A step forward in data analysis
Use Cases and Deployment Scope
Displayr is our essential, primary analytics tool at [...]. Having Displayr enables us to more quickly and efficiently crunch the numbers that underpin the commercial insights and advice that we deliver to our clients.
Without having to know a single line of R code, we're able to handle the important data basics (like data cleaning, setting up weighting, basic tables) quickly, so we can then get into the higher value-add analyses that unlock the power of survey data.
Pros
- The intuitive interface and menus make it easy to quickly learn Displayr and find the types of data transformation or analysis that we're looking to do.
- The support level from Displayr's team is FIRST CLASS. Where othe platforms force you to an FAQ or AI chat bot, Displayr's team will jump in first hand, into our data, or on a live call, and help us run a new type of analysis or troubleshoot a problem.
- The ability to work collaboratively, asynchronously and remotely, on the same data set and report is a really huge plus for us.
- The in-built options for multivariate analysis cover 99.9% of anything we have - or will - ever need to run.
Cons
- The new "glow-up" on the interface has helped make it a bit easier on the eye, but there are some features of working in the "three pane" browser that are a bit frustrating: especially having to 'rearrange' when resizing the window to look at another app simultaneously.
- Such a small point, but being able to drag and move multiple elements in a table (eg drag two rows to the top) SIMULTANEOUSLY would help a bunch.
- I don't think we take advantage of all the visualisation capabilities in Displayr, and perhaps an AI 'recommendation' engine that sees the data I'm working with and prompts either a specific visualisation, or additional analysis option I might use, would be great.
Likelihood to Recommend
Displayr is perfectly suited for any insights or data people that understand the type of analysis they want to do, but don't know R code - or just want to get to results more quickly than coding themselves.
It's probably not the best learning ground, if you've never done any quantitative analysis before, but then neither are traditional tools like SPSS or Q.
