πŸ”΄ First Look: Data Blending in Google Data Studio

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.

#DataVisualization
#GoogleDataStudio
#Dashboard

πŸ”— Links:

Google Data Studio Tutorial https://www.youtube.com/playlist?list=PLgr_8Hk8l4ZGijmrFPjYSeKwLbnsqwq1e

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
Facebook: http://www.facebook.com/measureschool
Twitter: http://www.twitter.com/measureschool
LinkedIn: https://www.linkedin.com/company/measureschool

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,Β  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.

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πŸ”΄ First Look: Pivot Tables in Google Data Studio

Pivot Tabes in Google Data Studio give you the ability to display your data in a table with multiple dimension at the same time. This gives you the ability to use Data Studio for Data Exploration but also it gives you a new ability to display your data in this Dashboarding Tools.

#PivotTables
#GoogleDataStudio
#DataVizualisation

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πŸ”΄ Google Data Studio Connectors (for Facebook Ads and more…)

Let’s chat live about the new Community Connectors announced for Google Data Studio. We now have the ability to Facebook Ads and more directly to Data Studio, which opens up a lot more capabilities.

#GoogleDataStudio
#Measure
#DataVizualisation

πŸ”— Links mentioned in the video:

Suerpmetrics: https://supermetrics.com/blog/data-studio-connectors/?aff=1014
Offical Announcement: https://analytics.googleblog.com/2017/09/google-data-studio-quicker-and-broader.html
Ben Collins: https://www.benlcollins.com/data-studio/community-connector/

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
Facebook: http://www.facebook.com/measureschool
Twitter: http://www.twitter.com/measureschool

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πŸ”΄ Data Studio Course: Summary und Live Q&A | Lesson 4

We have build a Dashboard. Let’s summaries our approach, see some more resources about data visualization and answer your questions Live.

Watch the full Course: https://www.youtube.com/watch?v=wVsSXFhjyUc&list=PLgr_8Hk8l4ZHchZpGaCBD6EA8kWrBEhYf&index=1

Q&A Section:
19:32 How to change the default Week day start?
21:40 Alternative to Supermetrics?
27: 40 One Report different sources?
28:57 Report Drop Down menu for sources?
30:29 Best way to compare 2 date ranges?
31:49 Best report for overall performance?
34:34 Connect DataStudio and Google Optimize?
37:35 Supermetrics is it an Agency license?
39:49 What data is available in Supermetrics?

πŸ”— Links mentioned in the video:
Supermetrics: http://supermetrics.com/?aff=1014
Data Vizualisation Books: https://kit.com/Measureschool/data-visualization-books
Ben Collin’s Course: https://benlcollins-data-school.teachable.com/?affcode=69396_b3spab2w
David’s course: https://learn.codingisforlosers.com/data-studio-the-lazy-way?coupon=MEASURE
Data Studio Gallery: https://datastudiogallery.appspot.com/
Tableau Gallery: https://public.tableau.com/en-us/s/gallery
YouTube Channel: DataSaurus Rex https://www.youtube.com/user/datasaurusrex
Stay up to date with Data Studio Changes: https://support.google.com/datastudio/answer/6311467
Lea Picas Present Beyond Measure Podcast: http://www.leapica.com/podcast/
Facebook Ads Manager for Excel: https://www.facebook.com/business/m/facebook-ads-manager-for-excel

#LiveQandA
#GoogleDataStudio
#DataVizualisation

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
Facebook: http://www.facebook.com/measureschool
Twitter: http://www.twitter.com/measureschool

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Facebook Ads Dashboard with Google Data Studio | Lesson 3

Facebook Ads Dashboard with Google Data Studio | Lesson 3

Facebook Dashboards can be easily built with Google Data Studio if you have prepared the data correctly. In this lesson we are going to visualize our data set and build our Dashboard complete with date control, filters and calculated fields.

You are going to learn how to calculate custom metrics, change their metrics name, layout your dashboard, build the visualizations required, build filter and date controls and make it all look pretty.

The template can be found at http://measureschool.com/facebookdashboard

Previous video: http://bit.ly/2uoa4qA

#GoogleDataStudio
#FacebookAdsDashboard
#FacebookPixel

πŸ”— Links mentioned in the video:

Full Playlist: http://bit.ly/2hkwUx4
Google Data Studio: https://www.google.com/analytics/data-studio/
Google Sheets: https://www.google.com/sheets/about/
Supermetrics: http://bit.ly/2hmxvOR

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
FACEBOOK: http://www.facebook.com/measureschool
TWITTER: http://www.twitter.com/measureschool

– Alright, so now that we have prepared our data in Google Sheets, we are ready to visualize it. We’ll first calculate our metrics, then lay out our dashboard, and then, finally, implement our data in Google Data Studio. All and more coming up right after this. Today our journey starts in Google Data Studio where we’re finally gonna visualize our data in our dashboard. Let’s start out by clicking on a blank sheet here, blank new sheet, and then choosing our data sources. So we can create a new data source and we’ll choose our Google Sheet. Now, from our Google Drive account, we’ll pick the sheet that we had prepared in our last lesson. Let’s do that. Now we can see that we can actually choose the different worksheets as a source. This is actually something that is unfortunate because you can only choose one worksheet as one data source. So you couldn’t say okay, I wanna choose the GA data from here and the Facebook data from here, and combine it all into one data source. No, you need to have them on one sheet in order to make this work. That’s why we prepared the data this way. Okay, let’s go over to Google Sheets and choose our combined datasheet, and then we can choose under the options to use the first row as headers. That is fine with me. If you look at the datasheet, this would describe our data, so we can pull that in. And we can include any kind of or filtered cells, which is not the case in our sheet, so I can untick this. You can also choose an optional range if you have data on that sheet in a special range. This will be all for us under the configuration. Let’s connect this all. And we will pull in our different dimensions and the different metrics. Now, as you might remember, in our last lesson we actually prepared that and looked into the metrics and dimensions that we want to pull. Unfortunately, first of all, these are not exactly the same name that we want to display them on the actual dashboard, and therefore I would recommend to actually rename them right here. It’s pretty easily done. For example, link clicks should just be clicks. You can just click on that and change the name around here. The amount spent will just be our ad spent. Our transactions are just our conversions, and our transaction revenue is actually the revenue. The campaign name, let’s rename that in just campaign, and the ad set, and the ad name can stay the same. All right. So now we have renamed our dimensions and metrics, but we also wanted to calculate some metrics. So for example, here’s the CTR which is impressions divided by our clicks, and we can easily input that by going into Google Data. So we’re clicking on this Plus button, and it will let us input a name, which in our case was the CTR, the click-through rate, and then the formula would be impressions, and it already pops up, our impressions from down here, divided by our clicks. Alright, let’s create this field, and it’s now part of our dataset. With calculating metrics, these are custom, so Google Data Studio doesn’t always know what kind of type it is, and this is actually a number but it’s actually a percentage. So you need to make sure that you choose that correctly. We’ll auto-aggregate that, that’s actually something we can’t really change. So let’s go ahead and do our other calculated metric, CPC. CPC is the cost per click. So let’s click on the Plus button here, CPC, and this would be the ad spent divided by the clicks. Alright, create this field. This is a number, that’s correct, but it’s also a currency, so we can choose that as well. Let’s pick US dollar here. And we have all CPC metric. Let’s go ahead and calculate the CPO, the cost per order. So let’s click on the Plus button, cost per order, that would be the ad spent divided by the order transactions. We called it conversions. All right. Create this field. And we have one more left, return on ad spent. Return on ad spent. This would be our ad spent divided by the revenue. Alright, that should do it. Now, we have a few more left that are actually manually inputted. This is something we could put into our sheet but it’s actually easier to update it manually in our sheet. Because sometimes Google Data Studio can actually pull the data from a sheet for certain cells. Okay, we have our data sources ready, let’s add this to our report. And here we go, now we have that available in our data sources if we choose to visualize anything. Right we you see our data range and our metrics, these are now available here. Okay, before we start out visualizing anything, let’s get clear on what we are trying to do. Fortunately, we have prepared a wireframe in our first lesson, so we know what we want to build and have an idea of what elements should be on our dashboard. So on this dashboard we have kind of like a three column layout here, and three columns here. Let’s mock that up really quickly in Data Studio, and we can choose the rectangle tool to do all this, just so we can get the proportions right. Because we don’t wanna mess with all the layout later on once we have our data together. This will make this whole process a whole lot easier. So let’s just mock this up. So now we have laid out our information, what goes where, and this is actually also a great template that we could use later on if you would like to build a new dashboard. So you can go ahead and actually make a copy of this and rename this in some kind of fashion to template so you have that available later on as well. Okay, let’s continue here with our report. Let’s fill this all with data now. So we’ll go ahead and fill out these panels. Up here we would have our controls, so that would be our campaign but also our date picker. So let’s put that in place. Date picker and filter control. Right here there’s actually a new filter control. This is for the different views of Google Analytics. That’s not something that we would use here. Okay, so we can get rid of the panels in the background, and this should give us capabilities of showing us the right campaign and the right date. Let’s view this and here we can see our different campaigns. There’s null. That is something we would investigate with our raw data again. And then we have our date picker, so that is all working as expected. Alright, let’s continue with these metrics groups here. Before we start out, I want to actually select the date range so we are working with dates that actually make sense for us, and in our case it would be the July date range. So I’m just gonna change this to this week here, and that will make all our data appear in that realm, and if anything goes wrong here, we can also adjust it later on. So let’s go ahead and build these metric groups. Now in our wireframe we see that we have these groups of acquisition, cost and conversion, and inside of them we have these different metrics that are represented by the actual impressions, the CTR and the clicks, and then also the comparison if it went up or down over the last period. So how do you implement this? You can do this with the scorecard elements. So we’ll just draw on the canvas here our scorecard element and choose the right metric, so in our case it would be impressions. And we can actually, this is a pretty big number, go into Style here and press on Compact Numbers, and this will make this a bit more compact so we can actually read it. We want to have our comparison metric, and for that to actually appear we need to implement this second date range so to compare date range, and this should compare to the previous period. This will give us this little number. Now you don’t see this actually, so I’m just gonna change this around and make the inside transparent. Okay. And before we move on and copy this over, let’s style this a bit so we don’t have to do this later on. We can easily copy it over and change the data around. So we want to have our CTR. That doesn’t make any sense so maybe there’s something wrong in our metrics. Let’s create a new metric or go to this menu and we have here our CTR. This should be not clicks, impressions, but clicks divided by impressions. Okay. Let’s update this field. And we see our data also changes. Now we als

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Combine Data Sources in Google Data Studio | Lesson 2

Combine Data Sources in Google Data Studio | Lesson 2

In this lesson we’re going to setup our data sources in Google Sheets with the help of Supermetrics. We’re going to pull data from Facebook Ads and Google Analytics and prepare it to later be used in Google Data Studio.

Google Sheets combined with Supermetrics is a great way to control data that later goes into our data dashboards – it gives you the possibility to change data around, clean it up and even combine data sources (which is not possible in Google Data Studio itself).

Previous video: http://bit.ly/2f4FgZl

#GoogleDataStudio
#DataSources
#DataVizualisation

πŸ”— Links mentioned in the video:
Google Data Sheet: http://bit.ly/2tUX3EF
Full Playlist: http://bit.ly/2hkwUx4
Coding is for Losers: http://codingisforlosers.com/
Ben Collins: http://benlcollins.com/
The Dashboard Plan: https://measureschool.com/dashboardplan
Google Data Studio: http://bit.ly/2bcb7zt
Google Sheets: http://bit.ly/1GAUvK5
Supermetrics: http://bit.ly/2hmxvOR

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
FACEBOOK: http://www.facebook.com/measureschool
TWITTER: http://www.twitter.com/measureschool

– In this lesson, we’re gonna set up our data sources in Google sheets with the help of Supermetrics. So we’re gonna pull the data from Facebook ads and Google Analytics. And then prepare it so it’s ready to be used as a source within Google Data Studio. All and more coming up right after this. Welcome back to this course. So in this lesson we’re gonna prepare our data sources in Google sheets. Now why do we go the route of Google Sheets as a source rather than all the other data connectors that are available within Data Studio. Well there are multiple advantages, but the first reason being that Google Data Studio doesn’t have a connector for Facebook ads yet. I don’t know if they’re gonna implement it at some point. I hope so, but it’s a Google product. So maybe they’re gonna leave themselves some time with the Facebook ads. But there is actually a tool that we can use in order to pull the data in and that is Google Sheets and the combination with Supermetrics. Now Supermetrics is a third party tool, an add on that you can install to your Google sheets account and then you can pull data in from various sources. They have many more data connectors than even Google Data Studio has and it’s a very versatile tool, and we’ll get into that in this lesson. But that’s not the only reason. Google Sheets gives us the opportunity to work with our raw data that we get from the tool like Facebook ads or Google Analytics before we then import it. We can actually change the data around, we can clean it up and most importantly, we can combine data sources. So that’s not possible within Google Data Studio itself to combine different data sources and then calculate metrics from that. So really, with the sheet, we have much greater control about the data that actually goes into our dashboard and if you run into any issues, we can investigate our data sources first and find out the error there. And that’s really why I love using Google sheets as this bridge between our raw data that comes from the tool and Google Data Studio that we will use for our visualization. Alright, enough said. We got still lots to cover in order to make this work. So let’s dive into today’s lesson. Alright, we will start out with a new Google sheet. And let’s think about what we actually need to make this dashboard work. We need our metrics and dimensions. Now just a recap, metrics are basically the numbers that you will have in your table later on, and the dimensions are the different properties that you want to divide your data by. And the table metrics will be represented by the different rows here and the metrics that would be in those rows. And the dimensions would be on top and represent the different columns. That’s important to think about, so we pull the data correctly. Next up, where do we pull the data from? Let’s go through a little bit of an exercise here. Let’s look at these metrics and decide where we would get them from and the impressions would come from Facebook. The clicks, as well from Facebook, then the CTR would actually be calculated. So this will be a calculated metric. The ad spent, as well from Facebook. The CPC, as well calculated, as well as the CPO. Then we have the revenue, which would actually come from Google Analytics and the conversions, also from Google Analytics. Now this is actually an attribution topic here. If you trust more the attribution of Google Analytics, then you want to pull that into your dashboard and we will do this in our example. Next up the return on ad spend, which is also calculated at the end. The ad budget, which will be put in manually. As well as the target CPO and the target CPC. So now have a good overview of what metric comes from where and what data we have to pull. Let’s talk about briefly about the dimensions because dimensions are the different columns that we want to pull. Now, these are obviously heavily based on our Facebook campaign. We have our date, campaign name, ad set, and ad name. But as we have seen, we want to also pull data from our Google analytics account. Now how would that be represented in Google Analytics? We may have the date available but not the campaign name, ad set and ad name at least by default in Google Analytics. And that’s what we need to actually connect both tools together in order to have all these dimensions in both tools. And that is done through UTM parameters. Now if you’re not familiar with UTM parameters, we have another video on that. But basically you need to make sure that when you input your campaigns into Facebook, you need to be clear on the campaign name, campaign content and campaign term that you would choose beforehand. Then you can go ahead and tag your link. So in this sheet, we have a link that we prepared in order for our campaigns to be tagged correctly and then when the user clicks on that link or goes to that URL, he will be automatically registered in Google Analytics with these campaign parameters. So make sure in Facebook, in your ads campaign, that your campaign name, your ad set name and your ad name actually, is tagged up correctly. So there’s an option for that which is called UTM parameters. You need to have these UTM parameters attached to your link in order for Google Analytics to register this correctly. So once the user clicks on the link, it will be registered in Google Analytics itself. So once you go to your source medium reports, you have here Facebook CPC. And then we would have our campaign name. So let’s put that in as a secondary dimension. This is called campaign in Google Analytics. Then we would have our ad content, which is the UTM content parameter. So here we have interest brands. And we would need to have our keyword, which is our UTM term, that we also fill with these parameters. So again, you need to make sure you tag them up correctly and send the user to the right link in order for this data that we want to break our metrics down by is available also in Google Analytics. So this actually only works if we have these dimensions in both Google Analytics and Facebook. Now in Facebook, these might be called date campaign name, ad set and add name. In Google Analytics itself, these would be called date campaign, ad content and keyword. Different naming convention, but essentially we should get the same data in Facebook when we query for this then in Google Analytics for these different parameters. So be sure you have the same data so you can connect it in your Google sheets later on. Alright, now that we are clear on what we need to pull from where with what dimensions, let’s go ahead and prepare our data sources. I’ll open up a new sheet here and call this Facebook data. And the second sheet called Google Analytics data. Now we can go ahead and pull our data with the help of Supermetrics. Now if you’re not familiar with Supermetrics, you can actually install it by going under the add-ons and go to get add-ons, and simply enter Supermetrics, and you can install it to your account. Now the capabilities that were used within Supermetrics are a paid feature, so you would need to upgrade your account. But for anybody who’s trying this out, you can use the Pro features for 30 days. So once you have it installed, you can go to add-ons and then on the Supermetrics, launch the side bar. And now you will be able to configure your query. Alright, first up, we will choose our data source. Now, Supermetrics has many data sources available and therefore it is more powerful than what the building capabilities of Google Data Studio actually provide. So you can pull in a host of other data into your dashboard if you choose so. And we will go obviously with our Facebook ads account. Now we need to enter our Facebook details. So you need to go through the process of registering this with Supermetrics, so it can pull the data into your account once you have that you can choose your account and then select the account, if you have multiple accounts, under you log in, then you can choose your different data sources and different accounts that you want to select. And we go on to actual date selection. Now how much data should be pulled here? There are differ

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Google Data Studio Dashboard Preparations | Lesson 1

Google Data Studio Dashboard Preparations | Lesson 1

Don’t start implementing your Dashboard without having gone through some preparations. In this video we’re going to go through the essentials steps to prepare your implementation of an effective Dashboard.

1. Exploration
2. Definition
3. Sketching / Wireframing

Previous video: http://bit.ly/2uwbUIh

#GoogleDataStudio
#DataVizualisation
#Dashboard

πŸ”— Links mentioned in the video:
Worksheet: https://measureschool.com/dashboardplan
Google Data Studio: https://www.google.com/analytics/data-studio/
Google Sheets: https://www.google.com/sheets/about/
Supermetrics: https://supermetrics.com

πŸŽ“ Learn more from Measureschool: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

πŸ“š Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books

πŸ“· Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear

πŸ‘ FOLLOW US
FACEBOOK: http://www.facebook.com/measureschool
TWITTER: http://www.twitter.com/measureschool

– Welcome back. In this lesson we are gonna talk about the preparational steps that you need to undertake in order to build an effective dashboard. We’ll go through some questions you need to ask your audience, assemble all the different metrics and dimensions you want to pull from your tool and sketch out your different visualizations that you later want to implement in Google Data Studio. All and more coming up right after this. Alright. In this course we’re gonna go through a three-step process in order to build our effective dashboard. First of all, we go through the preparation steps which we’ll do in a second here in this lesson. In the next lesson we’re gonna talk about the data setup and get our data sources ready so we can then in the last lesson visualize our data in Google Data Studio. But for now we are just gonna go through the preparational steps and these are very important. What does this actually entail? Well, before you begin implementing anything into different tools, you might want to ask yourself a few questions and this really goes into the exploration phase, what kind of dashboard are you trying to build, talk to your target audience, look into how they are analyzing their data maybe nowadays and what your dashboard will bring to the table. Then we’ll go into the definition phase where we’ll actually look at all the different metrics, dimension data and the sources that we need to have ready in order to build our dashboard and once we know what data we want to visualize we can actually start sketching out our wireframing, our dashboard on paper or in a wireframing software. So, let’s go a little bit more in depth into these steps. So, first of all, in the exploration phase you would ask questions. Now, who’s this data dashboard actually for? Be very clear about your target audience and then actually talk to your target audience, what they see the dashboard actually doing for them, what’s the goal of the dashboard, why do they want this dashboard to be built? How should this dashboard make their lives easier? Now if it’s for example about data analysis, then you might want to dig deeper and find out how they are doing data analysis without the dashboard at the moment. How can it actually save time? What data points are they looking at? What analysis are they going through? What are the different steps that they’re going through in order to get to insights. Now, all of that feedback should be taken into account once you conceptualize your dashboard so your dashboard actually fulfills its purpose for the target audience. Now, this might look like, in our case, take the Facebook optimizer that actually you would ask for questions asking what are your most important KPIs? What do you want to have on this dashboard. When you log into Facebook in the morning what steps are you going through? Why is that frustrating? How can that be solved through a dashboard? And you might get answers just like these that actually tell you a lot about what this dashboard should accomplish for the client, for the audience, for the user and that’s also how the dashboard can be really meaningful to the user because it actually saves some time and you’re actually using it in order to make decisions or get a quick overview in order to know where to dig deeper. So, this Facebook optimizer would maybe say I need an overview over my KPIs, I’m really going through these steps in order to optimize my campaigns, I’m looking at that data, I’m doing this analysis, and if the dashboard would help me to do this all faster, then it would be something that I would use. Now, there’s nothing worse than putting time into building an awesome dashboard that nobody uses. So, talk to your target audience and find out what they want on this dashboard before you start implementing anything. Now, once you’ve gone through that phase, you need to actually get some definitions straight. From the interview you probably elicited different metrics, different dimensions, and different sources where this data comes from and this is something that you need to write down in order to be ready for the next part when we pull the data actually from the system and prepare it in Google Sheets. If you don’t prepare that beforehand, first of all, won’t get clear on your visualization but may also find yourself going back and forth between your data extracts, the data that you want to display and the actual visualization which can be very distracting and not very efficient. So, get clear about the metrics, so for Facebook ads dashboard you might want to know how many clicks, how many impressions, what was the click through rate, what was the ad spend and so on. Put that all down onto a sheet of paper or into a document, so you’ll know what to look out for once you prepare your data in the next step. Now, once you have all the different data points that you want to visualize, it actually comes down to thinking about the visualization. How can I tell a story with my dashboard? And I’d recommend that you actually take time to look through other dashboards, look through other implementations of Google Data Studio dashboards, as for example the Google Data Studio gallery that you can see different visualizations from but also ask yourself how useful is this for my dashboard? Does it actually make sense to display the data in that way? Will it help my target audience to do what they want to do with the dashboard, for example, get you insights or keep a clear overview? Don’t overcrowd your dashboard and actually you can also look through other dashboards of other companies, of other tool vendors. There are also great examples that we will link up in the description below that you can check out and get inspired before you start actually sketching and wireframing. Now, for our example in this course I went ahead and built a little sketch in a tool called Balsamic. You can check that out in the description below as well, where I thought about okay, what story do I want to take my user through? What would be the visual layout? How would we segment the data later on? What is important to my target audience? And this is where I came up with this little sketch here where I said I want to have on the top my control panels where I can choose the date but also dig deeper into a campaign, then we would have our most important metrics in the first row and in these columns we would have the acquisition, the actual costs and the conversations, so we get a quick overview on how that is doing. Then we’ll go through and answer the most important questions such as how is this stacking up to my ad budget, my targets that I have in place already? Give some more context on the click versus cost per click price, the spend versus the revenue, we also probably also put in the whole return on investment metric and then down below we would have some more analysis in form of a table where the user can really dig into what campaign didn’t do so well, what was the driver of the growth of my campaign, or to the client and which ad sets should I be looking into further? Remember, the real goal here was to give a quick overview for a Facebook ads manager on how the performance of the campaign is doing and maybe also giving some points in order to ask more questions, dig deeper into the data, go into the Facebook ads interface and optimize his campaigns. So, I’d recommend for anybody to sketch out or wireframe your dashboard beforehand and get very clear about the visualizations that might make sense for your target audience to reach their goal. Alright, so there you have it. These are really the essential preparational steps that you should go through to build an effective dashboard. Now, if you want to think through this by yourself for your client or the dashboard that you are building we actually prepared a worksheet for you that you can download at measureschool.com/dashboardplan and there you can fill out this worksheet and really get clear on the message that you want to convey to your audience. And if you’re ready to proceed, then head over to the next video right over there and if you haven’t yet, then consider s

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5 Tips for Building Better Data Dashboards

5 Tips for Building Better Data Dashboards

A data dashboard is a great tool to visually track, analyze, and display key performance indicators, metrics and key data points to monitor the health of a business, department or specific process.

In this video, we’re going to go over some important points that you should consider before building your actual dashboard:

– Your Audience
– Your Story
– Your Data & Sources
– Visualization & Sketching
– Tools & Implementation

Links mentioned in the video:

Telling Data Stories by Daniel Waisberg: https://youtu.be/1MkI5TGBVqQ
Data Studio Tutorial: https://youtu.be/R0rV4ZS-ruQ

Visualization Tools:

Tableau: http://back.ly/KMK7
Tableau Gallery: http://back.ly/dZog
Google Data Studio: http://back.ly/8NGj
Data Studio Gallery: http://back.ly/2XGj
Supermetrics: http://back.ly/wQoy
Supermetrics Template Gallery: http://back.ly/eZoo
Klipfolio: http://back.ly/9KGQ
Geckoboard: http://back.ly/EeGL

Storytelling Resources:
Storytelling with Data: http://back.ly/qYoB
Data Visualization Storytelling Essentials Course: http://back.ly/bmyo

Measureschool Links:

GTM Ressource Guide: http://measureschool.com/guide
Free GTM Beginner course: https://measureschool.com/emailcourse
Courses: http://measureschool.com/products

πŸš€Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

Follow Us

Facebook: http://www.facebook.com/measureschool
Twitter: http://www.twitter.com/measureschool .
.
RECOMMENDED MEASURE BOOKS: https://kit.com/Measureschool/recommended-measure-books

GEAR WE USED TO PRODUCE THIS VIDEO: https://kit.com/Measureschool/measureschool-youtube-gear

– In this video, I’m gonna give you five tips on how you can build better dashboards. All the more coming up, right after this. Hi there, and welcome to another video of measureschool.com where we teach you the data driven way of digital marketing.

My name is Julian, and on this video I’m gonna give you five tips on how you can build better dashboards. This occurred to me when I did the Data Studio tutorial the other day, I was explaining a lot about the feature set of the tool, but really when you build dashboards, you need to take some things into consideration, to build an effective dashboard that actually communicates the right message to your audience.

So in this video, I want to go through some steps that can help you to build better dashboards, before you actually implement them into the tool. We’ve got lots to cover, so let’s get started. Number one, know your audience. So before you start building a dashboard you should be thinking about who is this actually for?

The dashboard itself is a distillation of different metrics, different data points, into a more confined, simplistic way of presenting data. So if you are building this dashboard for your boss, for a colleague, or just for yourself to explore the data by yourself, then you should be thinking about who is this actually for, and is the data that I’m gonna present relevant to this target audience?

This will tremendously help you to shift your dashboard in the right direction, and transport the right message to the right audience. Number two, get your story straight. Now a dashboard is probably there for communication, you want to inform somebody, you want to convince somebody, or you want to enable them to explore the data by themselves.

Now this message that you want to send is an important part of a dashboard, and you should be thinking about it beforehand. So what’s important when you communicate your message with a dashboard, is to stay on point, stick with the story, so you need to have a story that your data actually tells.

So think about, for example, when you go into a meeting and go through the data with your target audience, what talking points would you have, how would you explain that data, and how would the data support your story? There are many different techniques for storytelling, and even data storytelling, and there’s a great video by Daniel Waisberg, which I’m also gonna link up below here on YouTube, that you can watch about data storytelling, but being clear about that data and the story behind it, is a great point to make your messaging stand out and communicate it effectively with a dashboard.

Number three, get your data and your data sources ready. So in this step you would actually look around and see what data you want to use for your dashboard. Now they might be in different sources such as a Google Analytics, a Google AdWords, and you might also want to take a look at your tool, if the tool connects to all these sources, so for example, Data Studio is quite limited in the connectors that you have right now.

What you also want to be thinking about is how you clean and prepare the data, so it is useful for your dashboard later on. So are there any data points, any dimensions you need to pull in extra, because you want to have interactivity on your dashboard later, so have it filtered, or have a date range in there, the data actually, the data structure needs to be in place in order to do all this.

So prepare the data and the data sources beforehand, so you can start building your visualizations. Which brings us to number four, which is sketching out and visualizing. Now before you start fiddling with the tool, I would actually recommend to get out pen and paper, take your audience, take your message and your story that you want to convey and take the data, and sketch them out on pen and paper, how would you arrange your data on a canvas, which visualizations would you use to actually communicate your data effectively?

At this point in time, you can also start looking at other visualizations that other dashboards, how others have done it, there are great resources for example for Data Studio, there’s the Data Studio Gallery, there’s something similar for Tableau or for Supermetrics, or whichever tool you use to do your dashboards and your visualizations with, get inspired and look for the most effective way to present your data.

Now there are many other resources on data visualizations out there so I’m gonna link up some resources in the description below. And then we get to tip number five, which is getting your tools ready and then implementing your dashboards. Now it’s essential that you prepare a little bit before you start building a dashboard, how to actually use a tool, so our tutorial on Data Studio is a great start if you want to work with Data Studio.

There are also great resources out there for Tableau, or, we did a tutorial on Google Sheets, that lets you get started with the whole data visualization part, because you don’t want to just take your plan and start trying to implement it, you should be able to know which visualizations go where and how you can customize your visualizations to tell, again, your story.

And it’s all about being efficient here, so you don’t want to spend too much time fiddling around with the tool, but concentrating on getting your message across with a better dashboard. So I hope you find these tips useful. Just to recap, number one, know your audience, number two, get your story straight, and then three, prepare your data and your data sources, and then number four, sketch and visualize, and finally, get your tools ready and implement your dashboard.

And I’d love to hear from you if you have any tips on building better dashboards, please leave them in the comments below. And as always, if you like this video, please share it with a friend or a colleague, give us a thumbs up, hit that Subscribe button, so you will get new videos every Wednesday from us. My name is Julian, till next time.

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Google Data Studio Video Course

Google Data Studio Video Course

Google Data Studio can help you import data from different sources and visualize them on a dashboard you can share with the world. In our tutorial, we are going to show you how to build such a dashboard including the visualizations you can use, how to import data and build in interactivity features.

The Dashboard we built: https://goo.gl/A0wdVU

GA Demo Account: https://support.google.com/analytics/answer/6367342?hl=en
Google Data Studio Gallery: https://datastudiogallery.appspot.com/
Data Studio Video Tutorials (Google): https://support.google.com/360suite/datastudio/answer/6390659?hl=en&ref_topic=6267740
6 Advanced Techniques to master GDS: http://www.benlcollins.com/dashboard/google-data-studio-tips/

GTM Ressource Guide: http://measureschool.com/guide
Free GTM Beginner course: https://measureschool.com/emailcourse
Courses: http://measureschool.com/products

?Looking to kick-start your data journey? Hire us: https://measureschool.com/services/

RECOMMENDED MEASURE BOOKS: https://kit.com/Measureschool/recommended-measure-books

GEAR WE USED TO PRODUCE THIS VIDEO: https://kit.com/Measureschool/measureschool-youtube-gear

In this video your going to learn how to build dashboards with the help of Google Data Studio. You’re going to discover how to import data, visualize it, and share with our stakeholders. All the more coming-up right after this.

Hi there, and welcome to another video of measureschool.com, where we teach you the data-driven way of digital marketing. My name is Julian, and on this channel we do tutorials, how-to videos, and take a look at the latest marketing tech. Just like this one. So if you haven’t yet, consider subscribing. Now, looking at data in Google Analytics can become overwhelming really fast. You have so many reports, so I usually recommend using it only as an ad hoc research tool, and not to actually present your data, and findings to your clients or stakeholders. The route we usually go is to pull data from Google Analytics into other tools, such as a Google Sheets, to analyse, and then visuals, and show to our clients. We made another video about this that you can check out in the description below. But if you’re searching for an easier point-and-click dashboard solution, you might want to check out the new Google Data Studio. With the introduction of the Google 360 Suite, we also got access to this tool for free, to build our reports and dashboards. So it’s time to take a look at this new piece of marketing tech. We’ve got lots to cover; so let’s dive in. – [Narrator] Today our journey starts at, datastudio.google.com where you will get access to the beta version of this new product of Google. Now, with this free version of the Google Data Studio software you will only be able to build five reports, but it will give you a great overview about the tools you can use with Data Studio. Now, before you’ll get started with building a dashboard, I would actually encourage you to think about the audience you’re trying to reach, the purpose of the dashboard, what data should be on there, and maybe even sketch it out beforehand so you know what you’re looking for in the tool, and what data you need in the dashboard to build it with the help of Google Data Studio. Now, in our case I want to show you the functionality. So we’re going to build a general digital Analytics Dashboard, and we’ll use the data of the Google Analytics demo account; that you can also get access to. I will link up the instructions in the description below. So you might be familiar with the dashboard function within Google Analytics. This is pretty limited, and we now have the ability to pull the data from Google Analytics directly into Data Studio, and build our dashboard there. So let’s do that. First of all you can choose from a variety of templates. Some are good some are not so good, but what we want to do here is start with a blank report, and the first thing we need to do is actually pull the data in that we would require to build this dashboard. So google gives you, actually, some sample data that is available if you want to try it out. You can also use your data connectors, and build a new data source. Now, these connectors are basically the ability to directly connect to the data source. A lot of Google products here, but we also have some more open capabilities. Such as the ability to connect to MySQL database or to Google Sheets, where you could really import any kind of data, and do any kind of calculations that you might want. For now we’ll go with Google Analytics. We need to authorize our account. Which means our account needs to have access to the Google Analytics account in order for us to pull the data into data studio. If that’s the case you can choose here your account, and your view, and where you want to pull the data. Connect this all, and you will get an overview of the dimensions and metrics that can be pulled. Now, this is pretty standard. Google Analytics obviously integrates very well with Google Data Studio, but if you would link up a MySQL database or a Google spreadsheet you might need to define the fields, the type, and give it a description so you’ll be able to identify your fields, and your data that you’re working, with in the interface later. As I said this is pretty standard for Google Analytics so let’s add this to the report, and we are good to go to start building our report. Now, this is the blank canvas that we will be working with. By default, it is in portrait mode. Let’s change that over by going to the theme settings here, and as the layout I want to choose landscape. This is normally what I would use to work with. Now we can start building our visualizations we have different tools available up here. Better described, also here under insert, and you can simply choose one, for example the scorecard here, and draw it on our canvas. Just like this. This will connect to Google Analytics pull the data out, this is happening live, so you have the most recent data in here, and also filled, already, a metric that you might want to use. If you don’t want to use it, you can simply go to the metric and change it around. For example, the Users here. You can also heavily customize this, if you, for example, want to compare it, give it a bit more context, you could add a comparison here to the previous year, which will add this little date range comparison to your graphic. It’s also easy to then go ahead, and copy-paste this into your document. Again, align it and then change it over to the next metric that you might want to display. Now, let’s go ahead and use another visualization type. Let’s go to insert here, and use the time series, and draw something on our canvas again. Some data is fetched; now we want to change this data around. I want to, actually, know the Users here again so I’ll change the metric, and I actually want to give this a little bit more context again, and compare this, so I add another metric which are our Transactions. Now, this is a bit hard to read, so let’s style this a bit more, you can customize your visualizations, to a certain degree. Not everything is possible, but certainly the basics are there. You can change, for example, this line chart here to a bar chart, and also put another axis in so that it all gets a bit clearer. The same is possible with our other bar charts here; that we can utilize. Let’s make a country comparison here. So instead of looking at the Source we will look at the Country, and, again, look at Users, maybe add another metric, which would be new verses old. So that is now added to this chart. Again, we can customize this to get to the style that we want. And even change stuff around inside of the visualization its self, until we get our data to be like you want it to be. Then we can go to another visualization type, a table is often used in data as well. So let’s try this out, draw a data table. Just a little bit small here. So we can always change the element, by dragging and dropping it, and also customizing the data, again, that is seen here. We have here sessions, let’s say, we want to have the Conversion Rate next to this, as well. So let’s look for Conversion Rate, and it will be built. You can also change the order here if you want to by, again, dragging and dropping your metrics. I’ll make this a little more clearer. Great. And if we want to highlight some details here we can also go into Style, and edit this column. We can, for example, put in a heat map for column number one. That will show us the data here, now it’s not as readable anymore. Let’s change that around. And in the end, we’ll have a nice little table, that let’s us know all the data that we would need to know. Again, it’s easy just to copy-paste that if you want to have another data roll, exactly the same formatted. Let’s put this over here, and change this around. Next what I want to do is, actually, pull another metric here for our scorecards out of a different data source. So let’s copy that over, next to it, and let’s go back here to our data, and we don’t want too use Google Analytics anymore. Let’s try something else. Let’s go over here and create a new data source. I’ve already prepared a Google Sheet. Now, this Google Sheet could be any data point that you want to import. I have here a number of calls and the date range, so let’s import that. Connect it all up, and we get our familiar screen here. Google Data Studio did a great job of finding out that this is a date type, and a number here, and we can edit all to our report. This will be connected. Obviously we need to change, here, our metric. Now the date range doesn’t go as far back, to see what the change was here. So importing data from a different data source is possible, but you would need to use another visualization. You’re not able to, actually, mix data with different data sources. Another feature that I want to show you are calculated metrics. So you might know this feature from Google Analytics it’s self What you can also do is calculate metrics directly within Google Data Studio. So for example if you wanted to have a transaction per user we would be able to calculate this because it’s not in there by default. Let’s go into metrics here, and we’ll create a new metric that will be Transaction per User, and we simply need to put in a formula which we can do by start typing the metrics that we want to calculate. So in our case it will be Transactions divided by Users. We can simply create this field, and it’s now available for us to pick from the stack. So this is a great feature, again, to customize our data, all-in-all it’s a bit hard to clean, and transform your data, and that’s why I would actually recommend to pull it into a spreadsheet first, do your calculations there, and then push it out to Google Data Studio. Now, the last thing to do is to add a little bit of styling, and clean-up a little bit of the visuals here. So we can use some of the styling options with the rectangle here. So you can draw, actually, into the canvas, some design elements. Let’s do this really quickly. It changes a bit more to the style of Measureschool. Upload an image. Change a bit of the formatting. Alright looks good to me. Let’s look at our end product. We can go here to the edit mode, and you could see this is something I could share already to my friends and colleagues in order to inform them about the performance of this demo account. Now, one thing that is missing is, actually, a little bit of interactivity, So we already see that we have controls when we hover over certain data points. That these are interactive, and we can kind of see what’s going on, but if you want to give the user control, and this also depends on our data story, If you want to do that, then we can build that in as well. So let’s go back to the edit mode here, and build in some controls. There are, actually, two controls, right now, that you can build in. One is the date range picker. This is the same, that you can see from Google Analytics. Basically gives you a date range. We would need to change a bit of colour here, so that it’s visible, and if you go into edit mode we can select our date range, and we could say we’re going to have the last 30 days. Apply this, and this will pull the data, newly from Google Analytics, and update all our visualizations, here. So very handy when it comes to giving the user interactivity to dig through the data themselves. We can also edit in filter options. So let’s do this really quickly. We can use this further control field. Now by default this is a checkbox list, but we can also change it into a dropdown menu, just like this, and give the user a choice which data he wants to look at. So for example here I would like to let him sort this by the Source. So he can filter out dynamically, Source. We would need to connect this back to our Google Analytics data, and the dimension here would be Source, and Source Medium, and the metric we are looking at are Sessions. Let’s change the styling of this. Now if you go back to our view mode here we can actually get a drop down list of all the important fields, and if you only wanted to look, for example, Google/cpc data, Google AdWords data. We can automatically, reload our report, and update the numbers, and then see how our store is performing or how our website is performing. Only looking at that data source. So very handy, if you want to give interactivity to your users. So let’s say this is done, and now we want to present our data. What are our capabilities here. So first of all you can at any point share the report, even too collaborators to work with you on this dashboard. So you can invite them and give them added access, you are the only one who can delete it because you are the creator of this report, but you can invite somebody to access this report, and edit it with you. You can also invite people to view that report, if they have access to Google Data Studio, they would be able to play-around with the data, only the interactions we have defined on the page itself. Now you can also do is actually get a shareable link, and this will enable you to take this link put it into an open intranet or send it around to friends. Again, here you can view or edit, the same options that you would have with a document in Google Drive. Now currently their is no possibility to actually embed your dashboard into an intranet or onto a client’s page or into another dashboard that you might have prepared. Maybe that’s another functionality that will arrive soon. Another capability is to actually print this out as a PDF. So if you’re in view mode, you can go ahead, and print this whole thing by opening up your print settings and saving it as a PDF. Unfortunately you would need to do this with every page that is out there on your report. Now we’ll make this little dashboard I have built, it’s not very there could be some more tweaks that we could make to it, but anyways this was a demo that I wanted to give you for the capabilities of this dashboard tool. I will make this available to you in the description below. So you can actually copy it, and implement it to your data source. If you might choose so or if you want you can also go ahead, and go over to the Data Studio Gallery. Which features some really cool visualizations of data that were built with Google Data Studio. All of them are also free to open copy into your account, and then run your numbers on them. In the end don’t forget to give your report a name. Share it to your colleagues or your friends, and I hope this was useful so you can get started building your own Google Data Studio dashboard.

– So there you have it this is how you can import data, visualize it, and share it with your clients, and stakeholders, With the help of Google Data Studio. If you are already using Google Data Studio. I’d love to hear your experience in the comments below, and as always if you like this video please share it with a friend or colleague, and subscribe to this channel because we’ll bring you new videos every Wednesday. My name is Julian, till next time.

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