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Small mistakes can have big implications for how respondents understand and interpret the questions you ask, which can, in turn result in poor data quality. In this video I provide some tips for better survey design.

Last week I was on a tech/startup podcast called Pitchdeck Asia with the CEO/Founder of the start-up I work at, hosted by Graham Brown. During the episode we cover everything from how business needs are changing in relation to data analytics, to how our startup is navigating building a business in a post Covid-19 world.

With the world on lockdown as a result of Covid-19 one thing I’ve noticed over the last few months has been a steep rise in interest for charts and data visualization. And in today’s post I break down some examples of both good and bad dataviz related to Covid-19.

It’s been a while since I last posted here, and I’ve realised that my last post (This is How Data Kills Creativity) ended on something of a negative note. So today I wanted to switch things up by sharing a few examples of how data can actually inspire creativity.

In my latest post I look at a recent article published on LinkedIn that claimed to have found the secret sauce for understanding how content goes viral on LinkedIn. The article featured some rather questionable math, and in this post I break down exactly what went wrong and why.

A few years back after the release of Star Wars: The Force Awakens I wrote an article detailing the box office success of each Star Wars film during their first week of screening. So I thought it would be fun to refresh some of the numbers as well as look at total box office success rather than just opening week.

What are the different types of rating scales in online survey-based research, and how can you use them effectively? In this article, I’ll take you from A to Z and teach you how and when to use rating scales when designing a survey.

In this article, I examine some real-world examples of online survey design gone wrong. I’ll breakdown some common issues when it comes to designing surveys and how you can avoid making the same mistakes.