Using Survey Reports to Comprehend Survey Results Better

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Using Survey Reports to Comprehend Survey
Results Better
Now that you have collected survey responses, it
is time to be on your toes, do comprehensive
data-analysis, erase junk data, and make sense
out of this raw material. We have created this
post, to discuss how you can analyze survey
results to obtain key findings, behaviors, and
statistics.
List out the top research questions
Lets say you held a conference and trying to
gather valuable feedback, then questions like
How would you rate the conference overall?
should be on top of your list. It would help you
find out valuable points like the overall
feedback about the conference. In another
example, for a question like, Are you planning
to renew the package next year?, you can
bifurcate the answers in separate categories.
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If out of 100 users, around 30 said NO and 70
said YES, then it is clear that 70 of them are
planning to continue the use of your product.
Further, the opportunity lies in 30. You can try
connecting to them to know what went wrong or
maybe offer some discounts. Analyze
quantitative data first With quantitative data,
you can draw conclusions and reliable statistics.
This type of data is mostly obtained from
close-ended questions that you can easily convert
into a numeric value. For example, a question
like, What were the key points of the event
according to you? can allow the user to share
their personal experience. Once the data is
quantified, you can easily convert results into
a numeric value to compare them and identify
trends in customer behavior. The reason behind
starting with quantitative data is because they
help you better understand qualitative data. For
example, if 70 of customers are not satisfied
with your services, then you need to focus on
how you can enhance their experience. For that,
you can start by identifying roadblocks in the
journey and working on pain points.
Leverage reports by cross-tabulating
It is important that the data you are analyzing
contains the responses from your target audience.
For example, if you are analyzing the report
where you want to see area wise results, then
create segments accordingly. After that, take
variables like age, interests, occupations for
further analysis. Cross tabulating the data of
these variables will help you understand the
relationship between these variables based on
which you can craft your targeted marketing
strategies. Continuing the above example, in the
area wise report, after segmenting responses
according to your target areas, you can start
analyzing their responses by taking multiple
variables into count. This way, you can get
precise results by not letting junk data overrun
your actual data. Understand the statistical
significance This point talks solely about your
target audience. Its natural that we get excited
after receiving a good number of responses which
is very rare. But it is possible to miss out on
accuracy between large data sets. For example,
in your recent survey, 80 of responders are over
35 years old, but your target audience is 18 to
29 years old. In such cases, the data will not be
statistically significant.
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To avoid this, you can simply leverage survey
reports of SugarCRM Survey Module, and segment
individuals from a larger population into smaller
and niche groups. This will help you simplify
your survey responses and you would get more
accurate and presentable results. Consider
causation vs correlation In the end, when you
drive conclusions from surveys, they shouldnt be
inaccurate or insufficient. For instance, you
observed a correlation between T-shirt sales and
Shirt sales. In the next quarter, when you saw a
surge in the t-shirt sales on your e-store, you
estimated that professional shirt sales will
pick up too but they didnt. In this case, you
probably thought that those two sections had a
connection but -- no they dont. Just because
they seem correlated, it doesnt mean one causes
the other. In such cases, there is typically a
third variable -- trend -- that influences the
two independent variables. So before coming to
conclusions, check if any new influencer or
celebrity promoted shirts and because of that,
they were in trend. If so, then that was the
reason for the surge in shirt sales. Hence,
analyze what drives a customer to think, act in a
certain way rather than making assumptions.
Do not forget to compare
When you have current data, ascertain that you
are comparing it with previously accumulated
data. It can be yearly or quarterly. For example,
say 50 of responders said they would recommend
your business, which is a great number. But you
have to see where were you the previous year to
calculate the change. After analyzing the data
for the first time, you can benchmark those
results for the next analysis. This way you can
track changes monthly, quarterly, yearly or the
interval that is preferable for your
industry. Once you have the final insights in
place, it is time to convert the data in a
presentable format for everyones understanding.
You can present your data in the form of charts,
infographics, data tables, etc. Also, it is
important that others understand the insights the
way youve understood them. Because it is very
easy to misinterpret data.
Source Link https//www.appjetty.com/blog/using-
survey-reports-comprehend-survey-results