Dapresy Pro 2018 May Release
Our extensive May Release brings a lot of new features and improvements to Dapresy Pro. Supporting of R.I.M weighting, easier way of handling brand tracker questionnaire and what we take most pride in, the new My Stories module which allows to create report decks based on any slide or filter combination in a Storyteller.
We also want to inform about data cleaning and recoding functionalities to make it easier for our users to meet GDPR guidelines.
Customer Experience Studies
Data Cleaning and Recoding
- Include filters based on Open ended variables such as email addresses etc. which makes it easier to clean and recode data for specific persons which is relevant with the new GDPR anonymization regulations.
- Recode data permanently, this in combination with for example the ability to recode data automatically after a certain period of time makes it easy to permanently remove personal information from the data which is a requirement for the data minimization and data retention GDPR policies.
- Delete respondents to meet the GDPR right to be forgotten rules.
Compute and Input Variables
- Use floating time periods in expression when computing categorical variables like, for example, “Last 2 months”. The update makes it easier and more efficient to make special comparisons like “Latest month” compared to “Same month last year” without having to do any manual updates when new data is loaded in a tracker.
- Improved logic when computing numeric variables based on dates, the update is used in client follow-up processes as it makes it easier to get data for the number of days an alert has been in a certain step (like New, In progress, Closed etc.)
Use multiple filters in Events which makes setup more efficient in, for example, the case of having the need to filter the alert send outs by both geographical location and different touch points like Sales and Service.
New support for
- using Respondent data tables in Forms makes the setup of a Form faster and easier to get correctly aligned layout.
- viewing and analyzing the “customer history” in a Form when the same person/client participated in the survey multiple times. With this new function it is easier to view and analyze the history of the person/client before making any follow-up actions.
Here we see an example where the Respondent Data table object has been used in a Form. Cell formatting is used to color the Recommendation score and as shown the user can open a second Form report to view even more information about the respondent.
Respondent Data tables (Storyteller and Form)
- New padding settings which makes it easier to create an airy and clean layout.
- Display the Factor average instead of the answer text/answer id when using categorical variables in the Respondent data table. This is useful in case of for example having rescaled a 1-5 point scale to 0-100 point scale by using the factor average.
Storyteller charts and tables
New hierarchical filter sorting option, sort by branch or by level, which is useful when multiple units from different levels are selected to get the desired sorting in charts and tables
Brand Tracking Studies
My Stories – a new module
The My Stories tool allows end users to create their own report decks based on any slide and filter combination in the Storyteller reports. My Stories is a personal report library that is automatically updated each time new data is added. For example, with My Stories a product manager can build an “Executive Summary” deck to present online during a meeting, or download to PPT for email distribution.
The image shows a Storyteller report and the My Stories panel to the right. The panel is used to save and manage Stories and slides.
- The data weighting module now supports R.I.M weighing (Random Iterative Method). The R.I.M. weighting logic allows for the application of weight on multiple variables in the data so that after a predefined maximum number of loops it matches the target value of all of selected variables.
- Improved support to handle weight calculations when actual distribution is zero respondents.
- New ability to include filters when creating weight variables which is useful if, for example, different countries need different target distributions.
- Improved interface for creating weight variables.
Here we have an example of the weight table when the R.I.M method is used, as shown the Target distributions are setup individually per variable (Age and Gender in this example) and Country has been used as filter which allows different targets per Country.
Stacked Data Support
Stacked data can now be import to Dapresy Pro which makes it easier to especially handle brand tracker questionnaires where the same question, like brand statements or campaign follow up questions, are present multiple times which is a common case when the respondent evaluates multiple brands or different campaigns.
The tables show how a more report friendly data structure can look like which now can be imported to Dapresy Pro. The data has been split up in two files, the “normal” file and a stacked file for all the statements. In the stacked statement file you see that each respondent is present in multiple rows as the respondents answered the statements for multiple brands.
New ability to use floating time periods in expression when computing categorical variables like, for example, “Last 2 months”. The update makes it easier and more efficient to make special comparisons like “Latest month” compared to “Same month last year” without having to do any manual updates when new data is loaded in a tracker.