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The users flow report in Google Analytics is there to help cast light on how users are flowing through and exiting a website. However, the options to tweak the level of detail and site sections are limited, which can prevent an analyst from reaching their desired level of insight about user behaviour. Using the networkd3 package by Christopher Gandrud and the bigQueryR package by Mark Edmondson, we can create a fully customisable and interactive network diagram and sankey chart of visitor flows.
If there’s one thing guaranteed to drive an analyst to drink or violence, it’s a request to update a 500-slide Powerpoint deck with thousands of once-tidy datapoints into a wipe-right-on-click abomination. I suspect that marketers are doing everything in their power to drag us analysts into the mud, to suffer as they suffer. Luckily, with help from Google’s Apps Script and their APIs, analysts can output all their data into a nice, tidy Google Sheet and auto-populate it into a Google Slides document with a single button press.
Ever wished you could grab a guilt-free coffee whilst your humungous R script completes processing and be notified when it’s done? With the glorious pushoverr package by Brian D Connely, you can! Here’s the final effect we’re looking for: This post will look at a simple example of how to set up Pushover on an Android phone, install the pushoverr R package and send yourself a push notification after running a script.
Ever wished you could grab a guilt-free coffee whilst your humungous R script completes processing and be notified when it’s done? With the glorious pushoverr package by Brian D Connely, you can! Here’s the final effect we’re looking for: This post will look at a simple example of how to set up Pushover on an Android phone, install the pushoverr R package and send yourself a push notification after running a script.
I had the pleasure of attending Measurecamp London in early March, and had an absolute blast. My Measure Slack pal Pawel Kapuscinski pointed out that I should stop being a wuss and host a session, so I scrambled some slides together on the Friday night. Here’s a copy of the slides, which look at how to use the Google Pagespeed Insights API, coupled with a couple of functions I put together, to pull speed insights at scale using R.
Below is a copy of the post I wrote for the wonderful Dartistics website, which is maintained by Tim Wilson and Mark Edmondson. This example creates a Sankey chart to show how traffic flows from the homepage, split by device category. Steps to achieve this are: Call google_analytics_4 to get unique pageviews, split by the secondPagePath dimension. We apply a dimension filter to limit the results only to users landing on our website homepage.
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