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Dapresy Pro Aggregated Survey Data Format Guide

DAPRESY PRO AGGREGATED SURVEY DATA FORMAT GUIDE

of 9

July 2013

www.dapresy.com Dapresy Pro Aggregated Survey Data Format Guide of 9

INDEX

1 Introduction .......................................................................................................................................................... 3

2 Format .................................................................................................................................................................. 4

3 Process .................................................................................................................................................................. 6

3.1 Data import ................................................................................................................................................... 7

3.2 Defining Filters .............................................................................................................................................. 8

3.3 Reporting ...................................................................................................................................................... 8

3.3.1 Setup of a chart/table in Storyteller ..................................................................................................... 8

3.3.2 Exceptions and limitations in Storyteller .............................................................................................. 9


1 INTRODUCTION

This document is a guideline document for reporting aggregated survey data in Dapresy Pro.

Aggregated survey data differs to other kinds of aggregated data such as shipment figures, sales data, media

ratings, syndicated data, etc. For example, when looking at sales data two aggregated results can be merged

without any issues but when looking at aggregated survey data both the result and the base size needs to be

considered if two values are merged.

Example: Aggregated survey data has been imported on a monthly level as shown below.

• January = 25% (base size 100)

• February = 37% (base size 50)

• March = 26% (base size 90)

When looking at the cumulative first quarter, the result would be 29.3% (the mean value of the 3 months) if

the base size was not considered. In order to get a correct result, the number of respondents in each month

must be considered, and that correct result would be 26.4%.

1. Base size not considered: (25+37+26)/3) =29.3%

2. Base size considered: ((25*100)+(37*50)+(25*90))/(100+5++100)=26.4%

The solution proposed in this document takes the base size into consideration and this solution should only be

used for aggregated survey data and not for other types of aggregated data.

Aggregated data can be stored in many different file formats like Excel, SPSS.SAV and Triple-S which all can be

imported to Dapresy Pro. Since Excel is the most common way to store aggregated data, this document will

focus on the Excel format.

While storing aggregated survey data in Excel can be done in many different ways, this document describes a

standard format which makes the reporting very flexible. The solution supports the use of the built in time

functions which means that aggregated data can be imported on a weekly level but reported on a monthly,

yearly level etc.

Other features like Moving average calculations and Warnings for low base size will also be supported as the

base size is known.

Since it is typically required, this solution also supports the need of setting specific colors per question and

answer alternatives.

In summary, aggregated survey data can be imported in many different ways but the standard described in this

document should be followed for highest flexibility.

Note: Using aggregated data instead of respondent level data makes the process less effective and

limits the possibility to drilldown in data which is one of the core features in Dapresy Pro. Whenever

possible, Dapresy recommends that respondent level data is used to get the maximum benefit of

using Dapresy Pro.


2 FORMAT

When importing aggregated survey data, there is one calculated result and corresponding base size per

question/answer and target group for a specific date. Ideally, data should be reported by week and based on

these weekly data, monthly, quarterly and yearly results can be calculated by the system automatically.

In order to filter the data on any background variables, these variables must be included in the imported data

file as well. In the example below, an age and a gender variable is included.

The following parameters must be included in the imported Excel file:

• Date

• Questions

• Answers

• Result (a numeric value, %, mean or a special index etc)

• Base size (a numeric value)

• Target group definitions

Date

The Date column must hold a proper date containing month, day and year.

During the data upload, the meta data transformation capability within Dapresy Pro is used to define what date

format has been used; for example: dd-MM-yy, dd-MM-yyyy, MM/dd/YY


Questions

Each question in the survey should be added as a separate column. If a question has different results, for

example a mean value and the percentage share of a top 2 box, the question should be split into two

questions. In the example above, column D and E shows one question as the top box and one the mean value.

Brand/Answer

The answer alternative of the questions, for example a brand or any kind of answer option. As shown in column

F above, if the answer option Volvo is present in multiple questions it must have the same spelling in all

questions.

Filters

A column for each target group used must be present; in the example above columns G and H, age and gender

are used. Please note that these columns are not required if the results are not needed to be filtered by any

target group in the reporting.

Result

The result must be a numeric value. It does not matter if the result is a mean value, a % value or a special index.

Base size

The base size is needed for getting a correct result when merging aggregated result.


3 PROCESS

The process for creating reports based on aggregated survey data is more or less the same as when reporting

respondent level data. All features like changing meta data texts, creating question blocks, compute new

variables, change colors, etc can be used.

The main difference in the chart/table setup when using aggregated survey data versus respondent level data

is that the variables used in the reporting are numeric variables and not categorical variables. Because of this,

the question and answer selection is different when setting up a chart/table. The answers selected in the filter

tab as a numeric variable don’t have any answer categories. The image below shows an example of a chart

setup. The chapters below explain what needs to be done to get the correct result.

The images below show the setup of a chart. The first image shows the question selection. The second image

shows the Brand/Answer selection and the third image shows the result.

Image 1

Image 2

Image 3


3.1 DATA IMPORT

During the data import, the meta data transformation function in Dapresy Pro is used to recode the Excel data

into the appropriate format. The following steps are required:

• The Base size variable should be set to Weight Variable*

• The Date variable should be set to Response date variable

• Create a Respondent ID variable

• Recode the Brand/Answer and all Filter variables into categorical variables (they will be String as

default and must be recoded into categorical in order to report the data).

*This is the key to get the correct result when merging aggregated data points. By doing this, all calculations

will include the base size and the results will be correct.

The images below shows the Meta data transformation, the first image shows the original setting based on the

imported Excel file and second image shows the new defined question types.


3.2 DEFINING FILTERS

When creating a chart or a table the Brand/Answer selection must be made in the Filter section and this

variable must be defined as a Filter variable. The other filter variables like Gender and Age must be defined as

Filters variables as always.

The image below shows the Filter page and indicates the Brand/Answer variable is defined as a Filter variable.

3.3 REPORTING

The Table Tool and Chart creator can be used but it is recommended to not be distributed to users due to the

fact that the variables are numeric and the answer/brand selections are made in the Filter area. DO NOT

distribute to Report users due this complicated process for first time users. Our recommendation is to use the

Storyteller for making reports based on aggregated survey data.

3.3.1 SETUP OF A CHART/TABLE IN STORYTELLER

The setup of a chart and table works the same way as using respondent level data. The difference is the

variables; they are numeric instead of categorical.

To select the variables in the setup, select the option “Average Numeric questions” as shown in the image

below. When doing that all numeric variables appear in the variable list.


To select brands/answers use the Filter tab. Note that the compare option below the selection box must be

checked or the chart will show the mean value of Volvo and Ford and not the split between them.

3.3.2 EXCEPTIONS AND LIMITATIONS IN STORYTELLER

When using aggregated survey data, a few limitations appear in the Storyteller reporting.

• When using significant tests, the calculation must always be based on the formula used for Mean

values. Otherwise the aggregated result is a percentage share and the wrong formula will be applied.

This is due to the fact that the selected question type is an “Average numeric question”

• When using Numeric questions, the series type Side by side and Stacked bars can be used, Full stacked

cannot be used.

• The chart option “Apply positive/negative shares” cannot be used as the setting is located in the

answer options of categorical questions.

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