The creative market researcher always seeks to go beyond the limitations of the source data and add value.   One way of doing this is to create new variables or data points from existing ones.

Consider a scenario where there is a desire to plot:

• market penetration, an existing variable (“Ever”) …
• against adoption rate, a new dimension created by dividing the result for “Monthly” by the result for “Ever”.

A typical workflow might be …

There are however potential problems with this approach:

1. If the output needs to be updated, for example when there is new data added, many if not all the steps need to be repeated.
2. If the output needs to be replicated for say different filters or scenarios, this too can involve repetition.
3. If the updates or replications are to be done by someone other than the original author, the need to find the right Excel Workbook and the right location within it can take up valuable time.

The Power of Having Everything Connected

These problems are instantly resolved by having your data, outputs, and workings housed and connected in one document, as you can do in Displayr.   Zooming out in this example we can see the following set up.

• A) Hidden tables for the two source questions, “Ever” and “Last Month”.
• B) A hidden calculation, dividing the results for “Last Month” by “Ever”, our adoption ratio.
• C) A Calculation Grid, extracting brands from A and B and linking data via cell references.
• D) A scatter-plot visualization linked to C.

There are also some filter controls top left and a dynamic date filter applied to all inputs so the analysis will always show the most recent quarter as the data is updated.

Hidden items (indicated by grey cross-hatch shading) means that the document editor can see the output but it will not be shown when published to a dashboard or exported to PowerPoint.

If someone comes to edit the document later the relationships are easily identified via Displayr’s dependency graph (right click on an item to find it).  The scatter plot is created from the summary table, the summary table is a combination of Q3 and the adoption calculation, and so on.  This addresses problem 3 noted earlier (difficulty in tracing workings when they are in a different place).

But the real benefits kick in when it comes to updating or replicating this output (problems 1 and 2).   It should be self-evident but watch in this video how seamless it is to create new versions of the framework via filtering and updating it with new data … even the footer descripting the sample date and size changes.

If you want to take a closer look and study the workings in detail, you can get a copy of this document here: Embedded Workings

Once you’ve tried embedding your workings in your report and have both linked directly to the source data, it’s very hard to go back to using external workbooks or sheets.

A quick Google search on "BCG Matrix" demonstrates it's one of the most popular strategic tools around.   Courtesy of the Boston Consulting Group, it plots relative market share against growth rate, to help determine marketing or resource allocation effort:

• Invest in "Stars"
• Milk (maintanance-level investment) "Cash Cows"
• Reduce investment in "Dogs"
• Strategize high-growth/low share "Question Marks"

It can be used to study either your own portolio or an entire market, to help qualify the strength of competitive threats or opportunities.   Here is an example for a fictituous fast food market:

... made even more powerful!

With the required data at hand, it's not that hard to create a BCG matrix in Excel and dress it up in PowerPoint.  But what if you wanted to replicate the matrix for different geographic markets or revisit it when you have new data?   That's potentially a lot of time and effort.  Displayr makes it easy to create a dynamic BCG matrix.  You can easily switch between markets (or any other filters) and have it update automatically overtime, when new data is added.

This is enabled by your data, you workings, and the output all being connected and in the one place.   Changes in to any item automatically impact other items "downstream".

If our brand is "Burger Chef" the strategic position is vastly different in North and South America, requiring different marketing solutions.

You can access this dashboard, explore its workings, and see how the dynamic matrix was built in Displayr here.   The key steps in the process are also set out below ...

_______________________________________________________________________________

1 Source some market share data

Here we've used occasion counts to calculate share, and shown this overtime.   With the table selected, we've renamed it "market.share" in the Object Inspector (so it's easy to find in drop down lists, etc).

2 Calculate the x-axis (relative market share)

1. In our case we want to matrix to update annually so it's ready for each new phase of strategic planning.   We created a table using Table > Select > Input "market.share", then Select columns by > Last columns (1), so it's always showing the most recent market share.
2. With "current.share" selected, Calculation > Maximum > Maximum Each Column, name this calculation "maximum.share"
3. Select "current.share" table first, then holding down Shift, select "maximum.share" output, Calculation > Divide.  The selection order makes things more efficient when using mathematical functions.  Name the new output "relative.share"

3 Calculate the y-axis (year-on-year growth rate)

1. Find the "market.share" table in your document (Step 1) and duplicate it.   It will automatically be named "market.share.2".  Rename it "absolute.change".  Move it to a new page or working space.
2. With the table selected, Rules > Table Computations > Different Between Pair of Columns.  In the Rule settings, select "Last Column" as Column 1 input and "2nd Last Column"  as Column 2 input.  Again, in this way the data will always be up to date when it changes.   Label the new column "Change YOY".
3. An easy way to calculate relative change, our target metric, is to insert Calculation > Custom Code, then click on items to reference them or simply start typing their name.   This is the end result of the custom code needed:
   absolute.change[, 4]/(current.share-absolute.change[, 4])*100.

   Here's how easy it is to do ....

4 'Rough-in' the matrix

1. Visualization > Bubble > Labelled Bubble, then click and drag the cursor to locate the chart
2. Inputs > DATA SOURCE > X coordinates > relative.share, Y cordinates > growth.rate, Sizes > current.share
3. We opted to exclude a couple of outliers - Arnold's, as it's the known dominant leader and Bread Basket as it's new and has an artificually high growth rate.   In Inputs > ROW MANIPULATIONS > Rows to ignore add Arnold's, Bread Basket
4. In Chart, tidy up as required - add data and axes lables, remove grid lines, etc.

5 And finally, add a control

1. Anything > Filter > Control > Combo Box (Drop Down) on an Output, select the variable "Market" and allow the user to select more than one category when prompted.   A new variable will be created called "Combo Box Filter Market" which you can rename if you wish.
2. Find the the two source tables market.share and absolute.change, select them and apply the combo box filter via Inputs > Filter(s)

After Steps 4 and 5 you will have a working framework as per below.  We then handed the document to our designers to create the final version (as shown above), ready for publishing.    Before publishing you would Hide all the working steps above (hiding either the pages they are on or the individual items if they are below the main dashboard).

Calculation grids allow you to add a new type of table onto a page, where the table can be a mix of text,  values, or calculations, including links to other tables.

Calculation grids allow you to do things in Displayr that you previously would have had to do in Excel or PowerPoint.

How to use

Calculation grids are added from the Calculation menu in the toolbar. You can add data into a calculation grid by:

1. Typing directly into it. If you want to type text, surround it by quotation marks (e.g., "my text")
2. Copying either data from another table, or part of a table, and right-clicking and choosing from the paste options.

Example use case

It's often useful to create tables like the one below, which draw in data from multiple other tables.

These are now easy to do using calculation grids. The 2 minute demo video below runs through this use case.

Key differences from Excel

Feature roadmap

• Custom formatting of individual cells (font, color, number format, borders)
• Custom row and column heights/widths
• Speed and performance of calculations
• Excel like updating of cell references when copying formulas across cells
• Custom Displayr R functions to simplify formula creation e.g. vlookups

We hope you find calculation grids to be useful and if you have any feedback or questions please reach out to us via the help menu in app

Displayr has a large and growing library of automated variable creation options.   This library now includes the ability to automate combining the data contained within certain types of variables into new and interesting categories:

• Transform numeric variables into useful categorical variables
• Combine or collapse categorical variables into meaningful groups based on patterns in the data
• Convert information like Zip or Postal Codes into logical geographic areas

This automation can save you a lot of time. Most importantly, these functions make relationships in data clearer, to help sharpen your analysis and story building.

Displayr users can find and explore these features in Ready-Made New Variables > Automatically Combine Categories. Here are a few examples to bring these features to life...

Create Categories Based on Data Values

Select a numeric variable as input and have a high degree of flexibility in how you transform it - you can automatically create data-driven tidy categories, percentiles, equally spaced categories (where you can control the increments), or custom categories.  Custom categorization allows you to enter pre-defined 'cut-points' - the variable is created without having to use code or make manual edits. Displayr can also automate the Label style, with a range of options dependent on the categorization method selected.

In this video we create a complex numeric variable and transform it using a range of these methods:

Combine or Collapse Categories based on Patterns in Related Data

This option will automatically collapse categories in the input variable based on the statistical relationships to another variable. It does this using CHAID (Chi-Squared Automatic Interaction Detection). Simplifying the variable of interest gives the analysis a lot more focus, providing insight and promoting actionability.

In this example, looking at the impact of household structure on category consumption frequency, we started with 9 categories that indicated some relationships in the data and automatically transformed that to 3 categories where the relationships are abundantly clear. 'Young Singles' is the primary demographic segment of interest and 'Younger Groups' is the secondary segment of interest.

In Displayr, select Ready-Made New Variables > Automatically Combine Categories > By Pattern (CHAID). When working with ordinal variables you can force the function to only collapse adjacent categories.

Convert one type of Geographic Data into Another

The proliferation of online research and the integration of survey research with CRM systems has led to much larger sample sizes. This brings into play geographic variables like ZIP or postal codes.   Displayr has functionality to transform these and other types of geographical data for North America, Europe, Australia and New Zealand. This geographic heat map was created from scratch, combining ZIP code and category frequency data, in less than 2 minutes.

You can see the steps in this video:

Explore Automatic Combinations now!

Existing customers will quickly see how much time they can save and how much power they can add to their analysis using the automated functions to combine numeric, categorical, and geographic data. Anyone else can book a demo or take a free trial.[/vc_column_text][/vc_column][/vc_row]

However you can make the process of creating inputs for visualizations, charting, and tables even easier by adding calculations or values directly to the data input drop-down.

Example 1 – Custom Selection from a complex table

Here is a typical table that has been created from some consumption data for fictitious fast-food brands.

Let’s say we are only interested in charting the data for Burger Chef and a direct competitor, Burger Shack.    One way to do this would be to:

1. Duplicate the question (to keep the original data and table intact)
2. Create the table
3. Hide all but the two columns in question, or, use the Tables > Selection function to create a subset of the table
4. Insert a visualization, say for a column chart
5. Hook up the table to the visualization.

This would work fine but it also adds some complexity – Step 1 adds over 100 new variables to the Data Set (some of the rows have been merged) and there are several interdependent elements in the workflow described above.

With the ability to ' Enter a calculation or value' directly in the drop-down, in combination with Displayr’s point-and-click formula creation, the process is a whole lot easier.   You can see this in action here.

We took that slowly so you can see the steps, but in less than 30 seconds we’ve achieved the required result, and with fewer steps.

Example 2 – Modifying a Variable before visualization

The same Data Set contains information on the estimated number of visits each brand attracted in a month.

Let’s say we wanted to express this as a weekly average, to conform with other market metrics (e.g. weekly sales).   Again, one way to do with would be to:

1. Select the variable set
2. Calculate > Divide, which creates a new copy of the variable set
3. Enter ‘4’ as the single number to divide by, as a proxy for weekly data
4. Insert a visualization, say for a bar chart
5. Hook up the table to the visualization

Using the ‘Enter a calculation or value’ function this can be done without the need to create any new variables, as shown in this video

Again, all the required steps have been condensed to a few simple ones, and in just a few seconds

Learn more about custom selections and formula creation in Displayr: Calculate Anything! or Boost your analysis with in-built Calculations

The possibilities for Displayr’s custom selection and formula creation functions are vast – now you can easily add such calculations to visualization drop-downs, the only limit is your imagination!

In addition to creating tables and common advanced analysis functions (like clustering, correspondence mapping), Displayr has built-in operations to create simple calculations from variables or tables.

You can read more about these functions here.

Built In Calculations

Create your own custom code

You can however go a lot further with custom code.  Point-and-click functionality allows you to select the specific inputs you need.  This can refer to:

• variables
• specific table cells,
• entire rows or columns and ranges.

See how easy it is to create your own custom code here.

Calculate Anything

Bespoke analysis functions

Displays allows you to perform the types of functions that people ordinarily do in Excel (e.g. Sum, Average, Count, etc.)

There are a range of examples here

Bespoke Analyses

Calculate Anything In Displayr!

Next time you find yourself in problem-solving mode with your data, find the solution with Displayr's suite of calculation functions.

1:  Have a document with your PowerPoint template ready.

This will typically be in Standard (4:3 or A4) or Widescreen (16:9) format.   Decide what format your new Displayr template is to be in.

2:  Open a blank Displayr document

From the Document page, select +New Document, check that the tab at the top is set to your desired format, then select ’Blank’

3:  Go to the Page Master and edit the Displayr defaults

In addition to a “Blank” page (which requires no editing), there are default layouts for Title Only, Title Page, and Title and various Content Layouts.

This is the key step – you basically need to change the titles, text box formats and default chart colors to reflect your PowerPoint template and paste in any graphical elements from PowerPoint.

You can duplicate and edit any of these pages if you want to add more master pages.

4:  Save your template using the required file naming conversion and download a QPack.

Publish > Export Data > Download Document (*.QPack)

Name the *.QPack as per these conventions (this is required for it to be read in when uploaded, in Step 6).

• Widescreen templates: [Template Name].widescreen.template
• Standard templates: [Template Name].template

Be case specific for the "widescreen" and "template" terms

5: Create thumbnail images of some of the key pages (optional)

This step enables you to see a preview of your template in the gallery when creating a new document, so it’s worth doing. These are also used in Step 6.

The file-naming convention for the first image to show in the gallery is:

• Widescreen templates: [Template Name] 1.widescreen.template.png
• Standard templates: [Template Name] 1.template.png

For second and subsequent images, replace the “1”, with 2, 3, etc.  Note, apart tom the name text before the number, these terms are case sensitive and there must be a space between the template name and the number.

 6: Upload the template *.QPack and related *.png files to your Displayr Cloud Drive

The Displayr Cloud Drive is accessed via the Icon at the top right of screen:

Shortly after this step you will see your own template available from the gallery of options when you create a new document (as per the “Burger Chef” example here).

The steps in action

This video works through the key steps.

Anyone with basic PowerPoint skills can easily set their own corporate or client templates up in Displayr.  Once done, your analysis and report build can always be “on-brand”, saving you time and producing better looking reports

Some use cases for instance:

• Identifying and removing rogue respondents (speeders, flat-liners*, inconsistent responses, etc.).
• Fixing up an error that was missed in the survey scripting process
• Pasting in matching variables from another source (typically Excel), to allow them to be included in the analysis.
• Publishing filtered versions of the data file.
• Publishing clean versions of the data file (i.e. without ‘created’ variables, hidden programming variables) for external client use.

Displayr’s raw data editing and publishing features have a lot of built in functionality. As a result the deliver to these needs, with ease.

* Tip: Displayr can automatically identify flat-lining or straight-lining (respondents giving the same answer for all questions in a set). It gives you a report on questions effected.  From the main menu select Anything > Reports

Accessing the Raw Data Editor

To open the Data Editor, select one or more variables (or combined variable sets) in the Data Tree, then right-click and select "View in Data Editor". Alternatively, there is a button in the Object Inspector with the same name if you have a variable/variable set selected. You can also use the button that appears on the preview tooltip when hovering over a variable or question. The Editor will appear at the bottom of the screen showing the raw variables that you have selected.

You can also drag more variables to it once open and drag-and-drop columns inside the Data Editor. As a result you can reorder them as you like.

Using the Raw Data Editor

Manipulating the table

The column headers contain the 'names' (not labels) of the variables. The row headers contain the Raw Case Numbers. The rounded bars above each column show which Variables are grouped into Variable Sets. To toggle between showing raw values or labels, use the control at the right of the header.

You can sort your data using the sorting icons in the column headers. The first time you click, that column will be sorted in Ascending order. The second time you click it will toggle to Descending and a third click will reset it to not be sorted. You can sort by multiple columns in the order you activate their sorting.

Editing

Values can be edited directly by double-clicking on a cell or pressing “Enter” *. Edited cells have a “flag” added so you know which have been modified.

In the Data Editor you can right-click on edited values and select “Revert” to restore the data to it's original state. You can also do this in the Data Sets tree for entire variables.

You can also copy and paste values or ranges of values within the Data Editor or copy to or paste from Excel. If you have one or more full columns of values in Excel, you can copy them, right-click on a column header in the Data Editor and select "Insert New Variable(s)". These are added to your Data Source in Displayr. You can then use the new variable(s) as you would any other in Displayr.

In this example, we temporarily copied “Postcode” from the Data Editor, pasted into Excel, used a LOOKUP function to assign a Geographic Zone code, and “Inserted” this in Displayr.  as a result it becomes available in the Data Sets tree.

* Calculated variables (e.g. JavaScript or R variables) cannot be edited.

Deleting

Firstly, you can delete individual rows (cases) by clicking on the row header. Use Ctrl-clicking to add more rows tor Shift-clicking to select a range of rows. Just right-click in a selections and select "Delete Row(s)".

Secondly, you can delete rows that match a filter using the control near the right of the header of the Raw Data Editor. Select an existing filter (or create one in the Data Editor) by selecting "New") and the matching rows will be highlighted in Green. Right-click one of the matching rows, then select "Delete Row(s) Matching Filter".

This example is from a large scale “Usage and Attitude” study, where we would expect the interview length to be an absolute minimum of 15 minutes. Survey length here is measured in seconds. We created a filter to select respondents with the equivalent of 15 minutes in seconds and these respondents are highlighted. We can easily now remove them from the data.

To restore deleted rows, select the data source in the Data Tree, then in the Object Inspector click "Undelete observations...".

Publishing (or exporting) edited data.

You can publish a data file that reflects the edits made - from the "Publish" menu (top of screen) select "Export Data" and then choose your format. Currently there are options for SPSS (*.sav) or Excel (*.csv) formats.

Use cases include for instance:

• If the original file required a lot of cleaning, you may want to export and use an updated version, for the purposes of project efficiency.
  You may want to (for example) break a multi-country study into country specific files.
• You may want a version of the file for your external client that has your workings and “programmed” variables hidden.

Read more about this here: Publishing Data Files

The complete package.

Displayr already features state-of-the-art advanced analysis tools, excellent table and visualization functions, and editable and updatable PowerPoint exporting. With the Data Editing feature, it is even more so the complete package, for all your survey analysis and reporting needs.

In my first post, we covered the 10 advantages of creating PowerPoint reports in Displayr. The second post outlined the steps required to create a PowerPoint in Displayr from scratch and introduced how you can update an existing PowerPoint document.

Creating a report template and automating it for future reporting is a great way of saving time and working more efficiently. But more often than not that's not the end of it. In the vast majority of cases, reports evolve over time. Requirements change and reports need to be updated accordingly.

In this post, I will show you to use Displayr to make changes to your PowerPoint reports.

More specifically, this post will cover:

• How updating works in Displayr
• Add new slides to an existing PowerPoint report
• Add new objects to an existing PowerPoint slide, and
• Linking objects created in PowerPoint to Displayr

For the purposes of this post, an object refers to a chart, table, text box, or an image created in Displayr.

How updating works in Displayr

Updating in Displayr is based on GUIDs (Globally Unique Identifier code). Every object that can be updated from Displayr is assigned a GUID. The GUID can be found in the Object Inspector on the right of your screen under Properties > GENERAL > GUID. If you wish to copy the GUID, select the output and go to Copy > Copy GUID.

During the initial export (see Create a new document) the GUID of each object is recorded in PowerPoint in the Alt Text field.

This field is accessed in PowerPoint by right-clicking on an object and selecting Edit Alt Text...

When updating an existing PowerPoint document Displayr compares and matches GUIDs in the Displayr document to those in the existing PowerPoint deck. When matched Displayr updates the content of the object, while preserving the original PowerPoint design. For example, Displayr will update the data in charts and tables, it will update text within a text box, but not change its positioning, font size, or color.

In case Displayr can’t match the GUID number it won’t export the object. Displayr will only update the objects found in the PowerPoint document, without adding or removing any objects from it. You can also remove a GUID from a PowerPoint object in case you don't want it to update (e.g. a Title text box).

Add new slides to an existing PowerPoint report

To add a new slide to your report follow the below steps. For more details on how to create a PowerPoint report in Displayr see the previous post in this series.

1. Add a new page in your Displayr document by going to the Pages menu and clicking on the + button that appears when hovering the mouse over an existing page.
2. Create a page of results.
3. Export the page to PowerPoint by going to Publish > Export Pages > PowerPoint > Export Selected Pages > Create new document > Export.
4. Copy and paste the slide in the exported document to your initial PowerPoint document

A GUID has been assigned to all the objects on the new slide linking them back to the Displayr document. To reiterate, any objects not present in your PowerPoint report will not get exported when Updating an existing report.

Add new objects to an existing PowerPoint slide

The process of adding a new object to an existing PowerPoint slide is similar to adding a new slide.

1. Create the object in Displayr, either by creating a new page or by adding to the page corresponding to the PowerPoint slide.
2. Export the page with the new object to PowerPoint by going to the Publish > Export Pages > PowerPoint > Export Selected Pages > Create new document > Export.
3. Copy and paste the new object to your initial PowerPoint report.

The exported object will have a GUID assigned which and can be updated at a later stage.

Linking objects created in PowerPoint to Displayr

In order to be able to link a PowerPoint object to Displayr the two objects need to match. For example, the layout of the data table within the PowerPoint chart will need to match the layout created when exporting a slide from Displayr. It might take a couple of tries to get it right.

1. Create an object in Displayr matching the PowerPoint object
2. Select the object and go to Copy  > Copy GUID.
3. In the PowerPoint document, select the object you wish to link, right-click > Edit Alt Text... > CTRL+V to input the GUID.

If you have any questions or need help you can always contact the technical support team by dropping them an email on support@displayr.com. 

Creating binary filters from selected data

When creating a single filter variable, you can simply go to Insert > Filter > New Filter and choose the appropriate category. However, repeating this step for each category can potentially be time-consuming. Instead, creating many filters quickly is as easy as selecting the relevant variables and going to Insert > Filter > Filters from Selected Data. This will produce a filter for each category in the source question. Note that if you merge any categories via the related table, they will instead flow through to these filters, and any that have been removed will be excluded.

The grouped filters will appear below the source question under Data Sets.

A second use for this function is when you have Binary - Multi (Compact) or 'Max-Multi' questions that you wish to convert to binary data. This will in turn produce a single variable for each category. You can then untick the Usable as a filter option in the output if this is not needed.

Creating combo and list box controls and filters

While it generally takes a few steps to connect filters to a control box, there are shortcut options available.

In this example, I have the following grid of bars chart showing preferred cola over time:

To automatically apply a control filter, you should do the following:

1. Select the output(s) and go to Insert > Filter > Combo Box (Drop-Down) Filters on an Output or List Box Filters on an Output. We will choose a list box.
2. Next, choose the single-response variables you wish to use for the filter. Here I have chosen 'D1 – Age' and 'D3 – Gender'. Note that for each question selected, a separate control box will be created.
3. If you are creating combo boxes, you will need to additionally select Yes to allow the user to select more than one category in each control box.
4. A new combined filter variable called 'List Box Filter D1 – Age + D3 – Gender' has now appeared under Data Sets:
   
5. 2 list boxes also appear on the page with the filter automatically applied to the chart:
   

Creating text box controls and filters

An alternative to a combo or list box is a text box filter. You can use this for filtering lists of verbatims or any other output for that matter. The process is almost the same via Insert > Filter > Text Box Filters on an Output except for 2 steps:

• In step 2 above you will only have the choice to select text variables for creating the filter.
• In step 3 you will be asked if you want the filter to ignore case, that is, it doesn't matter whether you use capital letters or not.

The result will be a text field that you can type into to filter the other outputs. In the below example, we have based our text filter on an open-ended cola awareness question. When we then type "cola" into the field, it automatically filters the text question and the chart based on those who wrote "cola" in their verbatim response.

Rebasing multiple-response data to the NET

There are often situations when missing value settings in your data set are incorrect for multiple-response questions due to respondents skipping the question. This can lead to the NET not being 100%.

In the below example, there are 11 records out of 725 which have no data so we want to rebase the question out of those who actually answered it. This can be easily rectified via Insert > Utilities > Create New Variables > Rebase Multiple Response Data in Variable(s) to NET. This option will create a new rebased question at the bottom of your Pages section and provide the option of hiding the incorrect version in the prompt.

Rebasing questions based on other questions

Data exports can often have limitations with how missing values can be set when questions are filtered within the survey. This can leave the data file with incorrectly based questions. Alternatively, you may simply want to rebase your data differently on awareness or usage, for example.

In the following example, we have a multiple-response grid, Q14, where the respondent was asked to identify what supermarket brands correspond to specific attributes.

The table is currently based out of total sample but we would like to base it out of Q8, that is, whether they have shopped at these stores in the past 12 months:

The steps to follow are below:

1. Go to Insert > Filter > Filter One Question by Another Question
2. When prompted, select the question you want to filter then press OK. We will select Q14 here.
3. When prompted, select the question to use as a filter then press OK. Here we will select Q8.
4. If the question to be used as a filter is tagged with Usable as a filter, you will be asked whether you wish to simply apply this filter (Yes) or create a variable for each category (No).
5. If the question to be filtered has multiple variables, you may be asked whether you wish to split each variable by the filter categories (Yes) or simply apply the matching filter (No).
6. If you want Displayr to automatically match up the filters based on the source labels, select Yes.
7. As our labels match perfectly, Displayr will generate a new version of our question with the correct basing called 'Q14 filtered by Q8 Visited last 12 months':

The table looks like this:

6. Note that if you select No in step 4 or there are inconsistencies with labels and/or additional items, you will need to manually select the variables that correspond to each filter category via the prompts.
7. You can then choose whether to keep or remove the extra items that were not matched.

To avoid these extra steps, you can simply adjust the variable labels under Data Sets to provide consistency. If the difference, however, is only that the filter question also includes a "None of these" option, the easier solution is to copy this question via Home > Duplicate, go to DATA VALUES > Values, and set this option to Exclude from analyses. Now you can use this question instead and the items will match.

Note that, much like with the Filters from Selected Data option, here Displayr will also respect any merged or removed categories when creating the new variables.

Filtering variables

A second use case for Filter One Question by Another Question is for filtering your variables to allow for a 3-dimensional table.

Below is a table of how likely respondents are to recommend buying fruit and vegetables as an average crossed by the last supermarket they visited.

Although these 2 questions are easily crossed, you may still want to cross break the table further. This is where this script comes in handy.

As with the first few previous steps, you simply need to do the following:

1. Go to Insert > Filter > Filter One Question by Another Question
2. When prompted, select the question you want to filter then press OK. We will select 'Q12 Fruit & Veg'.
3. When prompted, select the question to use as a filter then press OK. Here we will select 'Q10 Last visited supermarket'.

The result is a simplified table which can now be further filtered by applying a banner question, such as gender:

Splitting sample

Displayr also offers you an automated solution for splitting your sample for predictive modeling such as regression.

The first option via Insert > Filter > Filters for Train-Test Split randomly creates a training and a testing filter. This defaults to a 70% / 30% split but you can change this in the prompt.

The second option via Insert > Filter > Filters for Train-Validation-Test Split randomly creates a training, validation, and testing filter. This defaults to a 50% / 25% / 25% split but you can likewise change this in the prompt.

Another use for this function is for effectively removing additional records from your data set if you have gone over your survey targets. In this case, you could use the Filters for Train-Test Split option and set the training sample accordingly.

If you wanted to remove 5% then you could use either 95 or 5 for the prompt and choose the appropriate filter:

This results in 2 grouped filters at the top of your data set:

This allows you to choose what table dimensions should be included in the final output without having to make changes to the source table. If you wish to display a table instead, referencing your source table via a Paste Table (Autofit) R output provides the same manipulation options.

Let's now go through the different types of filtering possible under the Inputs > ROW MANIPULATIONS and COLUMN MANIPULATIONS sections of these outputs.

Remove rows and columns with no data or small sample size

1. Hide empty rows/columns
This option removes any row or column that has no data in it.

2. Hide rows/columns with small sample sizes
Instead of only removing blank data, you can also specify a Sample size cut-off to remove rows and columns that do not meet this threshold. Note that the statistic used for sample size will be based on your source table, so Column Sample Size, Column n, Sample Size, or Base n must be included.

Display fixed rows and columns

3. Select rows/columns to show by > Type row names or indices
If you wish to show only specific rows/columns then you can list either the name or index number of the desired row/column under Rows/Columns to show, separating each item by a comma.

4. Rows/Columns to ignore
By default, NET, Total, and SUM are set to be ignored from your output but you can change this or add to the list by referencing the name of the row/column, again separating each item by a comma.

Display dynamically selected and auto-updating rows and columns

5. Select rows/columns to show by > Choosing from Combo Box or List Box control
When you have numerous brands or statements in a table, you often want to let the viewer select the items they are interested in via a Combo Box or List Box. This option will work seamlessly with any visualization or pasted table output when you select the appropriate control box under Rows/Columns to show. The result will be an output that automatically changes what data is displayed based on the user selections.

6. Number of rows/columns from top/left to show
If you have additional rows/columns in your source table and only want to show the first 6, for example, then setting this to 6 will always show these rows/columns even if your data updates. In this example, only 'Coca-Cola' to 'Pepsi Max' have been included from the table rows.

7. Number of rows/columns from bottom/right to show
This option is the same as the above but works the opposite way. If you have quarterly time series data and you want to only show the last 2 quarters i.e. the last 2 columns of your table, setting this to 2 will restrict the output to only show these columns. If your data then updates with additional months, this option will automatically adjust.

The idea is to get the vast majority of analysis and data outputs created in Displayr before exporting the document to PowerPoint and finalizing the report. I will also show you an easy way to make changes and update your PowerPoint reports.

This approach can be used to create one-off reports quickly and efficiently, but it's particularly powerful for setting up and automating projects that require regular reporting, such as tracking studies or multi-country projects.

Depending on the design requirements you can either create a new Displayr template or use an existing template. Alternatively, you can skip this step and instead use a PowerPoint template. In the below example I will use the latter approach. All you need to get started is a Data Set and a PowerPoint document template.

Step 1: Create a new document

• Create a new Displayr document
• In the Ribbon, choose Insert > New Data Set and select the data file you wish to use.

Step 2: Create a page of results

• Create a page of results

In the example below I created a page containing demographic information. I created three different charts for Gender, Age, and Region.

Step 3: Change the PowerPoint export format settings

By default, charts will be exported to PowerPoint as static images. However, once exported to PowerPoint I want to be able to edit the charts.

• To change the default setting and export all charts as editable charts, I need to change the export settings by selecting the chart and going to the Object Inspector > Properties > POWERPOINT EXPORT > Format and selecting Microsoft Chart.
• Next, I want all the charts to be exported using the style of charts selected in Displayr. I can do this by changing Export as under Properties > POWERPOINT EXPORT > Export as to Match Displayr.
• To apply the change to all charts in the document, I selected Set as default.

Note, if I selected a specific chart type, such as 3D Pie, from the Export as menu and then clicked Set as default, all charts in the document would be exported to PowerPoint as pie charts.

Step 4: Export to PowerPoint

• Select Publish > Export Pages > PowerPoint > Create new document > Export.

Displayr will export the page as a PowerPoint document placing each page of the Displayr document on an individual slide. In this case, I have exported only one page, resulting in one PowerPoint slide. The slide consists of the text box and three editable charts.

Step 5: Transfer the slide to your PowerPoint template

The exported PowerPoint document matches the design and layout of the Displayr document. However, I wish to use a different PowerPoint template. As mentioned earlier, it is possible to set up a specific template in Displayr, but for the purpose of this post, I want to show you how simple it is to use a pre-existing PowerPoint template, such as your company’s or your client’s template.

To do that, I opened my PowerPoint template and copy-pasted the slide from my exported document to my template. By default, PowerPoint inserts the slide using the Destination Theme Paste option – applying the template design. In our example, the chart colours changed.

Step 6: Modify the slide in PowerPoint

For this particular example, I have resized and moved the charts around. I also removed the question text and base information, hiding the ‘Less than 18 years’ data series, and changing the Chart Type designs in PowerPoint.

Whilst I could have done most of these changes in Displayr, the aim of this example is to show that this can also be done in PowerPoint without losing the ability to update the charts at a later time and keep the design intact. My PowerPoint slide now looks like this:

Step 7: Making changes to the PowerPoint report

Now, let’s say that we wish to make a change to our report and show Region and Age split by Gender. I could do this by going to my data tables, finding the data, and manually adding it to the PowerPoint chart. After all, we can edit the chart exported from Displayr.

But there’s a better way: I can make the change in my Displayr document and Displayr will update the report for me.

To make the change, I returned to my Displayr document, selected my Region chart, and added Gender by going to the Object Inspector > Inputs > DATA SOURCE > Columns.

I then repeated the same process for my Age chart to get the below output.

I also updated the title text, adding the words by Gender, to reflect the updated charts.

Step 8: Updating the PowerPoint report

To update the PowerPoint report, go to Publish > Export Pages > PowerPoint, but this time instead of creating a new document I selected Update existing document. I then dragged and dropped my PowerPoint document created in Step 6 into the blue box and clicked on Export.

Displayr updated the document and a pop-up window appeared containing information on the changes made.

In this example, Displayr updated the text box and three charts as per the below. The updated document reflects all the changes we made to our document during the previous step.

The approach outlined above has a wide range of uses from running analysis and creating a single PowerPoint report to full-scale automation of PowerPoint reporting.

In the next blog in this series, I will show you how to make changes to your PowerPoint reports built-in Displayr.

If you have any questions or need help you can always contact the technical support team by dropping them an email at support@displayr.com. 

Modifying your simulator

In our example, we have created a basic simulator with 3 alternatives:

There are various ways of modifying your simulator, including weighting and making adjustments to reflect market share. Here, we intend to add a combo box for filtering our preference shares by a specific survey question. We will use likelihood to travel in the next 10 years.

Connecting your simulator to a combo box

The best location for this combo box is on the Page Master which is accessible via Appearance > Page Master. This will allow the same control to appear on every page using this template while retaining the user selections.

We can create our own title page by selecting Title Only and pressing Home > Duplicate. We will rename this 'Page with Combo box'.

To add the control item, go to Insert > Control > Combo Box. We then connect Items from to an existing table for likelihood to travel. Alternatively, you can just paste the label options separated by a semi-colon into Item list. In this case, we will also need to delete the default items there. Next, we change Selection Mode to Multiple selection. You can also optionally change the name under Properties > GENERAL.

We can now go back via Appearance > Normal and change the simulator page via Home > Layout > Page with Combo box.

With Displayr, you can easily filter data using a combo box with an R variable. As we are using a single-response question but wish to allow multiple selections, we need to first make it binary via Insert > Filter > Filters from Selected Data. You should then select the appropriate respondent data file under Data Sets and go to Insert > R > Numeric Variable. For a multiple-response combo box, the filter formula to use in the R CODE field is as follows:

rowSums(`Question_name`[, combo_box_name, drop = FALSE]) > 0

The Question name can simply be dragged over to this field from Data Sets to look like this:

rowSums(`Q3: How likely is it that you will take a cruise vacation sometime in the next 10 years? - Filters`[, Combo.box, drop = FALSE])> 0

This code will filter Q3 to the items selected in 'Combo.box'. It will then only include the respondents who fall into these categories.

Next, tick Usable as a filter. We will name this 'combo.filter'. Now you can go back to your simulator page and apply 'combo.filter' to your 'preference.shares' output under FILTERS & WEIGHT > Filter(s).

Below is the formatted version of our simulator:

Weighting your data by alternative-specific respondent preference shares

Displayr allows you to complement your simulator with further visualizations that help tell the story of your data. One way to make further use of our simulator is to weight our demographic questions by a selected alternative's preference share results.

We will begin by making a new page with the same default combo box via Home > New Page > Page with Combo box. We will now copy the 'preference.shares' output from the simulator page via Home > Duplicate and drag it over to the new page to get the respondent-level results.

First, we need to remove the combo box filter from the output. We then need to paste the below code at the bottom of Properties > R CODE:

preferences.by.respondents = data.frame(matrix(resp.shares, ncol=3))
colnames(preferences.by.respondents) = c("Alternative 1","Alternative 2","Alternative 3") 
preferences.by.respondents

You will need to change the 'ncol' reference and column names to match the number of alternatives in your simulator.

The next steps involve creating the combo box filter. In the menu ribbon, select Insert > Control > Combo Box and paste Alternative 1; Alternative 2; Alternative 3 in Item list. I have named this combo box 'cCruise'.

Next, create the filter variable via Insert > R > Numeric Variable and paste the below into the R CODE field:

preferences.by.respondents[, cCruise]

This code will filter 'preferences.by.respondents' by the alternative number selected in 'cCruise'. Once you tick Usable as a weight, this can be applied to your outputs under Inputs > FILTERS & WEIGHT > Weight.

This allows you to add visualizations for various demographic questions with the combo box filter and weight applied to the source tables. Remember to drag the tables off the page and select Appearance > Hide. You can also use a variety of conjoint-specific visualizations, such as a demand curve for the price attribute.

Creating an optimizer

An alternative to creating an online simulator is to create what we call an 'Optimizer'. Unlike a simulator, an optimizer allows multiple selections per attribute and generates multiple-preference share combinations at the same time.

To create an optimizer, you can either select your conjoint analysis output and click Inputs > SIMULATION > Create optimizer or go to Insert > More > Conjoint/Choice Modeling > Optimizer from the ribbon. You will need to then specify the number of alternatives and whether you wish to include alternative-specific attributes. We will choose 3 here and disregard the alternative attribute. This will create a page called 'Optimizer'.

Similarly, we will also apply our combo box filter to the preference share output on this page.

Again, you can format the page objects as desired. In this case, an Autofit table provides more flexibility for the summary preference share table as you can easily drag the edges to align with the optimizer's columns. You can create this via Insert > Paste Table, ticking Autofit, and selecting this page's preference share output under DATA SOURCE.

Due to the varying size of the table, we can fix the height to ensure it adds a scroll bar. We will add row.height = "15px", to Properties > R CODE where the row specific fields are.

We can now select the original output, drag it off the page and press Appearance > Hide to ensure it remains hidden from the published version of the document.

Using your optimizer

One specific use case for the optimizer is fixing the options for the second and third alternatives while selecting multiple options for the first alternative. In the first column, we will select all the options under Room, Amenities, and Price to generate the 30 combinations for the multi-selected combo boxes.

A benefit of autofit tables for this scenario is we can automatically pre-sort the table from highest to lowest by the first column. Simply go to Inputs > ROW MANIPULATIONS, tick Sort rows, place '1' in Column used for sorting rows, and tick Sort in decreasing order.

You can see the finished document here.