Google Analytics is the standard analysis tool of the de facto industry.
It is installed on almost all business sites. (He is even looked at, sometimes, too.)
It provides a huge amount of data that you can manipulate, as well as customization options for the advanced features that users need.
Also, it is free.
Google Analytics excels at providing aggregated data at the surface level, at the top of the funnel.
Here is an example of what is practical, with some problems that it presents.
Where Google Analytics excels
This form of super-duper-in-depth quote request works great on your desktop. But what about mobile and tablet users?
It's a mobile world, and we live there. Not only more searches are performed on the mobile than on the desktop, but the use of mobile in general (and growth) continues to eclipse the use of the office .
Today, the top sites are mobile first from the ground up, overcoming inherited problems like weak UX, AI, and speed that hinders conversions.
Like, for example, long-bodied forms.
With only a few keystrokes in Google Analytics, your answer is waiting for you.
to reinvest in this old thing and breathe new life so that we can better capitalize on all these research visits that arrive.
They can probably use new statistics and data as the world has evolved in recent years. Today 's blog posts also tend to be more visual and progressive tactics, so let' s flesh out some of these top – level sections as well.
With the help of some basic Google Analytics reports you can quickly detect top-level trends like these and get decent reporting statistics on how your daily tactical activities (like blogs, tweeting, advertisements, etc.) affect new leads or new purchases.
If you are a scrappy, you can even perform advanced tactics such as split tests directly in Google Analytics .
For all good, there is harm.
There are some problem areas and obvious shortcomings where Google Analytics drops the ball. And you will probably need other software or tools to increase it in order to have an overall view.
(After all – Google Analytics is free, we can only complain.)
Here's where Google Analytics is struggling (and how to work around these issues).
Where Google Analytics Fails
The analyzes for cheap products are surprisingly simple.
Extreme volume can always be a problem. But otherwise, it's a direct shot from A -> B. Point, click and buy.
Google Analytics will show you the product business number online with conversions, and you do not always have to think too much about what you are looking at.
Consumers also do not overload the process, ranging from Stranger to Customer at one go (or sitting).
Unfortunately, we can not say the same for other organizations.
If you have a complex sales cycle or a multi-step conversion process (like most SaaS applications) that go from Visits -> Free Trial -> Pay, you will need to connect the points.
And with Google Analytics, this sometimes gives the impression of reading tea leaves rather than making decisions based on data.
1. Attribution problems and contact bias
Want quick statistics on performance at a glance to draw conclusions on the surface? Open GA.
However, when it comes to tracking the performance of specific campaigns (and comparing them to others) or seeing how prospects become prospects, sales opportunities, customers and prospects loyal promoters … this is starting to become cumbersome.
Google Analytics is session-based, primarily looking at individual visits. It means that he can tell you what's going on (more or less) during a visit. But if this visitor takes off, and returns next week, there is (above all) no way to find out.
This creates a whole series of attribution problems that can skew your marketing decisions.
For example, say you sell insurance. Here is what this typical flow looks like:
Prospect gets a new high-paying job, just celebrated his first birthday and has a baby on the way. Now, they realize that they should probably have life insurance!
Thus, the prospect begins to do general "unbranded" searches to determine what kind of coverage he may need and how much it will cost.
After becoming a bit more informed, they begin to do specific research around individual products and vague terms (like "riders").
They read a few articles on a few different websites, and start looking for companies or brokers to reach (by typing in key business phrases like, "life insurance quotes").
They click on a few websites, and eventually opt-in to one or two to begin the sales process.
Ok, let's stop for a minute.
There is still a lot to do. The majority of these prospects will never become a customer, but there are already some obvious problems.
Issue # 1. In Google Analytics, you can only see step 5. Nothing before that.
Issue # 2. You take a look at the conversion sources, and you only see the commercial-key-phrase research done at Step 4.
Confirmation bias. No duh – the highly commercial key phrases are going to convert well.
You can bid directly on these, but have you seen any CPC "life insurance" ranges lately ?!
And what is happening is that your company neglects or ignores all the other steps (especially, 1-3) that lead to this point, as well as the marketing requirements that it takes to provide these things – as the operation of your social media increases reputation and credibility, how to SEO for unbranded topics to increase brand awareness, how design and UX affect the first impression, which paths conversion are the most effective, and more.
Because you can not see all that! At least not in Google Analytics alone.
This is where you need to overlay in other tools to assign each user an individual ID and compile all their visits (which sometimes occur over days or weeks) leading to an opt-in or a purchase.
correctly labeled you can follow this work.
Another hack or workaround is the segmentation of Oli's incoming traffic where you create dedicated pages for each source or channel – even if they are the same information – for purposes measurement.
But … an AdWords campaign does not have = a larger promotional or advertising campaign.
A company-wide revenue-generating campaign involves several touch points and channels. Unlike offline mode, these channels help each other online (as we saw in the first step).
And our bosses (or customers) want to see how Campaign A compares to Campaign B in all marketing initiatives (not the granular and advanced CPC indicators of one term versus another).
Fortunately, the recent updates of the new report on new funnels can hugely help to find all the touch points that have contributed to the success of your campaign.
First, you want to create events that collect all your tracking codes and all your landing pages with this specific campaign variable.
increase conversion rates by 80% . But the important part is what happens after people watch a video.
For example, after watching a video :
64% of viewers are more likely to buy the product
50% of executives look for more information
39% of executives call a seller
Want to increase your sales? Turn more leads into customers? Convert more trialeurs into buyers?
Bring people to watch this damn video.
GA can display general video views in the form of a global engagement metric.
But this information is useless if you can not decipher the status of these visitors or if your prospects see it or not
Solve this by creating a funnel report and identifying those who did not realize the specific event you were looking for:
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