Sometimes all we need is just a little bit of fresh paint. And when it comes to websites and apps this is equally true. Sometimes a small dash of fresh "paint" can make an old and never-changing UI feel fresh and modern.

The kyco website itself has undergone several iterations, however, the most recent one must have been the easiest to implement with the most drastic impact. The change already took place last year May (2023) and I feel it still looks fresh and modern, especially when compared against the old design.

Can you notice a difference? Which one do you prefer?

All it took was adding two new fonts, adding more whitespace here and there and slightly adjusting the font sizes.

When giants like WhatsApp or Google change their UI the whole world gets to see it and it is very apparent that - even when nothing functionality-wise changes - a small splash of fresh paint can make a big difference!

The difference a small splash of fresh paint can make

Google Analytics allows you to export your data in several formats including PDF, Google Sheets, Excel and CSV through its user interface. While there are plenty of guides out there that cover these methods, they all seem to assume that you love spending hours on end laboriously exporting your data manually. We can skip these time-consuming approaches and use a smarter, more streamlined, automated approach.

Instead of relying on the manual process in Google's user interface, we will use code to directly access and format the data we need. Our goal is to create a tool which will end up looking something like the below.

The tool provides a basic "pagepath" / "pageviews" chart and table, which can be effortlessly exported to both CSV and JSON.

 you need to setup a "report request". For this you will require a 

 linked to your Google Analytics account and a 

, which are essential for authentication with the Universal Analytics API. Below is the foundation of our automated approach:

You can also enhance your report by adding more metrics and dimensions. For instance:

. If you have specific questions about the report request then the 

Google Analytics Viewer simplifies the process of retrieving and displaying data and gives you a good basis to start your own "code to data export" mission. For a detailed walkthrough on setting it up locally refer to the 

Configure the metrics and dimensions which are relevant to you.

Manage initial data transformations and adjust the frequency of API calls. The code already accounts for API request limits and uses the library 

 to ensure all data can be fetched without hitting thresholds.

Adjust how the data is finally transformed and exported. The main methods you'll want to adjust are:

used to manipulate data for display in the chart and table

used to define the structure of the CSV file export

And that's already it! I hope this tool helps you get your data exported.

How to backup Universal Analytics data?