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Happy Holidays!

This is Outfox’s Christmas card in 2019. 🎄 May 2019 end in joy, and 2020 start with success, for you!

While we wish for a white Christmas, this year’s illustration is showing our office at Ă…sögatan (“Skrapan”) on Södermalm in Stockholm as if it was located in Miami in the 80’s. Thanks Cristobal Maldonado for your awesome work!

This season, the companies within Dentsu Aegis Network in Sweden is joining forces and giving a gift to Barncancerfonden. You can see all of our previous Christmas cards on Instagram.

Merry Christmas and a Happy New Year!

Outfox Christmas 2018

All of the Outfoxers would like to thank all of you clients and partners for a fantastic year! We’re looking forward to working with you to improve digital services even more next year. We’ll achieve that through digital analysis and conversion optimization, in close collaboration with you.

The very talented graphical artist who created this year’s illustration is Aleksey Rico. He has used smooth vector lines to create a futuristic version of our office in Stockholm, while also flirting with a retro feel.

Outfox has donated meals to Stockholms Stadsmission this season. We’re also proud of belonging to Dentsu Aegis Network which has an ambitious strategy for social impact. One of the initiatives is the Female Foundry, an accelerator program that aims to open a door for more female entrepreneurs in Southeast Asia to succeed with the startups they are building. Diversity and economic sustainability is at the core.

Read more about what Dentsu Aegis Network is doing to build a digital economy for all.

We hope you’ll get some well-deserved time off, a nice holiday, and many exciting experiences!

PS. Want to see previous illustrations made for us? Check Instagram!

The New Functions in Data Studio

Google Data Studio was released into public beta in June 2016, since the release the usage of Data Studio has exploded, and Google has not been late to respond to the demand. Each quarter more than 20 updates to Data Studio have been released, the latest was released during Google’s Partner Summit in San Francisco. We will walk you through these updates and also give you a demo dashboard you are free to copy and use in your own organisation.

Calculated fields in specific charts

Until now the only person able to create new fields in data sources has been the owner of the data source, with this release that limitation is gone. With the function for calculated fields in specific charts, anyone with edit rights to the report can create new fields, but with the limitation that the field is only available in that chart. So now you can create calculated metrics without asking the data source owner for help and you can also create calculations with blended data – something you still can’t do via the regular way of creating fields. The ability to create fields with blended data is hopefully coming to the old fashion way of creating fields, but that will most likely take some time until that feature is released.

You create a new field by clicking on the chart you want to add the metric to, click on “Add metric” and then “Create field”. In the popup box you can use the same functions and expressions you are used to in the regular create field interface. This is a much faster way of creating fields, but with the drawback that the field is only available in that chart. 

Interactive charts

Interactive Filters in Data Studio

When activating the function interactive charts on a chart this chart will become like a filter for other charts. So, for example, clicking on a specific country on a map will filter all the other charts on that page (that are linked to the same data source) to only show data from that country. This function can be used to really filtering down your results in an interactive way, for example, first click on a Sweden, then on the part of a pie chart representing desktop devices and finally clicking on a specific product in a table to only get the sales for that product, in Sweden on desktops in a time graph.

This function is activated on a per chart bases – with the chart activated, look at the last option in the right-hand side menu – “Apply filter” and choose “Interactions”. This will activate that chart to be clicked on and able to filter all other charts on that page. If you want to limit the charts it can control, you need to group those charts together by selecting all the charts, right click and finally select “Group”.

Filters with search function

Filters with Search function in Data StudioAnother new filter function is the ”Search All” style of filter. This filter is a free text search on the field you have selected with different operators available. The operators you can select is “equals”, “contains”, “starts with”, “in” and “regular expression”, which in principal means that you can write any filter you want and search for the data you want instead of selecting exact matches from a list. So far, this function is only a search on includes X but I imagine that Google is working on an exclude X search function as well, then you could really create any filter you want to.

Improvements in multi-select function

The last and least impressive function, which you have missed unless you ever had the need to make changes to the size of multiple objects, is the improvements Data Studio has released to multi-select resizing. Now you can select multiple objects on the page and change the position and size on all of the objects at the same time. At the same time, the Data Studio team released functions to improve the visualisation of movement and resizing of objects that is overlapping. A very simple function but so useful when you need it!


I have created a simple example dashboard with some of the functions that you are more than welcome to play around or use in your own team. You can use the visual filtering by clicking on different charts, filter by search in the right corner of the dashboard. Also, a new function of Data Studio I utilise here is the possibility to have the dashboard display data year/quarter/month to date and have it updated automatically.

All the data in this dashboard is from the Google Analytics Demo Account, that you can import into Google Analytics and start using to visualise data in Data Studio if you don’t have any Google Analytics account you can use.


For me it is clear that Google is focusing on Data Studio and that even more functions will be launched soon. So, take this time to get to know Data Studio and what you can do, and if you haven’t already, create a Data Studio report for you or your team. It is just your ideas that set the limit on what you can create. And if you want more ideas or bounce ideas off somebody – feel free to leave a comment or contact us!

Outfox Recognized as a Super Company

It is a great honour to have Outfox recognized as a super company (“Superföretag”) by Veckans Affärer & Bisnode. Less than 1 per mille (‰) of Swedish businesses qualify.

You have to be qualified in a number of areas to be named a super company. You need to show that you have long term, sustainable, growth, efficient use of resources, profitability, etc. The list accounts for the environment you’re working in. It is, in other words, a more tough award to get compared to the Di Gasell.

Advanced Analysis in Google Analytics

Advanced Analysis – Powerful Reports

One of the benefits of using Google Analytics 360 is to access a new set of reports; “Advanced Analysis”. The reports allow you to explore, visualize and act on data from Google Analytics 360 in new ways. The reports are based on three different visualizations:

The reports in Advanced Analysis, unlike Data Studio, show only data from Google Analytics. In return, the reports are highly interactive. In this blog post we look at the “Segment Overlap” visualization, which is a Venn diagram that shows the overlap between different segments of users.

In the example, we have used data from the Google Merchandise Store and chosen to identify the extent to which visitors interact with different groups of products on the site. The product groups are Apparel, Bags and Drinkware.

The reports are  built by the toolbox on the left side of the page, where Segments, Dimensions and Metrics are selected (imported) from Google Analytics. Keep in mind that segments imported from Google Analytics must be created as “User scope” (ie a selection of users – not sessions) to allow the chart to show overlap.

The image above shows how three segments have been selected. The table below the Venn diagram shows the number of users in each segment. By adding the Revenue metric, we can see which revenue that is created by different user overlaps:

By adding one or more dimensions such as “Breakdown”, you can segment users even further. In this case we segment on the “Device Category” dimension shown on the Y axis and the combination / overlap of the segments on the X axis:


Use the data to improve customer experience

Now to the best part; For each segment, you can right-click and start interacting on that particular group of users. In the picture below, there are users who have seen both Apparel and Drinkware products on their phone. You can now choose to create a new segment of this particular user segment, build a target audience, or review the behaviour of these users in detail through User Explorer. This allows you to control keyword ads in Google Ads, programmatic media through Display & Video 360, and control A / B tests and content through Optimize 360 based on the discoveries you make in your data!

Google Cloud Next London 2018

I, Johan, went to Google Cloud Next in London to represent Outfox, and I made this interview with myself! 

O: Why did you go to Google Next in London, Johan?

J: Because you can’t sleep when Google is up to things in the cloud. Me being an analyst, I was extra interested in the products that relate to me and my job. Topics like BigQuery, BigQuery Machine Learning, TensorFlow (an open-source software library that can be used for building your own machine learning applications such as neural networks), and how you can use Google’s cloud products to deploy machine learning.

Johan, this sounds soooo nerdy, can you break it down?

J: I can try! For me, in the last couple of years, machine learning has improved what I do in ways that were hard to imagine before. It makes things that were impossible possible. Look at the Vision API for example. No more manual tagging of images. Just let the API do the job for you! This can save crazy amounts of time if you are working with tagging images. Read more: 

: Cool, but what about marketing?!

Aha, then the new possibility to use machine learning in BigQuery is just awesome. You can use it to find the users who are most likely to convert based on what they have done on the website. Sounds great, but the cool thing is that you don’t need to be a data scientist to make this happen. You just need some SQL skills, or a friend with some SQL skills. Say you are a B2B company and you want to target only the users who have a higher probability to convert. Then you ca, based on what they did on your site, use BigQuery and the machine learning capabilities to find them.

Any other cool things?

Yes, two more things that will stick with me going back home are: 1.) How King uses Google Cloud to create artificial intelligence for game testing. This means that King has improved the workflow for designing and testing levels. Instead of having people testing the levels and having them write a report and send it back, the AI will test the levels and give the feedback to you in minutes or hours instead of weeks.

2.) How universities use computing power from the Google Cloud Platform to solve the most amazing research problems.

Things like building models to understand and predict the spread of the zika virus. The zika virus is apparently very hard to predict, but it also requires a ridiculous amount of data to build meaningful models. Thanks to moving the workload to the cloud they are now able to perform these calculations in hours instead of weeks! 

Or how Researchers at the Neurosim lab use the cloud to understand the human brain! The amount of data that they have to processes is just amazing, and makes every marketing DMP look like a floppy disk. They were able to cut the compute time from five days to one hour! This means that the work they are doing can move much faster and help us understand the way our brains work much faster.

O: OMG Johan! Got more high-level stuff?!

Maybe just that the ones who have an infrastructure that makes the impossible possible, are the ones how will move faster than the others. 

O: Sorry, I do not understand. What you mean?

I think that Spotify is a great example of this. They have, with the help of Google Cloud Platform, made it a lot easier for their entire organization to understand their users, and to make smarter decisions based on their data. This would not be possible if they did not have a great digital infrastructure. It looks like leaders in this field have sat down and thought long and hard about how to make it easy to use the data we have about our users.

Any last things takeaways?

Google Sheets rules. Just check the 30 tips in the video. One of my favourites is to connect to Google Sheets to automate reporting. That function just saves a crazy amount of time, especially if you also consider that you can get data straight into Google Sheets from, for example, Google Analytics.

How does it work with Campaign Timeout in Google Analytics nowadays?

The other day we discussed Campaign Timeout in Google Analytics. In order to find out the correct answer we turned to Google and the first result led to a site where they stated that the campaign is prolonged each time a user comes to your site (if the traffic source is not changed. If you want to refresh your memory regarding traffic sources or attribution modelling in Google Analytics). Hmmm, that was not what I expected and remembered. I had to check it out by doing a test. Oh, the joy when I realized my memory did not fool me.

The short version:

If a user returns to your site by typing in the URL (hence direct traffic), the campaign is not prolonged (in the way that it did with ga.js).

The slightly longer version:

When Universal Analytics was rolled out in 2014, there was a change in how campaign timeout worked. This deals with for how long a traffic source is attributed even if the visitor comes as direct traffic. In the former, Classic Analytics (ga.js), the timeout was extended each time a visitor came to the site. This meant that a campaign or source of traffic could theoretically live forever.

Universal Analytics, hence now

Session timeout: 30 min

Campaign timeout: 6 months (default setting in Google Analytics)

1 sep 2018: Visit through campaign-tagged traffic source. Campaign timeout should now be 6 months ahead, March 1, 2019. Reported in Google Analytics as campaign traffic.

1 Nov 2018: Direct visit to Reported in Google Analytics as campaign traffic.

April 1, 2019: Direct visit to Reported in Google Analytics as direct traffic.


Classic Analytics, before 2014

Example from how it used to be, in the not to smart way:

Session timeout: 30 min

Campaign timeout: 6 months (default setting in Google Analytics)

1 Sep 2018: Visit to through a campaign-tagged traffic source. Reported in Google Analytics as campaign traffic. Campaign timeout should now be 6 months ahead, March 1, 2019.

1 Nov 2018: Direct visit to Reported in Google Analytics as campaign traffic. Campaign timeout moves forward 6 months ahead, May 1, 2019.

April 1, 2019: Direct visit to Reported in Google Analytics as campaign traffic. Campaign timeout moves forward 6 months ahead, Oct. 1, 2019.

And so, this could go on forever and ever (or as long as the visitor does not change traffic source, but continues to enter the site directly.)

This was a bit of a mess. So since 2014, it is more as you would expect.

So, if you read a blog post saying that the traffic source extends all the time (if the traffic source is not changed), you can dismiss it. So, that was Classic Analytics. Not now.

Then you can always discuss if six months is the ultimate length for how long you should give cred to a campaign, but we’ll take that in another blog post! If you want help with your campaign tagging you can use the GA Campaign URL addon. You can always contact Outfox if you would need assistance in your campaign management/analysis!

Add quantitative data to quantitative and get sort of qualitative data

It is not difficult to see which pages that are the most visited on a website. Just go to Google Analytics and click on the navigation to the left and click Content and then All Pages.

But. Often there are certain target groups for certain pages or categories of pages. How do we know if we reach that specific target group? In Google Analytics we can see what users have done, but we know little of what their intention was with the visit, and specifically, we do not know whether they have succeeded or not.

Happy days are here. There is the Outfox Survey, a web survey where the answers can be matched to the behaviour on site. We only ask three questions: In which role do you visit the website, what is your intention with the visit and did you succeed in solving your query.

Prioritized targets groups to study up close

By looking at a segment of your website’s prioritized users and see what their intentions are, and I like in particular to know more about those who have not found what they were looking for, I try to understand why they have not succeeded. Google Analytics is good at what, but not why.

When I have created a segment of those users I can look at the different reports in Google Analytics.

  • Which pages do they visit? Is there information missing on those pages or just not the information the user would expect?
  • What are they searching for in the internal site search? Are there queries that do not give the results that you would expect?
  • Which traffic sources do they come from? Which landing pages are common? Is there anything in the link between advertising and landing page that could be better?
  • Is there any device or browser that is more represented? This could help us in prioritizing when adapting pages and/or functions to mobile.
  • Which are the common exit pages? Are they pages that you would expect your visitors to leave your site from, or could they be pages where the visitor just gives up? What can we do to improve?

Well, the list could be even longer. So, if you have not yet made a survey (and yes, many people actually answer pop up surveys. We have about 25% answering rate on our surveys), contact us and we’ll make it happen.

Merry Christmas & Happy New Year

Here’s the Christmas card of the year from Outfox. It was illustrated by Joel Edlund. Outfox will be moving to this address during the first quarter of 2018. So what would be more appropriate than a King Kong style take over of the block?

The Dentsu Aegis Network Sweden family is making a donation to Unicef this Christmas.

We hope you’ll have a great and relaxing time with your loved ones this holiday!

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