Google Data Studio Data Blending lets you combine data sources in one visualization. Let’s take a look at the new Data Blender together and see how the new feature works.
Google Data Studio Tutorial https://www.youtube.com/playlist?list=PLgr_8Hk8l4ZGijmrFPjYSeKwLbnsqwq1e
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In this video, we’re going to take a first look on the new data blending feature in Google Data Studio. All and more coming up.
Hey there, welcome back to another video of measureschool.com teaching you the data driven way of marketing. My name is Julian, and we are live right now talking about the new Data Studio feature of data blending. Now, if you are aware of our other tutorials we did on data studio, you might know that we took the work around at that time, at least to pull in data to Google Sheets blend it together and then importing it into our Data Studio dashboard. This gave us a lot of flexibility. But at the same time was a little bit inconvenient. Now Google has done something about it, or at least the Google Data Studio Team, because they have announced the community connectors that actually let us pull in data from different data sources, then the Google products into Google Data Studio. So we can now pull data through third party connectors, like super metrics directly into Data Studio with these new functionalities of these data connectors. And that is important for Facebook ads. Now,what we are not what we were not able to do is actually take that data and then blend it together with other data sources. What do I mean by blending? Well, if you wanted to have data from Facebook ads, and Google Analytics in one table on one visualization, that was not possible to do within Google Data Studio, you would still need to go back, for example, to a third party system like Google Sheets, or a database blend the data there together and put it then into Google Data Studio. This has now been fixed with a new feature of data blending within Google Data Studio and we’re going to take a first look. So without further ado, let’s dive right into our little demo here.
So I’m here at Data Studio, let’s just come up with a completely new report. And at the beginning, we are asked to choose our data sources. Now, I’ve already connected my facebook account and my Google Analytics account, I actually want to just demo this. And let’s find out how many clicks we had on our Facebook ads campaign. So I’m adding this to my report. And we get our familiar Canvas em, now I will work with dates. So I’m going to just put this date picker right here and select the range,let’s go to some old data we have in the system from November,let’s go with the 15th year. Okay, so this is already pre put in here. Now, the next thing I want to do is actually make a table. And in this table, I want to show my Facebook ads not by campaign name, but actually by that date. So up here, we can choose our dimensions and our metrics, what I want to do is choose the data dimension, so we have appear time and this the super metrics connector to Google Data Studio, that you can then connect to your Facebook ads account, I have done this in this case, we are simply go with the date dimension. And as you might know, dates are in a in a spreadsheet, they are really the columns that you put in here. Now for the rows, I actually want to not have impressions here, I want to show the actual clicks that we had on our campaigns. So I’m going to go here to campaign and go with the link clicks.
And let’s get rid of, well, we can leave in the impressions doesn’t really matter. Now, what I want to do is actually know how many people converted. What I can do from my Google from my Facebook data is, obviously if I use the conversion tracking of Facebook, I can put that in as well. But Facebook will always give me different data, maybe that will be a great thing to actually compare if I can find the right metric here. Because as you might be aware, the website conversion value, Facebook API gives us a lot, a lot of data to look into. And I don’t, I’m not quite sure how I tag this, if this is just a custom conversion.
Let’s see if that does the trick. Yes, we have custom conversions here. So this is what Facebook actually records from the facebook pixel. Now, I want to compare this with Google Analytics data, right? Google Analytics has a different attribution modeling going on. Because you might know that Facebook is really looking just at how many people come to their website, click or come to the website, and then convert and they look back, if there was any contact point with Facebook, it will be attributed to Facebook. And Facebook will show that Google Analytics is different to that because its last click wins, or the last source that brought the traffic to your website, and then converted how many people that and how does that compare to Google Analytics. Now, I could do this in spreadsheets, obviously. But for demonstration here, we want to actually blend this data with our Facebook Ads data. And there is this new functionality here in the data sources where we see blend data. And I’m going to click this, this opens up this new menu down here, where we have our data sources. And we can blend multiple data sources to each other or into each other I guess. The data source that we are predominantly using right here is Facebook ads, this will be our primary data set, I’m going to add a data set to it. And available sources here, I’ve already connected this is my Google Analytics account. So I’m going to add this to the report.
Now, we have two reports in here. And we want to join this. Now, in order to join data with each other, you will need to have a Join key. Join key and databases, they’re also called primary keys are date metrics that you have in both data sources that are aligned to each other. So in our case, it would be the date obviously, the data is not is in Google Analytics and in Facebook ads, and it would atch that up correctly. What you could also do, if you have tagged your UTM parameters in your Facebook ads correctly so that through, for example, the source medium or the landing page so, you need to have a join key in order to align this to the data sources together. And we have date here so that is all fine. Now the last thing I want to do to make this a little bit bigger is to actually add a metric to this, now that that data is aligned, we can add the metric. And in our case, I want to just take a goal completion on my case, it would be the email sign up, find the right one here. That is the goal completion. Yes. And we’ll just drag that in. Let’s save this and see what it does for our table. Now we have our email signups in here. Now, you might notice that this is kind of screwed, because we have that many link clicks. And we have so many email signup. So it’s much higher than we would expect here. For the clicks that we are getting on this day. Maybe it’s much higher, it’s actually a little bit beneath it. But what you always need to keep in mind is that when you pull data from a second data source, that doesn’t mean that it’s automatically filtered based on the data source that it’s connected to. So in our case, we actually would need to say, or these email signups that we see right here are email signups that are originated from maybe different sources that came into our Google Analytics account. These are the totals of all goal completions on that day, just added to this, this table here. And therefore, we need to go in and actually implement a filter. So we can add a filter here. And we’ll just call this Facebook traffic. We want to the data sources master and only include we have here our dimensions, let’s go with the source medium and condition should contain Facebook.com. I think that’s what I entered as the as the UTM parameter so that should be correct. Let’s just save this, save this again. Now our data should be filtered down, or at least that column of email signups to only the Facebook data. So here we go, we see that it’s much lower, and the sources have been attributed differently. So we can look at what Facebook actually says it generated 71. What Google Analytics says it generated from our Facebook source quite interesting to see. Now if I would be honest, I would like to know the conversion rates, right. So I would like to put in a another column here saying what is the conversion rates between the link clicks and a website conversions. This is easily done for a native data source. So if we have Facebook ads, just as a data source or just Google Analytics, we could build a custom metric or a custom calculated metric from this. Unfortunately,this is not something you can easily do or not something I found in the interface at least to be something that you can do in the blender data form. So once you use blender data the custom metrics out of the play you can’t know the you can’t calculate the link clicks, conversion rate to the email signups of goal completion for. That said,probably something that they’re gonna fix at some point. For now, if you really need to do this, I guess you would need to go to something like Google Sheets Connector again, and do this first and Google Sheets and then import the data.
But overall, a pretty interesting feature that they have added and it was something that people needed. It also just simply breaks up the whole data silos, silos, right? You have data silos. Now you can import them into one dashboard. But they’re still silos in itself. But now you can blend them together and have much more interesting insights, I think in terms of comparing data, putting it together from different systems. That is really the power of building a custom dashboard. Then just looking at a dashboard and Google Analytics or on Facebook ads, this is something that we really needed and it’s now implemented into Google Data Studio.
Alright, that’s it for this little demo. If you have any more questions, then please leave them in the comments below. We also have new videos coming out all the time and live streams so be sure to subscribe to this channel and also check out this video.
My name is Julian. Till next time.