While Google Adwords is a great tool for creating ads and targeting a wider audience but when it comes to optimizing, it lacks one of the most important information about your customers – the behavioral data. Without it, you can understand what is happening but you can’t able to understand why is something happening?
So if you are interested to learn how to optimize your campaigns and keywords like a pro then read the post till the end.
1. Using context to find insights –
Before getting too deep, let’s first understand why context is so important?
If you look at the session trend above, you can see that it going up and down, overall it looks good. But nothing much, it’s not very clear what to do next.
Now rather than looking at a metric in isolation, let’s compare two metrics together to get some context. Here I am comparing Impressions and CTR.
Now you can see above that the google store has a huge spike in impressions on 18th June but the same day, it has the lowest CTR. And you can also see that as the impressions were getting lower and lower after 26th June, the CTR started to go up, in fact, it reached the highest point during the entire month. So, you can see that having more impressions is not good enough if people aren’t clicking on your ads.
I have written a whole post on this topic, please read it to learn more – 5 ways to use context to find hidden insights from your data.
Download the above GA custom report – Paid Search report.
2. Finding most valuable customers –
If you have a limited budget then it’s very critical to target only customers who are most likely to convert. So, how do you find them?
A great starting point is the Google Analytics map overlay report. Map overlay report gives you the breakdown of important metrics by country, region, city, etc. If you want to follow along then download the report – Map Overlay report.
We can see that the United States is performing better than any other country, have higher users, low bounce rate, etc. The second good performing country is Canada with good revenue and Per session value, followed by Australia, but not as good as it should be.
But what’s up to other countries in the list, the revenue from japan is $0.00 revenue, OMG!
Let’s see why is this happening?
Click on the comparison tab at the top right corner and change it from user to bounce rate from the drop-down menu compared to the site average.
What is Bounce Rate?
Percentage of all sessions on your site in which users looked at only a single page and leave it right away without taking any action.
In plain English – Users didn’t find your website helpful, they came and left.
Bounce Rate is one of the most important KPI (Key performance indicator) that you should look at when optimizing your campaigns.
Low Bounce Rate – Good
High Bounce rate – Bad
In the above picture, you can see apart from the United States and Canada, all the traffic from other countries are bouncing at a high rate which is why the per session values of these countries are so less.
Now go back and click the Per session value column to sort the report from highest to lowest, previously it was sorted by users.
Look at the countries in the green box. These countries were totally out of the picture before. Low traffic but a higher Per session value.
Also, focus on the per session value of Panama, the only sad thing is that the traffic from Panama is very low. I wish we had more users from Panama. Now we know where do we need to focus and take the advantage of the opportunities that lie ahead of us. Later in the post, I will describe some more amazing techniques that will help you to do it. So keep reading, don’t stop 🙂
Let’s focus on the United States because 47% of the users and 95% of the revenue of this website comes from the US.
Just click on the United States to drill-down to the regional level. Now, Look at both the maps.
If you look closely, you can see that although we have the highest number of sessions from California but Per session value is highest in Massachusetts. Look at the map to compare the performance of different regions in terms of sessions and per session value.
You can hover your mouse anywhere on the map to see respective values and you can also further drill-down just by clicking anywhere on the map itself.
And when you do the analysis, don’t forget to also use some behavior metrics like bounce rate to get the complete picture of performance. Always use Acquisition, Behavior, and outcome framework in your analysis.
3. Campaign Optimization –
The above report is sorted by RPC. The goal here is to understand where are we making the most amount of money for every click compared to how much each of those clicks costing us.
Look at the “Electronics” campaign, OMG it has the highest number of impressions among all campaigns but $0.00 in revenue, So pathetic. No wonder, why the impressions were so high but CTR was so low, as we saw earlier in this post.
We can’t measure the (not-set) in Campaigns because Google analytics didn’t receive any information about the visits associated with it.
The only campaign that is performing well is “Accessories”. Let’s dig deeper to understand why the Electronics campaign is performing so badly and try to optimize it.
The match type selected for this campaign’s keyword is Broad match to show the ads to a wider audience. If I click on the electronics campaign and then the sunglasses brand group, it will show you the keyword report.
We can see that the website trying to bidding on the “women sunglasses” keyword but due to the broad match, the keyword is matching with lots of different search queries which is not relevant to this website like jimmy choo, MLC, sunglasses dealers, etc.
Search queries are the actual queries that people typed into the search engine.
Almost 8 out of 10 search queries are different from the keyword they are bidding on. The broad match helped the website to target wider audiences but customers are not relevant to the site. The customers are looking for something else hence a higher bounce rate. Using a more strict match type will reduce this error. Try changing it and then adjust according to it.
Use the inline filter to only select the “Aw-Electronics” campaign then drill-down to keywords and then add a secondary dimension “search query” from the drop-down list to get results as I did above.
4. Keyword Optimization –
We will again apply the same technique that we used before but this time to find out keywords that are bouncing at a higher rate compared to the site average.
It turns out that out of the top 20 keywords, the keywords related to Google store, youtube merchandise, Google products, and Google backpacks are bouncing at a very higher rate.
To optimize these keywords, we are going to use a custom report – PPC keyword/matched query report.
As we saw earlier that if the keywords we bid on and the actual search queries used by the customers are different than the keywords or campaigns will have a high bounce rate and lower conversion.
Let’s see if this is the case here-
The match type used for “google store” is an exact match and if you click again on it you will see the actual query.
As it turns out there isn’t much difference.
So what we do now?
Let’s dig a little bit deeper to see if the users are landing on the right page or not?
It is also not the case. The visitors are landing on the right page, the Google store homepage.
Let’s not lose hope, try one more time. Apply the secondary dimension “device category” to the report. Now, look at the below pic.
It looks like people have some difficulties in using the website on mobile and tablet compared to desktop. They are not converting at all in this case.
Let look at the next keyword – Youtube merchandise.
Same story here. But if you look at the below pic, you can see that people are landing on the wrong page.
Rather than sending the traffic to the youtube product page, the website is sending the traffic to the homepage.
By looking at some keywords, we find out that people are getting redirected to the wrong landing page and also there might have some issues in using the website on mobile devices.
To be more confident in our hypothesis that people are finding difficulties in using the website on mobile and tablet devices, let’s use Advanced segmentation.
As we can see that the visitors are bouncing at a higher rate on mobile and tablet compared to desktop. E-commerce conversion rate and per session value are also low for mobile and tablet traffic.
And if we look at the segmented keyword report by device type, here also we can see that lots of keywords have zero or less conversion and per session value compared to desktop.
Now the next question is – What to do if you have a large volume of keywords?
It becomes a big problem when we have a very large volume of keywords, pages, etc. Most of the time we only look at the top 10 or 20 rows of data and move on with our life. But the top 10 or 20 rows rarely change too much.
So, how do you find hidden treasures?
A. Use inline filter –
Click on Advanced.
Now select Bounce rate and per session value. In this example, we want to find out keywords which have bounce rate lower than 30% and has per session value greater than $5. Hit apply and boom!
Now, you have a list of keywords that are performing very well. You want to invest more in these keywords, learn from them and understand why they are performing well and apply them to other keywords. You can use these techniques to also find keywords that are performing worst just by changing the filter criteria.
B. Term Cloud –
First, go to Acquisition > Adwords > Keywords
want to see which keywords are generating more revenue?
Here it is. One thing to remember when using the term cloud. It will only show you the total rows of data that are selected at the bottom. So if you want to see more rows of data just change the number of rows from the drop-down menu.
Let’s see, the visitors from which keywords added products to the cart and started the checkout process?
Now, you have the answer.
Ok, now let’s check out the visitors from which keywords completed the purchase?
Now compare both the visualization and find out visitors from which keywords started the checkout process but didn’t complete the purchase. Find out what caused them to abandon the purchase? Look at where these people are coming from? what can we do so that this doesn’t happen again? Real analysis with amazing insights.
C. Weighted Sort –
What is a weighted sort?
Weighted sort applies a smart algorithm to your data to bring the highest and most statistically significant metrics to rise to the top.
To use weighted sort, click on the bounce rate ( or any other percentage-based metrics) column header in the table. Then above the table, use the sort type selection menu to select weighted.
If you do that you will see a list of keywords that the Google analytics algorithm thinks you should focus on.
Wait there is more.
Now reverse sort the table.
Now you have a list of keywords which already have lower bounce rate and if you invest more on these keywords and optimize them further, you will make more money from your ads and keywords. No more guesswork only goodies.
One more tip – you can apply weighted sort on almost any report in google analytics like traffic source/medium, landing pages, internal site search etc.
want more tips? keep reading 🙂
5. Ad group optimization –
We learned a lot of ways to optimize our Adwords ads. In this section, we are going to use another great visualization technique to optimize the performance of our Ad group as well as campaigns and keywords. Let’s get started.
First, Go to the Acquisition > Adwords > Treemaps
Here we are comparing the number of users (Acquisition metric) of our ad groups to the bounce rate ( Behavior metric) of those ad groups.
Just by looking at the treemap, we can now understand that Merchandise brand[E] has received more users and has a lower bounce rate compared to other high traffic ad groups like Merchandise-brand [BMM] and store-brand[E]. And if we look at the bottom right of the pic, we can see that some of the ad groups like Swag-brand[BMM] and gear-brand[BMM], although has low traffic but the bounce rate of these ad groups is even lower.
Now, let’s compare an Acquisition metric to an outcome metric to understand the complete performance of these Ad groups.
Previously we saw that the bounce rate was very high for the Store-Brand[E] ad group but after applying an outcome metric “Avg. order value”, we can see that this ad group have a very good avg. order value. And If we reduce the bounce rate of this ad group, then we can make even more money from it.
If we have only applied the Acquisition and behavior metrics in our analysis, we would have made a wrong assumption about this ad group. But after applying an outcome metric, we are now able to see the complete performance of this ad group.
As I said before always use the ABO framework in your analysis to get the full picture.
Want to know which keywords are performing better in a particular Ad group? Click on any ad group to drill down to it.
Now, just by looking at the treemap, we know which keywords are performing better in each ad group.
6. Bidding strategies to maximize the ROI –
Rather than spending all your money equally during the whole day and week, you can get more out of less by spending more when your customers are more likely to convert and less when they aren’t. Hour of days reports in GA under the AdWords section exactly help you do that.
You can see that though people are coming throughout the day, sometimes more or less but most of the purchase is happening during 10 & 11 am, then during 2 and 3 pm, 5 pm, and 7 and 8 pm in the night.
And from the day of the week report, it is clear that most customers are buying on Wednesday, Friday, and Saturday.
Increase your bids during these times of day when your customers are more likely to convert and reduce the bid during other times.
7. Multi-Channel Funnels for Adwords –
In Google Analytics, conversions and E-commerce transactions are credited to the last campaign, source/medium that referred the user when he or she converted.
But in reality, customers interact with your business via various channels before making the final purchase.
But by Default, Google analytics will attribute all of the credit or e-commerce revenue to the last marketing channels or source which leads to conversion. This is called the Last-Click attribution model. Which is not fair to the channels that come before that.
So the question remains – how will you give credit to all the channels and how much?
In the above report, you can see that the direct channel is closing most of the sales but referral and organic channels also contributing to close the sales by introducing new customers to the brand.
The Multi-channel funnel report in Google Analytics exactly helps you to solve this problem. It’s not perfect but far better than using the last-click model.
A. Assisted Conversion report –
Assisted conversion and assisted conversion value – tells you the number of assisted conversions and their monetary value. The higher these numbers, the more important these channels are in assisting the conversion.
Last Click or Direct conversions and Last click or Direct conversion value – tells you the number of last click or direct conversions and their monetary value. The higher these numbers, the more important these channel’s role in closing the sales.
Assisted/Last Click or Direct Conversion – is the ratio that summarizes a channel’s overall role.
A value close to 0, indicates that the channel completed more sales in the last stage of the sales funnel than it assisted.
A value close to 1, indicates that the channel equally assisted and completed sales.
A value greater than 1, indicates that the channel has a bigger role in assisting sales.
In the above picture look at the last column, you can see that Display is doing well when it comes to assisting conversion compared to other channels so you might want to invest a little more in this channel, see how things work.
The value of Paid search is 0.59 which indicates that it mostly helps in closing more sales in the last stage than assisting.
You can also see the multi-channel funnel for your Adwords ads.
We can also see which Ad groups and keywords are driving more assisted conversions.
All web pages and Google ad groups have the highest value, driving more assisted conversions. while Store Brand[E], Drinkware brand[BMM] and Gear brand[BMM] all have the ratio of 1 means these ad groups are equally helping in assisting, and final conversions.
If you click on the other drop-down menu at the top, you can apply lots of other dimensions to this report like Source/medium, country, device category, etc.
B. Model Comparison –
Go to the Conversions > Attribution> Model comparison tool
Select the Time decay model against the Last interaction.
Now, look at the last column % change in conversions, as we can see Dynamic search ads have a positive 37% shift from the reference model in this case Last interaction. Again we can see that Dynamic search ads are performing better than we had given credit to i
Also, look at the CPA column and compare between two models. We can see that the CPA for Dynamic search ads is not $50, it is $37.
If you want to understand and measure your campaigns more effectively then, Upload the cost data of all your marketing campaigns and Use the Assisted conversion and model comparison tool to better allocate your marketing budget across different channels and campaigns.
I hope, you find these tips helpful. Please let me know in the comment section below.