You need to see what grows the business
Tools that help you assign credit are not built to help you to do this
You can boost the marketer’s ego or the business’s bank account!
What is MTA & Who Does it Help
MTA, or multitouch attribution,
is designed to solve the problem of how we reach the customer in multiple ways,
who deserves credit.
This is been an issue facing digital marketers for over 20 years.
There have been countless potential solutions that have hit the market,
including such things as Northbeam & Hyros or Wicked Reports & Triple Whale.
The majority of these MTA solutions promise to deliver an accurate read on what the customer journey looks like.
With that, you can begin to optimize that customer journey to make more money & scale your business.
These MTA solutions are built on the idea of who gets credit for what ultimately shares a common ideal customer use case, Add agencies or brands with multiple internal marketing teams.
This is also one of the reasons that they are tremendously flawed…
they deliver on the promise of the product when they are able to allow individual marketing efforts to take specific credit for a percentage of revenue.
However, if the point of looking at this information is to grow your business, the vast majority of these tools do not meet your needs, because they are not designed the solve your questions.
What is wrong with Multi-Touch Attribution?
The fundamental flaw of MTA, is that it is at best a retroactive report on the average customer's journey through the average marketing effort across all channels...
Averaging averages in a retroactive manner is an extremely low-value way to make high-confidence decisions for the future.
What’s even worse, is that tools like Northbeam & Hyros sell themselves as being able to tell you what ad in what ad set in what campaign drove a sale.
Not only is this extremely disingenuous,
because every customer's journey is different,
it’s also not a way to make future decisions on Facebook,
because it is built on the concept of micromanaging machine learning at scale.
The honest truth is, every single ad ever shown to anyone is a Retargeting ad…
& we have no control over the customer's journey before we are lucky enough to show our ad to a specific user…
& we have no idea their level of intent when an ad is shown.
There is a reason that these tools are extremely popular with ad agencies,
It is fundamentally impossible to truly measure the impact of any marketing channel as a constant against the customer journey at scale in any market.
The idea that any customer journey flow is fairly uniform is a critical fallacy.
You cannot measure a concept that is built on a false idea.
If the DNA of the tool is to measure something that doesn’t exist,
Then that tool is built to meet a business need that does not align with the growth of a brand,
And often built to satisfy the needs of people who have to justify their value by how much credit they deserve.
In the market today,
Triple Whale is the only full-scale attribution tool that is not built on helping an agency get credit, but more on allowing somebody to understand the impact of any specific marketing effort,
for the purpose of improving incrementality.
How do we measure incrementality and attribution?
The honest truth is, the concept of attribution itself is effectively a lie.
We can however, use it to understand platform-specific volume, value, and cost targets.
What we need to do is understand the impact across our ecosystem when we change our marketing mix and strategy.
For instance:
When we abandon Interest groups and Lookalikes and Retargeting Audiences on Facebook in favor of Broad…
We know we will see more search volume and a greater volume of valuable site traffic.
Knowing that Facebook amplifies our site traffic volume,
Stabilizing the quality of that traffic allows us to optimize for these other efforts that are far more profitable.
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