How Google Analytics Can Be Misleading...

I love Google Analytics, but their reports can be misleading if you don’t understand the critical concept in the article below.

In today's Check This Out, I’d love to get your input...

 

 

Why Google Analytics Reports Do Not

Match AdWords Reports

 

Out of many popular topics like Facebook advertising, email marketing, mobile website development, and a handful of others, would you believe me if I said more people want help with Google Analytics setup and reporting?  Well, it’s true.  My assumption going into the survey was that bland and boring Google Analtyics would be sitting on the rock bottom.  But it’s right at the top!
 

So with that in mind, I’ve decided to write about a topic that I’ve held back for fear that no one would find it interesting.  However, it’s a very important concept to keep in mind when you’re reviewing your Google Analytics reports.  It’ll also explain why your Google Analytics reports are often very different than your Google AdWords reports (if you’re advertising).
 
It’s call attribution.
 

What is Attribution?

Online attribution is the process of assigning credit for a website conversion, or Goal in Google Analytics. Think of it like giving credit to a salesman for closing a new client.  In that case you’re attributing the sale to one particular salesman.  The same thing happens online when a Goal is completed in Google Analytics.  The program must attribute the sale to the correct source of traffic (i.e. SEO, AdWords, Facebook referral, etc.).
 
This sounds simple until you think about the typical person surfing around online.
 
Let’s say I do a search in Google and click on one of your ads, which brings me to your website.  I read all about your amazing widget and how I would be insane if I didn’t purchase right now.  Then I leave your website. :)
 
I do a little more research into your company, I read some reviews, and find an online press release or two.  Finally, I search in Google again, but this time I use your company name, and I click on the non-paid result (the organic SEO result).  I’m already sold so I quickly make a purchase.
 
In that example, how do you think Google Analytics will handle attribution?  Does the AdWords ad get credit for the sale?  That’s how I originally found your site so that seems like a logical answer.  Or does the non-paid, organic result get credit because that’s the last action I took before purchasing?  Or do both get credit?
 
Take a guess if you’re not sure before reading on.  Don’t cheat. :)
 

How Google Analytics Handles Attribution

By default, Google Analytics uses what’s called “last click” attribution.  That means in my example, the conversion will show up as coming from the non-paid, organic search.  So it’ll look like revenue from SEO, not from the AdWords ad that originally brought me to the site!
 
Ah ha! See why I said this was a critical topic.  All this time you may have been misinterpreting your reports in Google Analytics.  Just because you’re getting all of your leads and/or sales from organic traffic, doesn’t mean your advertising is not performing.  It could be simply a case of mistaken attribution.
 
To make this even more complicated, I need to warn you that Google AdWords reporting uses “first click” attribution. That means in my example, when you run the report in Google AdWords, the sale would be attributed to the keyword and ad that was first clicked on.  So you’ll see the sale in AdWords and you’ll see the same sale in Analytics, but Analytics will be telling you the sale was generated from SEO!
uh oh… which program, Adwords or Analytics, should you trust?
 

Which Attribution Model Is Best For Your Business?

The short answer to my question above is that it depends on your business.  If most of your leads and sales are generated quickly upon the first visit, then “last click” attribution is most likely fine for you.  If you have a longer sales cycle and you know people shop around before making a purchase or contacting you, then first click might be best.  The good news is that earlier this year Google Analytics gave us the ability to report on conversions, or Goals, using 7 different attribution models.  They even let you create custom models if you really want to go nuts.  For the record, I do not recommend going nuts… Stick with the basic models.
 
To see this in action, log into your Google Analytics account and go to Conversions in the left navigation.  Then click on Attribution and then Model Comparison Tool.  You’ll see a report like the one below where you can compare different models.
 

 
I also recommend you review the Multi-Channel Funnels while you’re in the Conversions section of Google Analytics.  The most interesting reports are:

• “Time Lag” to see how many days it takes for prospects to convert.  This is where you can see if the majority of your conversions happen on the first day, or if it usually takes longer.
• “Top Conversion Paths” to see the full path to conversions.  In my previous example, this report would show “Paid Search” led to the “Organic Search” which then generated the sale.  So rather than rely on one single attribution model, you can see the entire sales path.

OK, that’s probably more than enough Google Analytics reporting info for one day.  The key takeaway is to always be aware of how Google Analytics (or any other tool you use) is attributing conversions in your reports.  And if you’re receiving reports from a marketing company, then make sure it’s clear how their tool is handling attribution.  Different attribution models can show vastly different results, which can lead to vastly different decisions about where to focus your marketing budget.

How To Conduct Ad Tests In Enhanced Campaigns

Enhanced campaigns have brought about many changes to AdWords. One of the biggest changes yet to be discussed is the fact that your ad testing methods will have to change.
One of the “features” of enhanced campaigns is that your campaign can now run on desktops and mobile devices with different CPCs that are controlled by bid modifiers. However, since your ads can be run on multiple devices at the same time, you need to test your ad metrics by device.
This can easily be accomplished with device preference and Excel filters. First, let’s discuss why this change needs to occur, and then, how to control the ad serving to ensure you are testing your enhanced campaign ads properly.

Why The Testing Change?

Let’s say we’re testing two ads and that we’re running both ads on all devices (desktops/tablets and mobile devices). What happens is that after a while, we check our metrics and we see data that looks like this:

If you simply used this data as-is, you would assume that Ad 1 is the best ad overall and go with that ad.
However, averages hide all the useful data. You need to segment your data to truly understand what is happening. If you were to segment these two ads by device type, the data looks much different:

In reality, Ad 1 is not the best ad — it is the best ad on mobile devices. The best ad on desktop devices is Ad 2.
Therefore, you’d now want to control which ad shows on which device, and this can be accomplished with device preferences.

Device Preferences

When  you create a text ad, you can specify the device preference:

If a campaign is set to show on all devices, and you have not set a preference by ad, your ads will be shown on all devices.
If a campaign is set to show on all devices, and all your ad preferences are set to mobile, your ads will be shown on all devices.
To control the ad serving by device, you need both a mobile preferred ad and a non-mobile preferred ad in each ad group. To test ads by devices, then you need at least two mobile preferred ads and two non-mobile preferred ads in each ad group.

Image Ad Preferences

In “legacy” campaigns, most sophisticated accounts would segment their display advertising from their search ads, and their mobile display campaigns from their desktop display campaigns. Because these campaigns were already segmented by device, most marketers would just upload “mobile” ads to their mobile campaigns and desktop sizes to their desktop campaigns based upon Google’s sizes:

However, several of the sizes that are not traditionally considered mobile ad sizes can be shown on mobile devices:

Therefore, you will also want to specify the mobile preference of an image ad so that you can test your image ads by devices as well as your text ads.

An Easy Way to Determine Ad Types by Device

In the AdWords interface, it is not easy to see if you have a mobile and non-mobile preferred ad in each ad group. The easiest way to see this data is to use a pivot table and conditional formatting.
In this case, a simple pivot table was used to show the number of ads by device preference in each ad group; and then, conditional formatting was applied to highlight any cell that was less than 1.

If you wanted to make sure you were testing in each ad group, you could also highlight all cells with less than 2 ads using conditional formatting. This would allow you to see which ad groups need ads created so that you can test them.

Run Your Statistical Confidence Numbers As Normal

Once you have the ads set up and running by device, you can do your statistical confidence calculations and pick your winner — just make sure to segment the information by device.
Only use your mobile information to test your mobile ads and pick winners.
Only use your desktop information to test your desktop ads and pick winners.
Once the data is segmented by device, the way you run your numbers and pick winners will not change with enhanced campaigns.

A “Cheater’s” Way Of Testing

Creating thousands of new ads can be a daunting task — so, there is a shortcut you can use. However, please note that, as with any shortcut, there are some underlying weaknesses.
Instead of creating ads for every device type, if your landing pages have the same content (such as with responsive design) and if overall conversion actions by device are the same, then you can start with just ads on “all” devices. You can then segment the data by device type and run your statistical confidence by device.
Once you have a winning ad by device, then you can change the ad’s preference type of mobile if it’s a mobile winner and leave the desktop winners as all devices.
There are a few inherent weaknesses to this approach:

• You cannot customize the call to action by device
• When you “edit” your winning mobile ad, it must go back under review and the stats are “reset” for the ad

This isn’t an ideal long term solution; but, if you are trying to transition many campaigns and thousands of ads to mobile devices, it can be a way to start ad testing.
However, with a “good” transition, you will keep your mobile ads in your enhanced campaign by moving the mobile ads to your desktop campaigns (or vice versa) and using ad preference to keep them segmented.

Wrap-Up

Enhanced campaigns are a major change to managing AdWords. However, they do not change the underlying principles of ad testing. You must test ads — and a good ad test will not only examine the differences in multiple ads, it will also take into account segmented data such as the device where the ad was displayed.
By ensuring you are controlling your ads displayed by device type, you can be confident in your ad tests and ensure that you are keeping the best ad for your account.
Even with device segmentation, many of the previous columns on ad testing are still true – they just require a previous step – device ad control. You can still easily manage and test millions of ads and use cross ad group testing principles.

How To Determine Your Hourly Bid Multipliers In AdWords

While hourly bid multipliers aren’t new, they remain a crucial tactic for optimizing your AdWords campaigns. They work by reducing your ad spend at poor-performing times of the week and increasing your exposure at the best times of the week. Here, I’m going to share the steps you can take (along with a helpful spreadsheet) to determine your hourly bid multipliers for better campaign optimization.

Step 1: Pulling An Hourly Performance Report From AdWords

On the Campaigns tab in AdWords, go to Columns>Customize Columns and ensure that you’ve selected the appropriate metrics. Performance metrics required for the spreadsheet to function properly are as follows: Campaign, Clicks, Impressions, Cost, Avg Pos, and Conv (1-per-click) — all other metrics selected in the screenshot below are optional:

Once your performance metrics have been selected, hit the “Download Report” button. When prompted, add the “Day of the week” and “Hour of day” segments:

This should provide you with all the data you need to analyze hourly performance at the campaign level.

Step 2: Determining Hourly Bid Multipliers

Similar to the template used to determine mobile and geo bid multipliers, I’ve created a basic spreadsheet to help analyze hourly performance and easily determine your hourly bid multipliers. You can download it here.
Copy and paste your AdWords report into this spreadsheet as directed. From here, you can take a closer look at the following:
a. Performance By Day Of Week

b. Performance By Hour

c. Performance By Hour & Day Of Week

If you have collected enough hourly data for each day of the week, you should absolutely make bid adjustments on an hourly basis. This process can be time consuming, as it requires making adjustments on a very granular level, but the results are well worth it.
For those times with less traffic, you can still leverage daily and/or hourly trends. For instance, looking at campaign #43 in the attached spreadsheet, it appears that there was not enough data collected on Sundays from 4:00 am to 5:00 am to make a specific bid multiplier suggestion — but you might still want to increase the bids, since the data indicate that both Sundays and the 4:00 am to 5:00 am window perform well in general.
The attached spreadsheet will only address those times of the week with sufficient hourly data, while keeping in mind that “bid adjustments for locations, days, times, and any ad group-level targeting methods can be set from -90% to +900%.” Thus, it can help you to determine relevant hourly bid multipliers between -90% and +900% when there are a statistically significant number of clicks:

Step 3: Implement Hourly Bid Multipliers In AdWords

At the campaign level, navigate to the “Settings” tab; then, go to the “Ad schedule” section. The first step is to specify when you want to make bid changes. Select a day of the week from the drop-down menu:

From there, you can you can adjust the effective hourly bid multipliers, as calculated by the spreadsheet:

Conclusion

All of this is fairly straight-forward; however, your hourly bid multipliers need to be maintained over time, hence the importance of a (semi-)automated process. Also, keep in mind that once set in AdWords, those hourly bid changes do not take into account multiple time zones. For instance, if your AdWords account is set to “(GMT-08:00) Pacific Time,” and you want to increase the bids by 20% at 1 pm, then these bid changes will occur at 1 pm PST across all PST/MST/CST/EST locations. As a result, it makes sense to break down your top campaigns by time zone in order to set more accurate hourly bids.