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From Zero to Goоgle Data Studio Hero


Nick's template →



Paul: Right then, so we're live guys. Yeah, hello everyone that's already sitting here watching. What have you guys been up to, before we get started? 

Matt: Just general day-to-day life of Data Studio really. Messing around with reports, trying to fix everything. Make sure we're getting where we need to be. Yeah, I say that's been pretty much my week so far anyway. 

Nick: Yeah, I'd say pretty similar here. Doing a lot of auditing at the moment. 

Paul: Right, thanks for everyone joining us. Today we're going to be going over Data Studio, with two Data Studio jedis here, as I call them, Nick and Matt. I'll let you guys introduce yourselves to everyone, so they understand who you are and where you come from. 

Nick: My name’s Nick. I've been primarily an SEO really for the best part of 20 years. I work with various clients, usually enterprise-level, Vodafone quite a lot. I don't think the American people will be too aware of them, but they used to be over in the US at one point. 

But yeah, very much into Data Studio and data and understanding how to make, or how to drive my activity with analytics really, with that political activity through the organization. Or, the data that we need to do proof concepts for SEO work. 

Matt: My name is Matt, I'm SEO manager at Rise at Seven. We're a creative SEO agency, work with a large range of clients. Always looking out for Data Studio stuff, basically, it's primarily what I'll do. 

I've been an SEO for probably just over five years now and pretty much straight away took on Data Studio and thought, "How can we start reporting better for everyone else? Give everyone more insights and just try and automate everything as well." 

Paul: Automation, that's great, and I believe you guys have been having a little play around with the SEMrush Data Studio connection. So, who wants to go first and show us what you've managed to come up with?

Google Data Studio SEMrush Connector

Matt: Fantastic, I'll go first. I've just been playing around with the SEMrush Data Studio connector. It's a relatively new product that they brought out, but one that's definitely made everything a lot easier. 

I've put in a varied sort of range of different things that you can do with this, some a bit more advanced, some a little bit easier to get to grips with straight away. 

The first two graphs that you can see, essentially using the blend of SEMrush, Google Analytics, and Google Search Console. Each of these we've blended the data sources and it basically allows us to see for any change that goes across in visibility through SEMrush. What difference does that make to our sessions? And also, the impressions that we're seeing as well. 

Then again, just replicating a very similar graph or just this time use the average position with organic sessions themselves. It just gives you a nice way to kind of pull through various data from different sources and see how they're actually affecting each other as well. 

Here we can see the sessions in Google Analytics and there's a separate graph for impressions from Search Console, building it all into one and blending is probably the easiest way to do it. A couple more we've got there are using the position tracking tool.

What we've done here is also then blended that with Search Console data, so we can see the position and the volume that we're getting through SEMrush there. But, we can also then see the impressions, clicks and click-through rate from Search Console. 

You could add previous position there as well or the difference in position. You can kind of see the difference you can get through click-through rate, the amount of clicks or impressions dependent on which position you start in the search results. 

Another one there, we're looking at the traffic and the search volume for each term that I've come across during each day. I'm then looking at the traffic percentage that we're driving as well at that time. These are just a really good way to kind of track over time for different implementations that we're making on the website or for any ranking improvement you might be seeing. 

What impact is that having on the bottom line of the business as well? One of the connectors that SEMrush have built is obviously their Backlink Analytics. We can start seeing the top referring domains as well. What this does is just allows us to check each referring domain for that chosen website. 

We can start seeing who's linking to them, see the authority score. You can play around with a little bit of a formula and pull through the logo as well, if you wanted it to look a bit more visual. Unfortunately, that's not built-in to Data Studio, but there are ways around it. 

Moving forward, looking at the Site Health Audit as well. This is a really good one to have, a very good overview of how's your website performing and what SEMrush is seeing through their Site Health Audit. We've got a nice little barometer there to see where's your site health sitting. 

Obviously, you always want it to be in green, so it's nice to have it visually as well. Then, out of everything and all the pages that crawled on your website, how many warnings, errors, et cetera are we seeing as well? 

For each of these, you can start to compare them day on day, so you can start seeing once we've implemented these fixes, what impact is that having and are we actually getting to the bottom of the issues? So, I will let you jump on now, Nick. 

Visualizing eCommerce SEO Metrics

Nick: I didn't get too much time to go into the SEMrush connector, but I'm very happy it's there though. So, I've started looking at the various metrics and data points, that's definitely going to be useful. 

I mean, essentially this is taking some of my previous work and then what I'd do with the SEMrush connector is exactly as Matt's gone ahead and done, is kind of overlay the positioning over some of these e-commerce graphs. 

I mean, this is essentially data coming through from GA, so it's using GA as a source. But, you can see here how you have, you can organize your digital sales, your visits to the site. This is very orientated towards the commercial metrics. 

We can then switch and see different channels. And, it would be brilliant to overlay the SEMrush data with this, so that we can start to see, as ranking positions improve, how that affects some of these commercial graphs. 

We'll look here at the business impact, revenue that's generated, average order value, the devices that users are on, channels that are driving revenue. That's quite a useful one, I seem to use that quite a lot. It's nice to see organic search at the top there, that's a very good way to visually explain to your stakeholders how important organic search is, and top-selling products as well. 

Google Trends data, I'm a huge fan of, so again we kind of look and see what the interest is here for different terms. Again, this is quite useful from a commercial standpoint. You can find different Google Trends points that are quite interesting to people.

Let's do something on this page speed. Yeah, so if you go into conversionuplift.co.uk, you can see here that Neil has actually created a guide here, a really step-by-step guide to putting this report together. I'd absolutely recommend that, go have a look. 

It's conversionuplift.co.uk, “how to create a page speed insight competitive dashboard”. I think we'll share some of the links after this, but that's a very handy report.

Nick: I was just talking to someone yesterday about Brandwatch, how to connect Brandwatch data into this, simple web data into this. This funnel has 500 different marketing sources, and all of these ones can be paid for and they mean that you don't have any programming to do at all.

This is kind of the basis behind what makes us excited about Data Studio, is the fact that we get access to data from different platforms and we can blend it together exactly as Matt showed you in his report, to really kind of get different insight. We've got two completely different data sources, we blend them together and we get to see ranking positions over revenue or anything like that. 

Couple of tips. One thing I quite liked doing within my reports is linking out to other reports, because there's so many people working on Data Studio already in the community. The last tip that I really like is putting in a contact page. It's brilliant in a report, I don't think enough people do this. So, I always make sure there's a connector and details there. 

You can also embed other documents into your Data Studio. You basically can create that, maintain that centrally and then you can include that data in your report, so it's quite handy. That's the SEMrush guide to metrics and definitions. 

Viewing Competitor Metrics and Tracking Keyword Position Changes in Data Studio

Paul: Someone's asking about...Where you can look at competitors and start to understand their metrics and keeping an eye with the main analytics section of the connector. 

Matt: Obviously, once you build out your dashboard and build everything that you need for your business internally, at that point or for your client, that's always going to be the first port of call. You probably won't need or be able to access half of that information for all of your sort of competitors as well, but there are definitely things we can see. 

We can start looking at the CrUX data for various domains, so you can start pulling in competitors there as well. Again, there's just a lot of data that you can pull through so you can run site audits using SEMrush for example, and just start to pull everything through to get a comparison of yours or your clients website vs. competitors as well. 

Paul: That's it and I like the way that you blended the Search Console and the analytics with your positions. I don't know if you want to show that to the people once more. 

Matt: Perfect. Yeah, I'll zoom in a bit and hopefully make it a bit better to see. Essentially using this one, what we're doing, is taking the position tracking that's available within your SEMrush account. Obviously, use sort of the keywords that you want to track there. You can add whichever ones are most relevant for your business. 

By default, you'll be able to pull through the keyword, the position, and the volume. But, there's also additional metrics you can get there, such as previous positions, based on the timeframe, and anything that you'd expect to see within your SEMrush account anyway. 

What we can do then to sort of take it to the next level is, by blending it with Search Console, because we can use connectors to say, "These dates match so we can use the dates as a join key." To blend any data you've got to have join keys. Each set of data or each data set you're pulling through needs to have at least one common denominator. Generally, it will be the date that tends to be the easiest one. 

Once you've connected those, you can pull through as many of the dimensions and metrics that are available in each as you're going to need when you're trying to build your table or your chart. For this one, fairly simple, we just decided to pull obviously the keyword position and volume from the SEMrush connector. 

And then, from Search Console, we wanted to look at the impressions, clicks and click-through rate. The main reasoning behind this is saying obviously over time if you tracking position changes, let's say we've gone from position three to position one. What impact has that then given to the amount of impressions that we get, the clicks, and the click-through rate? 

Because essentially, what Search Console can do in the background with Data Studio is match up those keywords with the query that's come through and being reported on in Search Console. 

We're essentially kind of marrying up a few various different part of the data within those, but it gives you a nice overview of saying, "Here's the bottom-line impact, if we can then increase these rankings or even if the rankings drop, what decrease are we seeing from that as well?" 

There's various ways we can build it as well. If that was a table, you could pull it through into pie charts, general charts, line trends. Obviously from each of them, you can then start segmenting as well. 

Nick: Yeah, that would be incredibly useful, because see... I think the problem you often get is the business is sort of saying, "Well, we've moved some positions up to one to three, but you're dealing with web traffic across the entire domain." Then they're looking at their overall GA traffic and they're sort of saying, "Well, has that had an impact on the entire traffic for the domain?" 

Not that it hasn't, so if you could segment that down so you just have certain directories or where you're actually working and improving those directories. I think that could be really useful for you. 

Matt: Yeah, definitely. I mean obviously, using the Search Console connector, you can start to segment it based on which directories everything's sitting on the landing page. If anyone is familiar with sort of the additional filters you can build within Data Studio as standard, you can add them to each various data set of a blended source as well. 

Another example of that that wasn't on that dashboard, but is looking at brand vs. non-brand clicks from Search Console. There's a few ways to do it, you can do it with a case statement, which if you know SQL you can probably build it without fail easily. You're essentially blending Search Console against itself twice, but using various filters to say, "This is branded, this is non-branded," and write a report on that as well. 

How Data Studio Contextualizes SEO Business Metrics

Paul: I like one of the other metrics you put in that Data Studio...was the search volume. I mean, a lot of people don't realize that you can actually pull that through with these reports as well. It gives you an idea of when you compare that and I have some reports that I use Data Studio for where I pull that search volume in. And then I place it next to the impressions that I'm getting within Search Console, so you can really understand what's what. 

I think more to the point is that, where we just literally just had a recent Google update, the type of reports that you're putting together there, like Nick was saying is that when traffic or users are coming through from a certain section of the site and you get hit with an update, like a lot of people have and relevance changes.

Sometimes it may look like you've actually got a drop in traffic, but you do not necessarily have, because it's just..the relevance has kicked in a bit more and there's not really a big shift in actually business metrics as you would say, Nick. 

Nick: I think that's so true, Paul. One of the reasons I got into Data Studio was so that I could visualize commercial metrics around SEO, because often in SEO you're put in a position where you're reporting on rankings and you don't get that interaction with senior people. Having a dashboard allows you to start to visualize those really important metrics that matter for the business. 

Once your stakeholders see the kind of work you're doing and the dashboards you're creating, then that gives it credibility and then you can start to ask, for example, for custom revenue figures that you wouldn't normally get from different parts of the business to be given to you. 

Even with some of the reports that I've built, we've even built them using Google Sheets behind the scenes, because Google Sheets might sound really low-tech, but the integration with Data Studio is fantastic. 

You can have a Google Sheet where you have a certain team in the business filling it out once a month, giving you that commercial information that you need. Then that's being brought into Data Studio with a connector and then blended. That's done against other metrics that you're looking at from an SEO point of view or anything else you're doing. That's amazingly useful, so that focus on commercial metrics is essential. 

Natural Language Processing in Google Data Studio

Paul: We have got a couple more questions coming. What about natural language processing at Google Data Studio? I'm not seeing anything with that, I don't know if you guys have at all.

Nick: I know my team have been playing with that. They've been doing this around intent, so I'll give you the rough outline of what they've been doing without giving too much away. I think they've been looking a lot at People Also Ask material and then taking that in from Google. 

Then also looking a lot at Search Console keyword data, because I know I mentioned earlier that you can download 1000 rows through the interface and get 5000 rows through that connection. But, if you connect via the API, you can get 50,000 rows per day. 

You start to build up a huge database of keyword data from Google. If you take 50,000 is a lot, I mean, as people say, you probably don't need that, maybe you need 70% of that. But, you start to build up a huge owned database of keyword data and then you can start to apply some of these APIs so you can then start to look at natural language APIs. 

You can break down these keywords by intent because I think that's really where we're all moving to in SEO, is how can we be cleverer and how can we understand, yeah, what's behind these terms? Why are people doing these searches?

Then we're providing them with the right kind of information and then we're fitting, and then with Google, because we want to enter that transactional, informational, navigational kind of format. It's definitely something everyone's doing, but if you're getting into that, you're definitely already at the stage where you're putting all your data in BigQuery I'd say or AWS.

Managing and Organizing Data Studio Reports 

Nick: I like Amanda's question. 

Paul: Yeah, I was literally just about to get onto that one.

Nick: Yeah, managing reports, organizing everything. When you're managing the data sources, it gets wildly out of control really, really quickly. A common naming convention is absolutely essential and yeah, come up with that, get everyone to agree to that because otherwise you just will spend half of your life wondering what each source was. 

Especially when it gets into blending, because often with blending you're creating multiple versions of each connection to be able to do the blend. That gets really complicated. Common naming convention will absolutely save your life. 

Unfortunately, that's not really a good kind of folder structure behind it. There's no folder structure behind Data Studio. You log in and you've got your last 90 data reports in there. Honestly if Google could do something, it would be great for them to start to organize folders. 

I used a kind of iconography across each page, so I had performance reports, I then have insight reports, action linked reports. You use different icons in each one and then you can kind of link out, you can use internal links to all the other reports connected to it. 

To be honest, that worked really well for me, because it just gave me a focal point for each team. There was one kind of keystone report that then linked to absolutely everything else and that was then very easy to find. I think otherwise you run the risk of just too many tech reports, people logging in now to them all the time and it's very, very hard to organize. That would be my recommendation. 

Data Studio: Giving Access to Data for Non-Devs

Paul: That's good. Then we've got another one here, which is, "Could you explain on the topic “connecting to API with SEO tools”? Like Nick mentioned, “People Also Ask API." Do you want to pick up on that one, Nick, at all, since they’re mentioning you? 

Nick: I mean, this is the easy bit behind Data Studio, that you have the common connectors. You have community connectors that do the API connection for you effectively. This is why Data Studio doesn't require you to, well initially, to be a programmer. This is why it's sort of democratized data and allowed all of us to become data geeks now, because we don't need to code each API. 

Yeah, your connectors are the way forward and other than your connectors, it's meta connectors. That's the Supermetrics and other people who, if the platforms that you're using don't have a connector created and they're popping up every day, then there's going to be some sort of meta connector that's already connected them and they have 500 plus different connectors. Funnel, Supermetrics, all of these ones work like that. 

Checking Who Views Your Data Studio Dashboards and Reports

Paul: Yeah, Simon Cox has asked a question, which I think you've mentioned this to me before, Nick, about (measuring people viewing the dashboards)

Nick: What you can do in Data Studio is you can add a GA code for each report, which is great. You actually then create a new Google Analytics property. You use that code in each of your reports and if you have different pages, then it will pull through the page alongside the traffic reviews, all the other metrics in relation to the engagement for that report. You end up with a sort of super report. 

Mine’s even got maps on it, so I can see who's accessed from different countries and because I work a lot with multiple markets, I can see exactly who's accessed from which market and the number of users. Having put this whole structure together, I can see exactly the usage that's going on across the group. 

Yeah, GA really is your friend and that's a little thing that's really overlooked with Data Studio, that little box you can put the GA code into. So yeah, add GA tracking to your report. 

Paul: So where do you place that? Is that within the theme or the style?

Nick: It's in the reports setting, it's a very practical one. What's really important then is what you're naming your reports. You can see here that this page is for the revenue, yup, so performance revenue model. Come up with a common naming convention for this and then this will appear on your GA reports, next to your traffic. 

Paul: That is pretty slick. 

Nick: Yup, it's a really useful report, because then you see exactly who's using it and how they're using it and the length of time they using it. What I do is I often launch new pages within this and then see if people are actually using it and that they find it useful and then reporting that back to the business. 

Competitor Backlink Analysis with SEMrush and Data Studio

Paul: Obviously with this, there are lots of ways that you can use the information. You can connect Search Console analytics and obviously SEMrush. Have you guys pulled anything to do with any sort of competitor analysis; how many backlinks they've been gathering or did you get that deep into it at all?

Matt: Yes, I did have a play with it. When it comes to some of the top referring domains, you can look at obviously the total number of domains that are linking to you. You can look at how many have been lost and how many new ones have arrived on each date.

It gives you a really good way to see not only yours, but you can then start using that for your competitors as well. The good thing about the SEMrush connector is the parameters that it allows you to set as default, but you can also have them customizable within the editable part as well. 

By default, you're pulling a specific domain, for example, where you'll pull all the data from. But within the report itself, as long as you've set it up correctly, you can then keep changing that domain and each time it changes you'll pull through that different competitor or a different website that you might own. It gives you a really quick and easy way to be able to just overlay the new information, see it quickly without having to completely rebuild a report and get it all that way.

Date Ranges in Data Studio

Paul: What does the date range dimension do? 

Matt: The date range dimension obviously, by default, you can change the date range that you're looking at reporting on. Pretty standard to what you'd expect in analytics. You can do a sort of customizable specific date ranges, but you can also do month to day, year to date, this month as a whole, whatever it might be. 

The date range time mentioned in the report settings is set in your default date range. If you're sort of reporting monthly for each client, you might want to do it as last month and by default what it will then do is pull from the first day to the last day of that prime month. Some people have more specific use cases in terms of the date, but that will slightly default date range, which it can customize throughout by adding the little date range picker, but that's the default one. 

Nick: I seem to spend half my life trying to get the date ranges right and aligned with the rest of the business. Yeah, good tip. Find out what the rest of the business is reporting on before you make your dashboard. That's my top tip. 

Paul: Right, so I think we picked up on all the questions in the chat there and I know this is quite a sort of hands-on webinar, it's not something that we can sort of go on about for too long. But, I think we can pretty much wrap out unless anyone else has got any more questions. We got one here, “when pulling dates, is it done at the end of the day or sometimes GA takes longer?” 

I see he's asking about obviously, is there a time lag between GA and that would be represented with any of the Data Studio reports. I know generally, there is a little bit of a lag in GA. Especially getting through into conversions. 

Nick: I'd say, I mean, their performance is probably one of the biggest issues I'd say with Data Studio because you'll see it, even when I was jumping in between the screens there. You can see that ends up being an issue. Yeah, I think in terms of that, just think about the charts that you have on each page, don't go crazy. 

Then obviously consider the fact that Data Studio is free, GA is, unless you're on 360, is free. You may need to at some point, jump to BigQuery, which I haven't really talked about a lot on this on. But, having that database storage just does speed things up dramatically, because then you're pulling it from...well, from a database, not from connectors. 

Closing Tips and Wrapping Up

Paul: I think one of the other things we probably should mention is the fact that you're able to email these reports weekly and stuff, straight from within Data Studio. If you've got a client report that needs to be pinged out for a certain date range, and a certain data amount, you can do that.

Yeah, I think that's a wrap, to be honest with you guys. There's no more questions coming in, obviously there's only so much we can go into in-depth. But yeah, if anyone's got any more questions, obviously on the webinar pages it's got all our profiles that you can reach out and ask us. I've learned a lot from this, I hope everyone else has as well, so that's great. Yeah, any last tips from you guys at all, before we wrap this up?

Matt: I think I'd say mine is have patience, definitely have patience. If you're definitely getting into Data Studio for the first time, it's going to be stressful and it will break, just don't let it break you. Just keep going, figure it out and just Google it. That will always be the case, is Google it. 

Nick: Yeah, there's a huge amount of support out there and there's a great community around Data Studio and people will be always there to help you learn that bit of SQL you need to do the trick you need to do. There's a lot of sharing that goes on and really on that point is, go and look at some of the reports that are out there and see it's quite amazing that you can just copy any report. 

And, you'll see that when we share these ones. You literally copy it, add your data sources and you have that work. This almost takes me back to the old days where we were just copying websites to just learn how they worked, and it's amazing. We have a data tool that's democratized really.