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In Google Analytics Essential Training, Corey Koberg shows how to use the Google web analytics platform to generate and evaluate information about the visitors to a web site, including data on site traffic, user behavior, and marketing effectiveness. This course covers the out-of-the-box functionality, from account creation to reporting fundamentals, and explains how to glean insights from the vast array of data available.
There are three reasons the AdWords reports are some of the most powerful in all of Google Analytics: One, because they have the ability to present data that can't be found elsewhere; two, they are extremely actionable; and three, they are directly related to the amount of cash that goes out the door. Improvements based on this analysis could be directly attributed to the bottom line, which always makes for a popular report and usually a popular analyst. We navigate here via the advertising section. You'll see that the AdWords reports have their own section as well, under the main one, and we'll start out in the Campaigns report. By clicking on Clicks in the top navigation, we can see an important mash-up of two key databases: the data about the visits from your Google Analytics data sets and then the rest of the top line matrix associated with AdWords, such as how many impressions, how much revenue, ROI etc that have been pulled from the AdWords database and correlated here.
After all, Google Analytics has no concept of impressions. That happens before you even hit the site and Google Analytics would not have had a chance to run. As we discussed earlier in the chapter, when you turn on auto-tagging and link your Google Analytics accounts with your AdWords, this as all happens automatically. And comparing even these top-line metrics, it can be very illuminating to use the Compare to Past feature. Here we can quickly see that our visits are down only slightly, but our revenue per click has dropped dramatically, so what happened? We certainly want to investigate that in a hurry, especially if you are paying for every one of those clicks that are apparently not helping as much as they used to.
Here in the Campaigns reports, it follows the same hierarchy as if you were in AdWords. Starting at Campaigns and then if you click to view the Ad Groups heading or if you click down into a given campaign, you will see your campaign data broken down into the Ad Groups that belong to that campaign. Since we clicked and drilled down into the Google Store campaign, we're going to see the associated Ad Groups beneath that as the default segment. We're initially sorted by the Visits column, but it's interesting to evaluate the other performance metrics. Since the system knows what we paid an AdWords for the ad click and Google Analytics knows if it brought any revenue in the associated visit, we can calculate ROI statistics, including Margin, which is our net revenue divided by our total revenue--in other words total revenue minus cost divided by the revenue.
In the Margin column here we'll see some things have practically jump off the page at us. 44% isn't too shabby, but -11,000%? We'll certainly want to take a closer look at those Ad Groups and figure out exactly what is going on there. One thing we can see right away is this particular disparity. Every time somebody clicks on that ad, I am paying a cost per click of about a buck 18, but we're only receiving one cent back in revenue per click. So do we want to keep doing that? Not likely. This is highly, highly actionable analytics. These new AdWords reports bring us a ton of segmentation options to really dig into.
Some even get their own dedicated report, as we see over here in the left-hand navigation. Well, look at those in depth, but for now let's look at some of the lesser used ones that still provide a lot of value. There are so many of these available that they actually scroll off our screen, but I want to bring your attention to three in particular that I think we'll want to highlight: Ad Content, Ad Distribution Network, and Match Type. The first of these, Ad Content, shows us how each version of an ad was performing, and it's useful for split testing which, by the way, you should all be doing. In this case, we see we were putting an insertion operator to use. If you are unfamiliar, the insertion operator allows the ad to reflect the exact text of the search query, which can make your ad appear to be highly specific to the search or search phrase.
Now some people speculate that this is good for enticing users to click on the ads because they see the ultra-specific ad text reflected back to them, and they think that your site has exactly what they need. But the suspicion is that the performance of those visits is not necessarily so great once they get to your site, and they realize it's not as perfect a match as they thought based on that ad text. So how can we evaluate that easily? Let's take a look at the metrics we've got here. Assuming the ad is displayed in equal number of times, we just compare Visits and Bounce Rate. Here we see the ad was good at generating clicks, but as we suspected, it has a high Bounce Rate, more than twice the ad without the insertion text.
Sometimes that insertion operator works great. I am not saying it doesn't. But you need to use your analytics to evaluate it carefully for your site. There's also a great deal of discussion about which of Google's ad networks works the best. Well, best is a vague word and there is a lot of ways we can analyze this in Google Analytics, using the Ad Distribution Network as a secondary dimension of our campaign. In this case we can see that in terms of Ecommerce Conversion Rate and Per Visit Value, Google Search greatly outperforms the Search partners. The next segment is Match Type, which shows the performance when the keywords were broad matched, phrase matched, or exact matched, and it's another hotly debated item and you'll need data to back up your own decisions and strategy.
We can do that using the Match Type segment here that shows us the performance of each type, and in this particular account it proves the critics right and shows us why Broad matches often bemoaned. Though it gets far more visitors than the other match type, its conversion rate and revenue are much lower than the exact match. This is not always the case. Check your own stats and do the analysis on your account. The next one is Placement Domain. Here we are seeing the domains in the Google Display Network where the ads have been placed, and we can see how each site is performing. Some sites will have the type of traffic that that is ideal for your business and converts like mad, and some sites may never convert a single visitor.
Here are the Ad Groups from our T- shirt and Jersey campaign, and it's pretty clear that the folks on Google.com are more interested in our jerseys and T-shirts than the other domains. If you're interested in the actual URL, not just the overall domains, perhaps because we're running ads on different parts of the site, we can see that with this Placement URL report we can evaluate the results in order to adjust our advertising strategy accordingly. Next we'll look at the Content Targeting option, which will indicate whether we are targeting keyword searches or specific ad placements on the Google Display Network sites. You don't know the performance until you have the data, and in this case automatic placements are responsible for a lot more visits.
We can continue on with all kinds of combinations of dimensions, secondary dimension, goal metrics, site usage metrics, et cetera, so that we can tweak and optimize our campaign towards specific targets. You can't manage what you can't measure and those who want to manage AdWords will find plenty to do in these reports as they consolidate, isolate, and segment your AdWords data so you can make informed decisions about your ads spent.
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