All About Attribution Models
So, someone clicked on your ad. A brand new customer made a purchase. But how should you determine what piece of marketing actually attracted that new customer? In turn, how should you determine how to utilize your budget in the most efficient way?
You may have guessed it…from the title. There are several attribution models that offer unique insights into which digital marketing channels are working for your business (and which ones are lagging). The three important types for our purposes are: Last Click, First Click and Multi-Channel. Cross-Channel attribution is where we’re headed in the future.
Last Click Attribution
Last click attribution assigns 100% of acquisition value to the final channel a user visited before making a purchase. This allows you to measure how effective a channel is for driving conversions; this, however, does not offer insight into what combined efforts might be working, or what channel might have drawn in potential customers in the first place.
First Click Attribution
First click attributes 100% of acquisition value to the original channel that brought a customer in. Another good one for startups, this attribution model heavily relies on a customer’s ability to remember a brand when making a purchase. First click attribution shows which strategies are best for driving qualified brand awareness.
Your customer saw a display ad one month ago, and then he or she clicked a paid search ad 2 weeks later. Eventually, a remarketing ad converted that customer. Would attributing the entire sale to the remarketing ad alone do justice to the efficacy of your entire strategy? Not necessarily.
Multi-channel attribution gives credit to multiple touch-points along the customer purchase journey. Establishing different weights associated with each of the channels in the example above offers a unique way to understand what channels are doing their jobs well. Multi-channel attribution is forgiving, especially when sales cycles are long and you’re operating in a time when all businesses need to stay top of mind.
All in all, multi-channel attribution means that you can gain insight into what channels, ads, and methods are driving qualified brand awareness. It helps you answer a very important question: how is the conversion funnel operating and which channels are making the most difference? Viewing your Multi-channel funnels report in Google Analytics will get you started as you explore this attribution model.
Startups or any company implementing a branding campaign should be interested in seeing how brand awareness spreads from channel to channel.
A Note About Cross-Channel Attribution Modeling
Though I’d certainly hesitate to say last-touch methods don’t offer viable information, this articlemakes an interesting point:
“According to a Forrester Research report on attribution modeling: ‘Traditional one-to-one, last-touch methods of allocating demand to marketing efforts are outdated and lead to a suboptimal marketing mix. Customer Intelligence (CI) professionals must adopt a cross-channel attribution model in order to optimize marketing budgets, accurately calculate customer value and acquisition costs, and develop a holistic view of the marketing ecosystem. Failure to embrace this new standard is expensive — firms will be plagued with continued channel conflict and an inefficient marketing budget.’”
Marketers are utilizing more and more channels to reach more and more people; on average, marketers are using 13 channels to reach their audiences. However, a majority of these marketers aren’t measuring the combined effects of their multifaceted strategies. 41% look at each channel separately; 36% are trying their hands at cross-channel attribution.
84% of those recently surveyed “said that it is very to critically important to them to be able to change media buys based on prior attribution results and impact and 76 percent find great importance in measuring incremental sales by channel.” Cross-channel attribution is ever-growing in importance as new marketing technologies and channels evolve everyday.
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