I am not a big numbers guy.
I almost (and should probably have) flunked out of math in my junior year of high school.
I didn’t quite make it to calculus, I met my match at not-completely-basic-but-still-entry-level algebra.
And yet, as a digital marketer, not only do I work with numbers, I rely on them to save my ass every single day.
When I am trying to improve the performance of a campaign, to stretch ad dollars longer, numbers are my greatest ally.
One look at the data completely removes the guesswork from what would otherwise be brain-fumbling, time-consuming challenges.
What area should we test the new local-level campaigns in?
The data has the answer. (Whether you want to ramp up what’s already working, or try to make up for the slack where it’s not.)
Sure, you like ad X better, but which one actually sold more & should be pushed to the nation-wide campaign?
The data has the answer.
What colors should the new T-shirt designs be printed in?
The data has the answer.
There have been times when just me, one guy, looking at the data has lead to campaign performance improvements of 2–300%.
Without data, reaching the same level of performance always takes way longer and costs a lot more.. if it even happens at all.
Even with a talented team of marketing professionals. (Although if they are truly talented, they will insist on tracking results.)
Even if you haven’t started advertising online yet, you start out tracking & testing, you can catch yourself before you make mistakes to the tune of $1000s of dollars & weeks, months or even years down the drain, following a campaign that you thought was working that actually didn’t.
You will be able to course-correct in real time, based on real feedback from actual users, and get where you want to be much faster & much cheaper.
And the best thing is, one of the most powerful analytics tools on the planet is 100% free. (Except for that pesky data, of course.)
Crash Course on Google Analytics
The following tutorials and how to’s will show you how important parts of Google analytics works, or how to set up crucial elements of Google analytics.
(If you want a guide on how to use a Google alternative, leave a comment. If I get a few I will write one up.)
- How To Install The Google Analytics Code On Your Website. (Alternative for WordPress / Alternative for Shopify )
- How To Set Up A Goal/Conversion Point
- UTM Parameters: What They Are & How To Use Them
- How To Sync Google Ads with GA (Important Note: If you connect your Google Ads account with your GA account, you don’t need to set up parameters for Google ads campaigns.)
- (If you are computer-savvy; most of this is summed up quicker in the Getting Started With Google Analytics video)
Short Checklist To Make Sure That You Get The Most Data For Your Dollar:
- Make sure to set up conversion tracking (that works) before spending a single dollar on ads.
- You correctly set up UTM Parameters To Accurately Track Sources Of Traffic & Their Quality / Results. Make sure you change the UTM_Campaign & UTM_content for each campaign and ad. (Unnecessary for Google Ads campaigns if you linked your Google ads account with GA.)
- Don’t just mindlessly run ads, test hypothesis and theories you have about your product and business. (Sell a product to men, but think it might catch on with women in a certain area? Test it. Think that most of your sales come from a certain platform? Test it. Feel like a certain state might be a good match for your product? Test it.)
How To Make Sense Of The Data — 3 Simple Views That Will Become Your Best Friends
Now that you have started gathering up this data, how can you make sense of it?
How can you let it guide you to make better marketing decisions in the future?
You should start off by using the following 3 views.
Acquisition With Campaign & Ad Content Dimensions.
Head over to acquisition > All traffic > Channels, and select Campaign as the Primary Dimension, Then (Optional) Select Ad Content as The Second dimension.
That gives you the following breakdown.
The biggest things you should pay attention to, are the Goal Conversion rate & overall goal completions.
Other than that, Bounce rate, Avg. session Duration & Pages / Session can be decent indicators of traffic quality (aka an ad that probably works) before you actually start landing sales.
The best thing is, to get the same insights about landing pages, all you need to do is to change the primary dimension to landing pages, and voila.
(If you use Google Ads, you should rely on the Google ads, campaign breakdown for similar results but which includes the stats for ad spend & ROAS as well.)
Wondering Where People Are Leaving Your Site? Behavior Flow
If you are wondering where people are leaving your site after coming in through various campaigns, you can go to behavior > behavior flow.
There you can see the most common paths of your visitors, including which pages they leave from most often.
If you have one page with a very high exit rate, consider implementing an exit survey, or simply improving on the page’s desing/UX to lower it.
Wondering If A Campaign Is Worth It? Compare Attribution Models.
If you are not exactly sure if a campaign is worth it or not, you should check the numbers with a different attribution model.
By default, Google Analytics credits conversions based on the “last click” before the conversion.. even if the user originally clicked an ad, and then searched Google to come back and purchase a few days later.
I like to compare last interaction with first interaction & last non-direct click.
For funnels that take longer (bigger purchases) you will often see a huge up-tick in conversions for first interactions.
When You Can’t Use Standard AnalyticsーGo Old School.
In some cases you might not have the access to be able to track conversions all the way to the end using GA.
For example, if you don’t handle the orders yourself (like with Amazon FBA) you might not be able to install the Google Analytics code and conversion actions.
In that case, if you decide to try a new advertising platforming, you need to go old school:
- Test A Product That Gets Stable Sales And Measure Difference Before/After
- Region/City Based Testing (For example, Facebook Ads in one state, Google Ads in another, check the orders that come in from each area to Gauge ROAS.)
Going old school is still a lot better than just blindly starting a large-scale campaign and hoping for the best.
Start small, test, review the data, and then scale once you hit profitably ROAS.
Still Confused? Want More?
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