DIY - How to quickly optimize your Google Adwords Campaigns, Keywords, and Ad groups?


According to Pew research center survey of U.S. adults, the survey finds that roughly eight in ten Americans are now online shoppers. Targeting people online isn’t a problem anymore with Online Advertising platforms like Google Adwords, Facebook ads etc. They have lots of anonymous data of people like Whether someone is married or not, Where they went to college, What kind of topic they talk about online, whether someone clicked on an ad or not and if they did, did they do something valuable to marketers, companies like purchase a product or watched a video etc.



Today, the biggest problem a company has, whether they are Fortune 500 company or a husband and wife running a company from their living room is understanding what the data is telling and make decisions based on the data that the digital world has to offer.
Every Time we google something, Facebook someone or just carry a phone, we create data, yet we do not benefit from this wealth of information as much as we should.
The amount of data created in the past two years is greater than in the entire previous history of human race.
You can invest as much money as you want in analytics tools in the market, you can but the important thing isn’t the tool or the huge amount of data you have, or if you have a free tool or paid, you can get as much data as you need from free tools like Google Analytics. The most important thing is the ability of someone inside your company to find the hidden insights in the data and help you to make decisions as fast as possible.
My promise with this post is that even you are not too much familiar with data or Google analytics, you not only able to understand it but also able to apply it in your own company today. With step by step guide and lots of visualizations, I will make it easier for you to apply it to your data.

Just a couple of reminders before we start, we are going to use Google analytics to optimize our campaigns and use custom reports made by Avinash Kaushik to make things easier and effective.
1. Benefits of linking your Google analytics and AdWords accounts and how to link them via Google.
2. To download the custom report bundle just click here. If you didn’t find any custom report I am using in this post, don’t worry I will add a link of it wherever I used it.
Here are the things we are going to cover -
1. First getting some context to your current performance.
2. Where do your most valuable customers come from?
3. Campaigns optimization.
4. Keyword optimization.
5. Ad groups optimization.
6. Bidding strategies to maximize your ROI.
7. Pan session analysis of your customers.
8. Multi-Channel Funnels for Adwords.
1. First getting some context to your current performance.
Most of the time, When we start optimizing our Adwords campaigns, We jump directly into campaigns, keywords, and ad group. But it is always a good practice to first understand our current performance then optimize. It will help you to see the bigger picture of what is good and bad, Where things are broken, Are you doing good or sucking over time? Let me show you with some examples- how can context bring insight which was hidden before.

If you look at the above pic., you can see that the trend line of sessions is going upward in the right direction with some spikes here and there. Which, is good. You can also see that Google merchandise store has spent $1300 and made $14,902 in revenue and some other data. Everything is looking good.

Now if you click on the date selector at the top right corner and check compared to the previous period and apply. This is what will you see -



Now, look at the report. See, what was missing before. You can clearly see that compared to May, GMS gets more sessions in June. Also, there is a huge increase in Ad impressions 487% and 91% of clicks. But the sad thing is CTR went down and RPC went down and Avg. CPC has increased from $0.17 to $0.33, Which is bad.
But there is something amazing happening, though the cost has increased in June but the numbers of transactions, as well as Revenue, has increased in June compared to previous month.
It would be better if the cost was low for June but If you want to increase your opportunity pie, you have to spend more money to attract more customers. Right ? The real question is are we generating more revenue and profit to run our company more smoothly and stay ahead of our competitors.
One thing to note, don’t forget to calculate the profit.
Overall the performance is good. There are lots of room for improvement, which we will see later in this post how to do it exactly.
See, just by applying a little bit of context, How much more we are able to understand the performance of our AdWords Ads. And you don’t have to stop here, Compare the performance of this quarter to previous quarter or this month to previous month last year etc. Whatever makes sense to you.
One more thing did you notice the green and red arrows, without even looking at your data and comparing, you know what is good and bad. Green - Good, red - Bad.
Let’s look at another example.
If you look closely, you will see that I have changed the sessions from the drop down menu to the left to impressions and compared it with CTR to give context.
During this time period, there is a huge spike in impressions on 18th June but on the same day, the GMS has one of the lowest CTR. You can also see that as the impressions were getting lower and lower after 26th June but CTR started to go up and in fact, it reached the highest point during the entire month.
Life lesson - you can have millions and millions of impressions for your ads but if it is not relevant and helpful to users, then you can’t drive people to your website and get them converted.
Ok, one more example.
It is good to understand your own performance but what about your competitors? Are you crushing them or getting crushed by them? Are you increasing your market share over time? How do you know if you are doing better or worse compared to your competitors? Use competitive intelligence data to gain more insights.
This is the trend line of total visits for the past 6 months of Flipkart, one of India’s biggest e-commerce company. They got the highest traffic in May because they ran a huge discount offer at this time for their 10th year anniversary, then the traffic went down in June. Everything looking cool except the decrease in the number of visits.
Now let’s give some context to the performance of Flipkart with CI data.
Now, look at the above pic. Did you see the difference? Amazon started their operation in 2013, way late then Flipkart, but they are totally crushing them. The difference isn’t one or two million in visits, it’s astonishingly double the amount of visits Flipkart is getting.
I think now you understand Why it is so much important to get some context before diving deep into the data or creating your marketing strategy etc. It will not only help you to make better decisions but it will also help you to think more strategically.
BTW, I used Similarweb for the above competitive data. Please, check it out, it has lots of amazing data about your competitors, Which you can use to improve your own performance and beat your competitors.
Download the custom report used in this section from here - Paid search report.
2. Where do your most valuable customers come from?
One of the biggest wish as a marketer or business owner we have is to target the entire world with our Ads :) 
But money always became a big issue. So to target as wide as possible with less money, we need to think more creatively. That’s where Map overlay report in Google analytics comes in.
Map overlay report gives you a breakdown of important metrics by Country, Region, city etc.
If you want to follow along with the analysis I am doing, Download this custom report - Map overlay visualization report
We can see that United states have the highest number of users. Also, low bounce rate, high Average Session duration, revenue, and Per session value.
The second good performing country is Canada with good revenue and per session value. Australia is good, but not as good as it should be, so does the United Kingdom. We need to do lots of optimizations to improve their performance.
But what’s up with India, Japan, Germany, and Spain. Japan has $0.00 revenue from 1337 users, OMG!
One quick cheap trick to understand the performance.
Click on the comparison tab at the top right corner and change the user to bounce rate from the drop down menu of compared to 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, as Avinash says “I came, I puke and left.”
Bounce rate is a great Key performance indicator(KPI), though it will not tell you everything, but it will give you a great starting point in your analysis then you can go deep down and figure out what is the problem?
In the above pic, it is totally obvious that United states and Canada is doing good and others are doing bad.
Low bounce rate - Good
High bounce rate - Bad
Now we also know why does Australia and United Kingdom has so less per session value because most of the traffic is bouncing at a higher rate.
Now click on 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 in the previous report. Low traffic but higher per session value than the few previous countries.
Also, focus on the per session value of Panama, only sad thing is that the traffic from Panama is very low. I wish we had more users from Panama. Now we know where are we missing opportunities? Later in the post, I will describe some more amazing technique that will help you to do it. So keep reading, don’t stop :)
Let’s focus on united states because 47% of our users and 95% of the revenue comes from the US.
Just click on the United States to drill down to region level. Now, look at both 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 across the map to compare the performance of different regions in terms of sessions and PSV. 
You can hover your mouse anywhere on the map to see their respective values and you can also further drill down just clicking anywhere on the Map itself.
And When you do the analysis, don’t forget to also use the behavior metrics like Bounce Rate, Avg. Session duration etc. to get the complete picture of performance. Always use Acquisition-Behavior-Outcome/Conversions(ABO) framework in your analysis.
3. Optimizing Campaigns -
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 click 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. We are losing money for each and every click from this campaign. No wonder, Why the impressions were so high but CTR was so low, as we seen earlier in this post. The culprit is found :)
For the Dynamic search Ads, the CPC is $0.40 and RPC is $0.50. Are we making any money from this campaign? The total cost of this campaign is $407 and revenue generated is $502 but don’t forget that the cost of goods sold isn't added to the cost yet. I don’t think we are making any profit from this campaign.
We can’t measure the (not-set) in campaigns because GA didn’t receive any information about 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 bad?
The match type selected for this campaign’s keywords are Broad match to show the Ads to a wider audience. If you click on the Electronics campaign and then the Sunglasses brand ad group, you will see the keywords report.
Now, look at the above picture. Actually GMS bids on keyword “Women Sunglasses” but due to broad match, the keywords are matching with lots of different search queries.
Search queries - are the actual queries people type on the search engine.
Almost 8 out of 10 search queries are totally different from the keyword they bid on. Broad match helped them to target wider audiences but customers intent wasn’t matching with their keyword.
They have nothing to do with “Jimmy Choo” or “polaryte hd sunglasses men and women the dealer” OMG “dealer” :)
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 the above-desired result.
4. Keyword Optimization -
We gonna apply the same technique that we used before to find out which keywords are bouncing at a higher rate compared to the site Average.


It turns out for the top 20 keywords, the keywords related to google store, YouTube merchandise, google products and google backpacks are bouncing at a higher rate.
To optimize the keywords, we are going to use the custom report -PPC keyword/matched query report.
As we saw earlier that the keywords we bid on and the actual search queries can be very different from each other which can lead to higher bounce rate and lower conversions.
Let’s see if this is the case.
The match type used for "google store" is an exact match and if you click again you can see the actual query.
As it turns out there isn’t any difference, just the order of the words.
So what we do now?
Let’s dig a little deeper to see if the users are landing on the right page or not?
Hmm, it is also not the case. The visitors are landing on the right page, the google store homepage.
Now What?
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 are having some difficulties using the website in mobile and tablet compared to desktop. They are not converting at all in this case.
Let see the next keyword - youtube merchandise
Same story here. But if you look at the below pic, you can see that people are landing on a wrong page.
Rather than sending the traffic to the youtube product page, GMS is sending the traffic to the homepage.
By looking at some keywords, We find out that people are landing on a wrong page and people are also having trouble using the website on mobile devices.
To know for sure that people are really finding difficult to use the website on mobile and tablet, let’s use Advanced Segmentation. One of the most important features in Google analytics.
In fact, visitors are bouncing at a higher rate on mobile and tablet compared to desktop. E-commerce conversion rate and per session value is also low for mobile and tablet traffic.
And if we look at the keyword report segmented by device type, lots of keywords has zero or less conversion and per session value compared to desktop.
There might be one reason, why aren’t customers are converting on mobile and tablet is that lots of people like to research on mobile and later convert on the desktop. There are lots of other ways to understand what is the real cause but we have a lot to cover in this post so let’s assume that people are having troubles using the website on mobile devices or we need to further investigate to know the true reason.
One way you can try is to look at the Shopping behavior report in the conversion tab along with device type segment applied to understand more about customers behavior. One another great technique is to use customer survey to gain more insight. Who is better than our customers to tell us what really sucks.
What if we have a large volume of keywords?
It really becomes a huge challenge to analyze when we have a very large volume of keywords, pages etc. What happens most of the time we only look at top 10 or 20 rows of data and move on with our life. But top 10 or 20 of most of the thing rarely changes. The real opportunities lie when we move beyond top 20.
So let’s understand how to actually do it.
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 we have a list of keywords that match our criteria. Sadly, in this case, We have only 5 keywords that match our criteria. I wish there is more.
But Now we know, how much powerful this feature can be to cut through a huge amount of data and only gives you the data which you are most interested in. You can apply more conditions, whatever make sense to you by adding more dimensions or metrics depending upon what are you trying to accomplish.
B. Term cloud -
First Go to Acquisition > Adwords > Keywords
Do you want to see which keywords are generating more revenue?
Here it is. One thing to remember When using term cloud. It will only show you the total rows of data that is 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 actually added products to the cart and started the checkout process.
Now we have the answer.
OK, Now check out the visitors from which keywords actually 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? Where are these people coming from? What can we do so that this doesn’t happen again? Real analysis with amazing insights.
C. Weighted sort -
What is weighted sort?
Weighted sort applies an algorithm to your data to bring the highest and most statistically significant metrics rise up to the top.
To use weighted sort, click the bounce rate( or other percentage based metrics) column header in a 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 GA algorithm think you should focus on. If you improve the bounce rate of these keywords you will get the most value out of your investment.
Wait there is more.
Now reverse sort the table.
Boom! Now you have a list of keywords which already have lower bounce rate and if you focus on these keywords and improve their performance, you can extract as much value as possible.
No more beating our head to understand what to focus or not to focus in the ocean of keywords. Google analytics do this heavy lifting for us.
Isn’t that great?
One Bonus tip - you can apply weighted sort on almost any report in Google Analytics like traffic source/medium, landing pages, internal site search report etc.
Want more magics? 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 groups as well as campaign 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 Treemaps, we can now understand that Merchandise brand [E] has more users and lower bounce rate compared to other high traffic ad groups like Merchandise-brand [BMM] and Store-brand[E]. And if we look at the right bottom of the pic, we can see that some of the Ad groups like Swag-brand[BMM] and Gear-brand[BMM] though has low traffic but has even lower bounce rate than other ad groups.
Now let’s compare an Acquisition metric to an outcome metric to understand the complete performance of these Ad groups.
In the previous analysis, 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 it has a very good avg. order value. If we reduce the bounce rate of this ad group, we can make more money and can further increase Avg. order value of 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 able to see the complete performance of our ad groups.
As I said before always use ABO framework in your analysis to get the full picture.
Do you want to know which keywords are performing better in a particular Ad group?
Ok Google, show us :)
Boom! Now, just by looking at the treemap, we know what is good and what is bad. Isn’t analytics so cool?
You can do the same for campaigns also.
You might be thinking, if we can directly use the treemap to find out the performance of our campaigns, ad groups and keywords then why the hell I explain all the other techniques?
The answer is, treemap only tells you what is good and bad but it didn’t tell you why? Also, the treemap isn’t available in lots of the reports, even it is not included in all the amazing reports inside Adwords sections which we will see later and also it is limited, Treemap will only display up to 16 rectangles at a time. You need all other techniques to do deeper analysis and find out the answers you are looking for.
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 Adwords section exactly help you to 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 again during 2 and 3 pm, at 5 pm in the evening and 7 and 8 pm in the night.
And from the day of week report, it’s clear that most customers are buying on Wednesday, Friday, and Saturday.
So why to waste most of your money when the visitors to your website aren’t most likely to convert. Use these two reports to do the smart bidding and save lots of money, You will be glad that you did it. But don’t forget to check these reports periodically and make changes accordingly.
7. Pan-Session analysis ( multiple visits by the same person) -
a. How much time did it take someone to make a purchase after their first interaction?
First, go to the Conversions > Multi-channel funnels > Time Lag
Click on conversion tab at the top and uncheck all the goals and apply. Click on Adwords type from All.
In the GMS case, 65% of the customers purchase on the same day after their first interaction and equals to 53% of the total revenue.
But 35% of the customers complete their purchase after 1 day after their first interaction and equals to 47% of the total revenue.
And If you look at the bottom, 19% of the customers take more than 12-30 days to finally make a purchase OMG! , you can also see that as the number of days starts to pass after 8 days, the revenue also starts to increase more. At the bottom, 19% of the customers are responsible for 39% of the total revenue.
B. How loyal are your customers?
To find it out, Go to Audience > Behavior > Frequency and recency > Count of sessions
Frequency or Count of sessions tells you how often the users visit your website during a particular time, in this case, June.
The Avg. sessions per user are 1.24 but when you look at the distribution below, you can see that this is not the case. There are lots of users who not only visited more than 2 times but even 9 - 201+ times. You can see that Averages can lie.
73% of the users(51,176) came to the site only once and never again. How pathetic is that? If 73% of the user never coming back to your site then how the hell do you gonna sell and achieve your dreams of becoming the market leader?
Only 27% of the users came more than 1 times. So lame. Few people came to the site more than 8 or 9 times during June. These people are your loyal customers. Your goal here is to have the larger number of users at the bottom of the distribution, the higher the number, more awesomeness, and money for you.
C. How engaged are your customers with your website?
Look at the Engagement report just below the frequency & recency report in the behavior section.

The Avg. session duration is 2 minute and 40 seconds during June but the distribution of session duration( the length of a session in seconds) again tells a different story.
48% of the user(31,841) only stayed for just 1-10 seconds, only 10 seconds, feels like it’s time for some meditation :) You want your customers to stay at least more than 3 minutes, the higher the number, more good for your company. One good thing here is at least 20% of the users stayed more than 3 minutes. But still lame, we want more.
Always be cautious when you use Averages or percentage, they can mislead you.
Through our Pan-session analysis, we see that most of the GMS customers aren’t that much loyal and engaged with the site. If your report looks like this then you are not losing money, you are bleeding money. Go and figure out what are you going to do to engage your customers more? How do you make your customers visit your website multiple times within a month? What changes are you going to make in your campaigns or on your website to get the desired results?
There are a couple of more reports in the behavior section and multi-channel funnel section, make sure to check them out also. And don’t forget to apply relevant segments to your report to better understand the user's behavior.
8. Multi-Channel Funnels for Adwords -
In Google analytics, conversions and e-commerce transactions are credited to the last campaign, search or ads that referred the user when he or she converted.
But in reality, customers research, compare and make purchase decisions via multiple touch points across multiple channels.
By default, Google Analytics will attribute all of the credit or e-commerce revenue to the last marketing activity. This is called a Last-Click attribution model. Which is not fair.
So the question is- Which channel you give the most credit and how much?
In the above report, you can see that direct traffic is closing most of the sales and conversions but referral and organic also contributing to close the sale by introducing customers to your brand.
Multi-channel funnels help us to understand it and better allocate and invest our marketing time and budget wisely.
Assisted conversion and assisted conversion value - tells you the number of assisted conversions and their monetary value of sales and conversions the channel assisted. The higher these number, the more important the assist role of the channel.
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 of sales and conversions the channel closed or completed. The higher these numbers, the more important the channel’s role in closing sales and conversions.
Assisted/Last Click or Direct conversion - is a ratio which summarizes a channel’s overall role.
A value close to 0, indicates that the channel completed more sales and conversions than it assisted.
A value close to 1, indicates that the channel equally assisted and completed sales and conversions.
A value greater than 1, indicates that the channel has a bigger role in assisted sales and conversions.
In the above picture, look at the last column. We can see that the value of Display is 5.50, which is highest among all channels. Which means that Display help to assist most conversions than any other channels. Second highest is the Social network.
The value of paid search is 0.59 which indicates that it mostly helps in closing more sales than assist.
And if you only focus on the default Last click attribution model then you are not giving enough credit to Display, social media, organic search and referral in this case for introducing your brand to new people, working hard in early stage of conversion process, helping in closing the sales prior to the final direct conversion.
Let’s understand the multi-channel funnel for our Adwords Ads.
Remember, In our analysis, we made an assumption about aw- dynamic search ads campaign, though it was generating revenue but we are worried that we might be losing money because the difference between the cost and the revenue was very low. But now if we look at the assisted conversion report, we can see that this campaign also assisted 10 conversions and added additional $414.09 in assisted value to the merchandise store. If we only considered the default last click attribution model, we would have been made an error in our analysis.
We can also see which Ad groups and keywords are driving more assisted conversions. We can see that All webpages 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 equally helping in assisted and final conversions.
Though Merchandise Brand[E] has a value of 0.41 means helping mostly in final conversions but it has also the highest assisted conversions and conversion values than other ad groups.
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 Last interaction.
Now look at the last column % change in conversions, as we can see Aw- Dynamic search ads have a positive 37% shift from the reference model in this case Last interaction. Again we see that Dynamic search ads are performing better than we would otherwise have credit them previously.
When the results are significant a green and red arrows shown and where it is directional, up or down gray arrows shown.
Also look at the CPA column and compare between two model. We can see that the CPA for Dynamic search ads is not $50, it is actually $37 dollar.
How cool is that?
Upload the cost data of your all marketing channels to measure each channel effectively.
Use Assisted conversion and model Comparison tool to better allocate your marketing budget/efforts across different marketing channels, Adwords campaigns etc.
I hope this post is helpful to you and will help you quickly optimize your Adwords campaigns more effectively.
Happy analytics!
P.S. Before you leave please provide your valuable thoughts with all of us.
Is this post helpful to you and would you recommend this post to others? What do you like most about this post and why? What are some major issues you face while optimizing your Adwords campaigns? Please share your thoughts positive or negative with all of us.
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  1. Love your Analytics posts! Goes into so much detail -- and you cover topics that usually are not explained well enough on the web.

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    1. Thanks Zakaria for giving us some of your valuable time to read the post. We are really happy that you find it helpful. Hope you have an amazing day ahead.

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