Have you ever run campaigns on different channels such as Google & Facebook - only to find wildly varied conversion numbers between the platforms?
“Why doesn’t xxxx and xxxx conversion data match my CRM/Google Analytics” — This is an all-to common question.
Most of us have faced this — Some know why and some don’t, this article is intended for the latter.
Ad platforms can/do attribute ‘conversion credit’ differently.
Attribution is one of those things most marketers understand at a very high level but rarely dig into the nuts and bolts of. The main reason most marketers don’t have a grasp on attribution is that it can get very complex and there isn’t a ‘1 size fits all’ solution.
So what is an attribution model?
An attribution model is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths.
Quick example :
A user sees one of your Instagram stories then visits your blog — they read the content then leave.
1 week later - they click a Facebook ad promoting your product — then leave the site to look at reviews.
Then 2 days later — they search for your brand on Google to then make a purchase.
Which marketing channel deserves credit for that sale? Was it instagram that generated initial interest? Was it Facebook that served a timely remarketing ad? Or was it Google because that’s the last thing the user did before buying?
This is where attribution comes in.
Attribution is determining who gets what credit. An attribution model is the formula used to optimize your marketing.
Below are 3 things every marketing manager should know about attribution modeling:
1. There are many types of attribution models
The best attribution model for a business is determined through ongoing testing and optimization of your campaigns. There is no perfect model for everyone and there are many tools to help you identify which model works best for you.
2. How to use Basic Attribution Reports in Google Analytics
Attribution reporting in Google Analytics is a great way to pull insights to help drive educated marketing decisions.
The top conversion paths report helps you paint a picture of the users journey over a period of time. Using this report to understand how a user first visited the site, all the way until the point of conversion is GOLD for educated marketing decisions.
You can also use the model comparison tool to compare attribution models against eachother. Use these model comparisons to help identify what benefits the bottom line of the business.
Paid attribution programs get expensive and confusing quickly — so understanding what you have access to for free in Google Analytics is the logical first step.
3. You should stop using last click attribution
Last click attribution gives 100% credit to the last thing the user did in the journey before converting.
Everyone… young AND old is moving between devices, apps and websites like never before. GONE are the days of users clicking and converting in one seamless motion.
20 years ago if you wanted to try a new place for dinner — you might have driven past a certain restaurant a few times, then dropped in to give it a try.
Fast forward to 2020 — If you want to try a new dinner spot.. you’ve been on Google maps and Yelp before even being hungry…
The Last click attribution model is old..
I personally like the position based attribution model if a brand I’m working with doesn’t have a custom or data driven model established.
The position based model distributes credit through the buyers journey by giving 40% credit to the first and 40% to the last interactions — the remaining 20% is distributed evenly in between.
So if we go back to our quick example from above using position based attribution:
- User sees a story on Instagram (40% credit)
- User clicks a remarketing ad on Facebook (20% credit)
- User searches on Google to purchase (40% credit)
Attribution can be a very deep rabbit hole - it’s important to remember before entering, you have a specific goal in mind. Going off of bad data or simply not enough data can lead to a slow and painful death to your funnels.
Sherlock nailed it with:
“It is a capital mistake to theorize before one has data.” — Sherlock Holmes
Thanks for reading and happy analyzing.