Insights from Ratings

Improve your Tableau dashboard with new WriteBackExtreme form fields


Do you work with many Tableau Dashboards? Are you concerned about the user experience part of the dashboards? What if there is a functionality within Tableau to collect user’s cognitive experience to different types of dashboards where we can build insights from people’s opinions and attitudes? What if we can use these insights in an effective way to boost the impact of your dashboard by making informed decisions?

The new WriteBackExtreme Tableau extension comes with an effective feature which can answer all the questions above – “Ratings”.

The ratings feature is an effective way to collect information about people’s opinions and understand their thoughts on products and services. A simple understanding / attempt to collect and interpret will lead to valuable insights. When a Tableau dashboard user starts giving feedbacks as ratings/reviews through a more interactive form fields instead of just text, it will make a huge jump in the usability of the dashboard by forming a new way of communication between the dashboard user and the dashboard designer. Similarly, this effective mode of communication can be used to address a diverse set of collaboration scenarions to improve dashboards so people use them more and better. Go from good to great and make more impact!

This blog mainly focuses on the introduction to the methodology part. We will show you ways to effectively utilize ratings and it’s ability to understand and synthesize information from Rating Scales, thereby empowers decision making in an ever-changing environment.

So, let’s start with a small idea – “Insights from Ratings” – and make a huge impact!

Rating Scales – What are they?

Rating scales can take many forms, from star rating to a slider. So, a rating scale usually holds responses from the users to a close ended question. So, in general, rating scales are instruments to measure properties which are not physical in nature, for example opinions and subjective interpretations. Such measurements are very important to understand an ever-changing environment. At the same time, it comes with challenges like the complexity of such measurements, as they are abstract and often cannot be summarised with a single question or rating. Instead, we need a series of questions covering different aspects.

This blog covers a simple case study on effective usage of the new ratings feature that comes with WriteBackExtreme. It emphasises the importance of the new cool feature which can add a ton of value to your existing processes!

Basic concepts to effectively utilize rating scales

To make the data collection process through ratings effective, a very general understanding of ratings scales will be beneficial. Also, dealing with cognitive information is tricky on many occasions so it’s always a good idea to segregate the information into different categories.

First, we can divide the ways to capture data into four different statistical measurement scales.  These scales define the kind of data being captured. The four scales are Nominal, Ordinal, Interval, and Ratio. The choice of levels is purely up to the user and the kind of information the designer wants to gather. Click here for more details.

Furthermore, there are other considerations which we should  take into account while working with rating scale measures. The most important one among them is that an individual item is not a measure of the overall interest.  At the same time, a group measure will not necessarily convey information regarding the individual level. Another question which arises is whether data is continues or discrete.  Rating scales with numerical inputs which can also be considered as a continuous data if the number of categories is high. In rating scale, the number of categories plays a role in the way the user responds. For example, rating response with less categories (less than 4) creates a biased responses from the users, and the responses may appear in intervals.

If you are planning to dive deep with the ratings data, a statistical validation always is a good idea to investigate concepts and modelling strategies like analysis of covariance, linear regression, or the basic ANOVA. Elaborated descriptions about the usage data types like nominal, ordinal, scale, interval, are beyond the scope of this blog, as this is a mere introduction to advanced use case of the new form field addition to our product WriteBackExtreme 1.4.

Curious to know more? Learn how to create a feedback form in WriteBackExtreme in this tutorial! Would you like to hear more about the WriteBackExtreme extension and its features or do you need support related to building similar studies/use cases? Visit our WriteBackExtreme page!

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