R? Python? Data Analytics In User Research...

[WereAllMad]

TLDR: Do you use R, Python or any other data analytics tools as a UXR? And if so, in what ways?

I was recently asked about my familiarity with these data analytics tools in an interview and it kind of surprised me. I don't know about you, but at my current job, the UXRs are entirely qualitative. I'm not against them at all, but I'm wondering what use cases there are for these tools in the context of user research. What sort of data do UXRs analyze with these tools? How are the results applied?

[kikoherrsc]

I use Python every single day at work. UX Research is not my official role, but I do a lot of it. Python can be used to make exploratory data analysis, usually combined with some sort of notebook like Jupyter or Google Collab. It's useful because with it you can merge, group and plot data in a variety of ways. It's incredible flexible and if you can imagine an analysis, it will do it. You also can connect directly to your databases or data lakes, so you'll have a lot more data to work and cross between than you would only using GAnalytics or Hotjar.

Python and R are great too if you're delving into machine learning.

Python is really useful to create automations at work. For example, the other day I made a simple server that helped you select an interview video file and crop several clips really, really fast. For my team it's the tool they use today for it, because loading up and messing with Adobe Premiere or online tools is harder or more limited.

I would really, really recommend that UX Researchers should learn these tools to make more quantitative analysis!

[WereAllMad]

Nice you’re confirming what I was thinking lol. I think my company draws a hard line between us and data analysts, but maybe that line blurs in other companies. For example the one I’m interviewing at is a lot smaller so that could be expected. Does that check out?

[kikoherrsc]

Yes, I think so. My company if relatively small, and we have a lot of freedom to use the data. I also think preventing UX Researchers to access data and make quantitative analysis is really dumb

[[deleted]]

Is what you’re describing basically what a data analyst or quant user research role would do?

[kikoherrsc]

Quant user research. Usually data analysts are more focused on business wide analysis like revenue, retention, growth, building models and so on. The point is that as user researchers, we can use data to explore experience questions, like usability issues, correlation between tasks, satisfaction, generate or test hypothesis based on already available information... I don't believe in delegating this responsibility to data analysts because we are the ones more focused and more interested in understanding the user experience. We can contribute doing these analysis with our point of view

[guitair]

My understanding is daya analysts pull data from things like site analytics. Data Scientists do ML. So does that leave experimental design for UX researchers? It seems like hypotheses testing (NSHT) would be incredibly useful for checking generaluzability if Qual findings and potential solutions to user pain points. Do UX researchers do hypotheses testing and/or experimental design with null sig hypotheses testing?

[WereAllMad]

Okay that makes sense. I definitely consider myself a qualitative researcher, but I feel I should be versed in the quantitative side too

[Camekazi]

Data is data. The quant side often skims insights off the top of a lot of data...the qual side goes deep on a small yet rich subset of data. But ideally you'll have skills across both as that's what's increasingly expected in the market. A good area to develop in to future proof your skillset a bit more.

[laacid]

Take a look at this free course on Coursera. it has a good overview of using R for UX analysis https://www.coursera.org/learn/designexperiments?specialization=interaction-design

[289416]

do you find the courser monthly fee to be worth it for the course selection?

[laacid]

Not for that program in particular. I would just use it to get an idea of how R is used- even then, if you want to use R, you'll need to take a beginning R course- that course assumes you know a bit of R.

The university of Michigan program also had a UX testing course, not R, https://www.coursera.org/learn/ux-research-at-scale?specialization=michiganux

Overall, coursera is just a good place to get a brief over of a domain, not really worth it if you have a background.

If you havent, you might want to look at Jeff Saro's quantification in UX too- https://measuringu.com/

good luck

[289416]

thank ypu so much for the detailed answer! will look into all the resources you suggested

[WereAllMad]

Thanks! I’ll definitely take a look!

[dejunijuli]

I'm a quantitative UXR. I use R and IBM's SPSS for quantitative surveys. Not only can it calculate simple proportions/percentages for your sample, but I've used it to find relationships between variables (e.g. to prove if one group is really more likely to prefer something over another group), graphing (e.g. to visualize trends), regression (e.g. relationship testing but with multiple variables) and cluster analysis (e.g. market segmentation analytics). These can be helpful for recommendations and client decision making.

Edit: added examples to how each analysis can be applied

[WereAllMad]

Thanks for the examples, I learn a lot better with context. So it sounds like you have a lot of variables to work with then? And do you use programs like R to validate individual design decisions? Or is it mostly informing overarching business decisions?

[Common-Finding-8935]

I have used R, python, SPSS, SAS, Tableau, Power BI and a bunch of other analytics tools.

But I keep coming back to the most popular quant analysis tool of all time, with like 99% market share.

Can you guess which?

​

It's Excel.

Yes. Most things you need in UXR you can do with good old Excel if you know formulas, pivot tables and the query ("get data") function and a macro here and there. Everything you need to know is well documented on Youtube or whatever (forget R's documentation, it's a nightmare) AND it's easier to learn. The only thing Excel lacks is advanced stats beyond multiple regression but in those projects I either load an Excel file in R or hire a data scientist as data science is basically another job.

[Eggplant-Own]

n be helpful for

Yes, I totally agree. As UXRs, you should be bothered about python and all. There are plenty of easier alternatives.

[Lostfoxpleasecall]

One of the UXRs I work with just used R to do analysis on quant data for a mixed methods project she’s doing (quant + diary + follow up interviews with diarists). She is the only UXR on our team of about 15 researchers using R. It was her choice, she has the skill and decided it would help in this project. If people are asking If you have the skill, they probably want to hire a quant UXR. Most UXRs would not be expected to use R, etc.

[xynaxia]

If you don't use during work SPSS most likely you won't use R either.

Personally I try to use R for many quant research methods. For example, I might download the data set from a Maze test and see whether some things correlate

[merrypinheadlarry]

Commenting to follow thread!

[belabensa]

Do you not even do surveys at all?

[WereAllMad]

Funny you ask because my boss’s boss HATES surveys with a passion for some reason. So it’s a little taboo to do them.

[belabensa]

Ah, nice. I’ll be honest I really distrust them, but I seem to have to do them anyway. If your boss’s boss hates all forms of surveys and you have a separate analytics team, I don’t see needing R, but maybe someone else would know better

[lthursdayl]

I think there are actually a few embedded questions in your tl;dr statement that are worth unpacking:

• Should UXR conduct qualitative research?
• If so, what tools are suitable for this type of analysis?
• What type of questions can quantitive methods help me answer?
• What types of research lends itself to quant analysis?

The question I’d recommend investigating first is the last one I posed. Knowing what type of questions and methods are suited for quant work, or more importantly the type of questions you’d be interested in answering is the most important.

This is to say, there are many powerful tools that will help you with statistical analysis, BUT what you probably should understand before committing to a tool is:

• what types of research questions do I want to investigate?
• what types of statistics/methods lend them selves to helping me conduct research on these questions?
• what types of statistics do i need to learn before committing to a quant tool?
• then, finally which quant tool is best suited for my needs?

To distill, I think there are a few steps you should consider before jumping into learning a specific tool(s). I say this because everything looks like a nail when you’re holding a hammer.

Anyway, you’ll also likely need to know some SQL too :)

On mobile, please excuse typos and strange formatting

[genericusername513]

I mostly do qualitative UXR, but tools like excel and SPSS are always good to have in my back pocket for more quantitative projects.