For your next campaign: Use a simple tool to determine the influence of each channel
Unfortunately, the data provided by Google Analytics is not as spectacular or conclusive as that provided by other tools. Here are some screenshots, just so you know this isn’t a (very) biased opinion 🙂 …
Consistent data? Advanced optimizations?
Even more likely is you’re still in shock from so many “Not Available” messages. Why do we need to know about conversions per route? Is this information really useful?
We must be very careful to avoid one of the great dangers of being over-informed: paralysis. This means if we get bogged down by information overload in the form of numbers, the reaction can be inaction, or paralysis. This is what we need to avoid. Some call this infoxication or information overload.
Fortunately, technology and tools are available for us to interpret data more clearly, allowing us to make decisions and take action in order to achieve our objectives.
But, even if you choose to keep working with Google Analytics, you can still get useful information. For example:
How much influence does Affiliate Marketing have over PPC campaigns?
Let’s create a “Segment determined by the user”, such as this one:
How much does the SEM influence the SEO?
The result would be:
In other words, more than half of the SEO sales have been aided by SEM traffic, and so on throughout each successive channel…
Wouldn’t it be better and simpler for everyone if information could seen in this way?
Where:
a) 63 out of 200 affiliate sales have been obtained due particularly to Adwords Search.
b) 19 out of 351 Bing sales come from Adwords.
c) …
Google Analytics does not provide all data. And, when there is data provided, it requires very advanced knowledge in programming in order to modify its Javascript. One such piece of data is:
Number of clicks per interaction: We’ve just seen the number of conversions per
interaction. But, how can we see the number of clicks per interaction?
A tool such as Adinton can easily give us:
See how the percentages only drop considerably after the seventh click. At least, this is how the commercial version of Google Adwords is sold. In other words, those of you who have spoken with Google Adwords salespeople know that when they present their Search remarketing option, their sales message is that more clicks means more chances of completing the sale, since clicks mean the user is interested in our product, bringing us closer to the sale.
This table shows us the number of clicks, conversions and % of conversions, according to the order of clicks. In other words, we have 1366 conversions that were the result of 22,323 clicks, and each conversion was the result of 3 clicks.
Here are some other interpretations of the same data. Out of a total of 1,156,000 clicks, 991,000 clicks were the first click, 30,111 of them resulting in conversion, 82,904 kept on clicking. The other 878,000 did not return. You might be thinking where we really judge the success of our online marketing campaigns is on the first click, CRO pure and simple, and not on attribution models. I can only say, I agree with you! So for that, let me show you again the image from the beginning of this paper:
More than 50% of conversions result from the 1st click or the first interaction.
But, since this document is about attribution models, we will continue to optimize them.
Download our Attribution Model white paper. It’s set out in clear language, with answers based on experience and specific examples of the following topics:
1. A clear definition of Attribution Models and the Customer Journey.
2. A chart with the pros and cons of every attribution models.
3. A case study showing how to find out at a glance if attribution models are needed.
4. Optimization actions based on analyses of the attribution model.
5. Use a very simple tool in order to understand the influence between channels.
6. Duplicate conversions do not mean duplicate sales.
