulleted if you wish. This summary can also be used as a

reference when your reader is finished the report and wants to just glance over the major points.

Methodology

Describe how you got your data. Whether you conducted an online, paper or telephone survey, or

perhaps you talked to people face to face, make sure you list how your research was conducted. Also

make note of how many people participated, response rates, and the time it took to conduct this

research.

Findings

Present your research results in detail. You want to be detailed with this section of the report. Display

your results in the form of tables, charts and graphs, and incorporate descriptive text to explain what

these visuals mean, and to emphasize important points. eSurveysPro's charts are fully customizable so

you can display your data in a variety of ways, such as bar or pie charts, or even tables. The chart

legends can also be adjusted to suit your needs. This flexibility allows you to be creative when displaying



your results. However you arrange your results, it is helpful to have a close correlation between the text

and visuals so that your audience will understand how they are related. For example:

Survey Conclusions

Summarize the key points. This concise collection of findings is similar to the Executive Summary. These

conclusions should be strong statements that establish a relationship between the data and the visuals.

Remember that thoughts expressed here must be supported by data. You may also mention anything

that may be related to this survey research, such as previous studies or survey results that may prove

useful if included.

Recommendations

Suggest a course of action. Based on your conclusions, make suggestions at a high-level, as to what

actions could be taken to help the survey project meet the research objectives. For example, if you

concluded that customers are not satisfied with customer service from the support staff, you may

recommend that management should monitor support staff calls to assure quality customer service

standards are met.

Making a recommendation doesn't necessarily mean that action is going to take place, but it provides

management with a baseline from which to make their decisions.

Presentation Media

In years past, formal reporting of research results was presented as a printed report, often very long

and difficult to comprehend. In recent years, the convenience of word processing, spreadsheet and

presentation software has streamlined and condensed this process dramatically.

Presentation software, like Microsoft PowerPoint, has become a standard in most industries. Used in a

slide format, it can display your survey results in an organized manner. eSurveysPro data and graphics,

whether exported right from the software package, or having been manipulated in Excel, can be inserted

into this slide format easily.

To give an idea of how efficient this presentation media is, here's an example. A traditional text heavy

report may contain 100 pages of text and graphics, and wading through this material can be time-

consuming and hard to understand. However when organized in a slide format, this massive amount of

information can be reduced down to a 20-50 page slide presentation, with concise bullet points and

compelling visuals. Follow the tips below to streamline the look and feel of your presentation.

Tips on formatting your slides:

1. Experiment with type styles, sizes, and colors. Don't be afraid to bold text, underline or

italicize if you are trying to emphasize a point.

2. Keep titles short. About 5-7 words will get your point across.

3. Make good use of the space available in the slide. Enlarge the graphs and have the text

large enough that it is easy to read across a room.



4. Format your slides horizontally (landscape) and not vertically (portrait). You don't want

part of your slide to be below eye level.

5. Don't put too much data on one slide. One idea per slide is ideal. If you have many graphs

and data in one place, the audience may lose interest. In addition, the increased amount of text

will most likely require you reduce your font size, which will make it harder to read from a

distance.6. Two graphs maximum per slide. This will make your data easier to understand. If you must

have two visuals, make sure the text accompanying it is simple.

7. Avoid using busy slide backgrounds. Multiple colors or gradients can make text hard to read.

Conclusion

Communicate your survey results effectively to your audience with a survey research report. Organize

your survey findings with background information, detailed data and results, conclusions and

recommendations. eSurveysPro gives you the flexibility to display your results as-is, or transfer your

data to other applications to create compelling slide presentations. With eSurveysPro, you can rest

assured that your data and graphics will have that professional touch.

BI Survey Report Relevent Info(Sem 3)

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