4 Visualizations For Your Customer Satisfaction Data

Customer satisfaction is a valuable customer feedback metric. Here are the four visualizations to find stories in your customer satisfaction data.

How to Filter a Dashboard Based on User Logins

You can restrict what people see on a Displayr dashboard based on their department, geographic region, or some other user characteristic. For example, you can...

What is Driver Analysis?

Driver analysis, which is also known as key driver analysis, importance analysis, and relative importance analysis, quantifies the importance of a series of predictor variables...

8 Tips for Interpreting R-Squared

Hopefully, if you have landed on this post you have a basic idea of what the R-Squared statistic means. The R-Squared statistic is a number...

How to Dynamically Change a Question Based on a Control Box

Control boxes are a popular way for users to change things on a Displayr page. This post will show you how to use a control...

How to Interpret Logistic Regression Coefficients

This post describes how to interpret the coefficients, also known as parameter estimates, from logistic regression (aka binary logit and binary logistic regression). It does...

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How to Interpret Logistic Regression Coefficients

Sample Size for Conjoint Analysis

Working out the sample size required for a choice-based conjoint study is a mixture of art and science. What makes it tricky is that the…

7 Questions for Those Considering Predictive Lead Scoring (+ Free Checklist!)

It can be confusing to work out if predictive lead scoring is suitable for your company. In this article, I pose seven question for you...

Who is Predictive Lead Scoring For?

You might be reading about predictive lead scoring and wondering if it's something that's right for you. It can sound a little daunting and something...

Customer Onboarding for SaaS

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How to Control Who Can View your Documents in Displayr

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How to Control Who Can View Pages in your Document

On larger projects, you may need to build reports or dashboards that contain results relevant to different groups of people. For example, your customer satisfaction...

CSAT vs NPS: What’s the Difference?

You've probably heard of Customer Satisfaction scores, which measure how satisfied customers were with their experience with your brand. You've also probably heard of the...

4 Reasons Why You Should Be Measuring your Net Promoter Score

There are many reasons why you should be measuring your company's Net Promoter Score.

What is Customer Satisfaction?

If you've ever purchased anything, you've likely come across the Customer Satisfaction Score. It's everywhere, from online stores to airports to dentists' offices. But do...

What’s in the Future for Predictive Lead Scoring?

It was only a few years ago that people were proclaiming that the future of B2B marketing had arrived in the form of predictive lead...

What is the Net Promoter Score (NPS)?

The Net Promoter Score (NPS) is one of the most commonly used customer feedback metrics. With a single question, you can measure customer sentiment and...

What is Predictive Lead Scoring?

Predictive lead scoring is a data-driven lead scoring methodology that uses historical and activity data and predictive modeling to identify the sales leads that are...

6 Ways to Improve the Data Quality of Online Quantitative Surveys

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Make Beautiful Tables with the Formattable Package

I love the formattable package, but I always struggle to remember its syntax. A quick Google search reveals that I’m not alone in this struggle.…

Writing a Questionnaire for a Conjoint Analysis Study

The hard bit of designing a choice-based conjoint analysis (choice modeling) study is creating the experimental design. However, there are a few others parts of...

Main Applications of Conjoint Analysis

Ready to dive further into conjoint analysis? In this post I describe the main applications of choice-based conjoint analysis (choice modeling; CBC).

Conjoint Analysis: The Basics

Choice-based conjoint analysis is a technique for quantifying how the attributes of products and services affect their performance. It is used to help decision makers...

What is Sampling Error?

When data is randomly sampled from a population, the randomness with which observations are selected from the population ensures that the value of statistics computed...

How to Extract Column Comparison Letters into a Table Automatically in Q using R

In recent posts weâ€™ve discussed how you can reference source tables using R in Q to manipulate the statistics into a new custom table. In…

How to Embed a Video in a Displayr Dashboard

You can have a video playing on a page in Displayr, as it’s very simple to set up. The video needs to be hosted on…

Building an Interactive Globe Visualization in R

This post describes how to use the threejs package to plot data on a globe, allowing rotation and zoom. Location markers are added as lines,...

Comparing your Results to the Previous Period in Q

Q has a terrific feature whereby it can automatically compare statistics against the previous period (of time). This is great for tracking scenarios, when you…

Tips for Recoding Missing Values in Q

Missing valuesÂ in a data set are “blank” values. They are normally associated with survey skips. Those who skip a variable/question receive a missing value. Missing…

How to create a HEX color palette for Displayr

While most visualizations have built-in color palettes, more often than not you'll want or need to customize them. Having a color palette set up BEFORE...

Using Q to Make a Snake Plot in PowerPoint

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How to Control Who Can Edit Documents in Displayr

When you have a larger set of people at your organization using Displayr, it can become necessary to define which people are allowed to work...

Focusing the Results of Correspondence Analysis in Displayr

Correspondence analysis is often used to visualize a table of data. The goal is to represent as much information as possible, as accuratelyÂ as possible. However,...

How to Make a Histogram in Q

Histograms may look like bar charts, but they plot data in an entirely different way. While bar charts depict the frequency of occurrences, or averages,...

What is a Latent Variable?

A latent variable is a variable that is inferred using models from observed data. For example, in psychology, the latent variable of generalized intelligence is...

Decision Trees Are Usually Better Than Logistic Regression

If you’ve studied a bit of statistics or machine learning, there is a good chance you have come across logistic regression (aka binary logit). It…

This post describes how to interpret the coefficients, also known as parameter estimates, from logistic regression (aka binary logit and binary logistic regression). It does...

What is Feature Engineering?

Feature engineering refers to a process of selecting and transforming variables when creating a predictive model using machine learning or statistical modeling (such as deep...

Feature Engineering in Displayr

Feature engineeringÂ refers to the process of manipulating predictor variablesÂ (features) with the goal of improving a predictive model. In this post I outline some of the…

Feature Engineering for Categorical Variables

When creating a predictive model, there are two types of predictors (features): numeric variables, such as height and weight, and categorical variables, such as occupation…

How to do Logistic Regression in Displayr

In this post I describe how to perform a logistic regression in Displayr. I illustrate the basics using a data set on customer churn for...

Feature Engineering for Numeric Variables

When building a predictive model, it is often practical to improve predictive performance by modifying the numeric variables in some way. In statistics, this is…

How to Interpret Logistic Regression Outputs

Logistic regression, also known asÂ binary logitÂ andÂ binary logistic regression,Â is a particularly useful predictive modeling technique, beloved in both the machine learning and the statistics communities. It...

How to Create a Heatmap in Q

Heatmaps are a powerful visualization for depicting the distribution of data. Unlike traditional charts, like bar charts or pie charts, heatmaps are represented by matrices....

How to Create a Correlation Matrix in R

A correlation matrix is a table of correlation coefficients for a set of variables used to determine if a relationship exists between the variables. The…

How to Make a Column Chart in Q

The most standard way for graphically representing categorical data is with a column chart. The advantage of using column charts is that you can easily...

How to Create a Density Plot in Q

A density plot is a smoothed histogram. Like the histogram, they are used to visualize the distribution of numeric values. A smoothing algorithm is applied...

How to Make an Area Chart in Excel

An area chart is based on a line chart, with the area between the line and the x-axis colored to illustrate volume. In this post,...

How to Make an Area Chart in R

Area charts are useful for visualizing one or more variables over time. We can create area charts in R using one of the many available...

What is Non-Sampling Error?

Non-sampling error refers to any deviation between the results of a survey and the truth which are not caused by the random selecting of observations....

How to Make a Heatmap in Excel

Any large table of data with lots of numbers becomes difficult to read. As a human, you'd have to process each number and then compare...

How to Calculate Sentiment Scores for Open-Ended Responses in Q

Sentiment analysis is a way to quantify the feeling or tone of written text. In a survey context, this is a useful technique for gauging...

How to Make a Density Plot in Displayr

Density plots can be a great tool for trying to understand the shape of the distribution of some data. They do not plot the data...

How to do Simple Table Manipulations with R Using Displayr

R is not just a tool for the data science elite. It is an immensely powerful tool that can be used by market researchers in...

How to Export Updatable Text to PowerPoint from Q

Most Q users would be familiar with Q's PowerPoint export options. The normal option allows you to export your tables to PowerPoint and create charts...

How to Make a Geographic Map in Q

Geographic map visualizations are a great way to show comparative values across countries, states, or regions. The geographic map shades the color of each location...

5 Alternatives to the Default R Outputs for GLMs and Linear Models

One of the ironic bits of using R is that even though it is often described as being a great tool for data visualization, most...

How to do Traditional Correspondence Analysis in Q

Correspondence analysis is a data analysis technique which summarizes the patterns in a table of data as a visualization. Tables with more than a handful...

How to Create a Heatmap in Displayr

Heatmaps are a great way to pick up patterns in tables of data. The heatmap represents the table by shading the cells according to the...

What is Survey Data Processing?

Survey data processing is the crucial step that follows the collection of any survey data. The aim of data processing is to manipulate or transform...

How to Create a Box Plot in Displayr

Box plots are used to display the median, interquartile range, and outliers for a set of numeric data. They let you focus on the characteristics...

What is a Conversion Rate?

A conversion rate is the percentage of people or companies that move from one stage to the next stage in a process. Common examples include...

How to Make a Radar Chart in Excel

Radar charts are a great way to visualize two-dimensional data and show the differences between sub-groups. Think of them as a line chart that's been...

How to Create a Pie Chart in Q

One of the most basic and widely used visualizations is the pie chart which has been around since 1801! Pie charts are very effective when...

Extracting Results from Tables as R Outputs

This post describes how to extract results from tables in Displayr. The results are extracted as R Outputs. These R Outputs can then either be...

What is a Model?

A model is a usable description of how a system is believed to work. It is a simplification of reality, with unnecessary detail excluded. Good...