We’re taught in middle school science and math classes that defining and understanding variables is key within the scientific and mathematical methods. Yet, as grown adults and data analysts, we’ve somehow forgotten this core methodology. Variables are powerful. Take for example the title of this article–Attribution is B.S. The undefined variables of “B” and “S” likely took on an innate definition in your mind upon reading them. And while I love being a tad bit cheeky, for the purpose of this article “B” and “S” stand for “Business Sabotage” (though the obvious–and unprofessional–definition is also true and applicable).
When evaluating the success of our efforts, we often default to the simple formula of A + B = C. We assume that A (the ad) plus B (the traffic) will result in C (the lead). It seems straightforward, right? Unfortunately, it's not that simple in our industry. By viewing our marketing strategy through this narrow, linear lens, we overlook the influence of our additional time and efforts. This approach not only undermines our business but also risks losing valuable leads and, ultimately, sales. Additionally, it means we're spending more money for the same results. In essence, we're being inefficient and wasteful.
Attribution is Business Sabotage
If your analysis is purely linear, you're ignoring the impact of other variables and the various efforts that guide your customer toward becoming a lead. This means you're not giving yourself enough credit for all the time and money you've invested. More importantly, by not identifying these missing variables and their effects, you might end up spending too much in the wrong areas.
Let's break this down further.
Scenario A: The Misguided Marketer Spends More Money on Direct Attribution
Scenario A focuses on conversions–or “key events” that indicate a lead has been generated–tracking direct conversions from each ad. This strategy is granular and zeroes in on ads that convert the most leads through direct attributions. Essentially, it follows the simple formula of Ad + Traffic = Lead.
Ad Attribution Example 1:
- 360 leads are attributed to a paid company branded search campaign.
- The Missing Variable:These customers likely already knew about your company. They’ve visited or interacted with your brand before and are now returning to take the next step. This paid campaign likely didn’t bring in new customers but rather returning ones ready to convert.
Ad Attribution Example 2:
- 45 leads are attributed to a lead generation Meta campaign for a specific community.
- The Missing Variables: While the lead count looks impressive, the quality likely isn’t. Many of these leads might not be real or qualified, with only a small fraction converting to appointments or sales. Additionally, a general market campaign running at a third of the cost-per-click of the lead generation campaign generates 20 times the traffic and effectively serves its purpose of brand discovery. Meta is a platform for awareness, it's push marketing after all.
We’re not saying these campaign strategies are worthless–they do serve their purpose. However, if you rely solely on linear conversion attribution to determine success and allocate budget, then you’re at risk of business sabotage.
- You might end up paying top dollar for traffic you could get through organic efforts.
- You could allocate budgets to ads with a high cost-per-click but low reach, effectively paying three times more for the same lead volume.
Scenario B: The Savvy Marketer Spends Money on Optimized Performance
Scenario B’s marketer takes a step back and evaluates the overall performance of their digital efforts. In this strategy, the marketer understands that while A + B = C, the variables can have different meanings and lead to better results at a lower cost. This marketer understands that a rising tide lifts all boats. They run a full analysis, adopting a holistic approach with all their efforts.
- Variable A is a general market ad on Meta with a low cost-per-click, generating 50% of your Meta traffic to your website.
- Variable B is an in-market display ad via Google, running at $5 per day and driving a high volume of traffic to your site.
- Variable C isn’t a lead or even high-quality traffic—it’s characterized by low time on site and low key event conversion. However, Variable C results in an increase in organic search traffic, which is your true moneymaker.
Key Insight: Low-cost awareness campaigns can significantly boost high-intent customers who return to search for you, spend considerable time on your site educating themselves, and eventually convert into leads.
The Cost of Linear Conversion Attribution
These campaigns may feel familiar to you, and in a well-rounded marketing strategy, it’s normal to have all these campaigns running simultaneously. This is fine, especially if there’s a balance between spend and the expected results. However, if we only focus on high-cost, high-conversion campaigns and neglect the smaller, successful channels that build awareness or target intent, the data can reveal surprising insights when we analyze with actual dollar amounts.
In Scenario A above, let's say a company spends $4 per click on Google and $7 per result on Meta (as defined by Meta), and let’s say their funnel performs at national benchmark levels:
- They generate 100 leads
- They book 41 appointments
- They result in 8 online sales
The results look great, but at what cost? In this case, they spent $55,000 on digital marketing, which translates to $550 per lead and $6,707 per sale.
Applying the same to scenario B, the company spends $1.50 per click on Google and $0.50 per click on Meta. They also perform at national benchmark levels, but their results only cost them $10,000 on digital marketing, resulting in $100 per lead and $1,219 per sale.
This breakdown examines data over the course of a month. If we apply this trend over a year of marketing, spend, and sales, the total budget difference would be a staggering $540,000 per year for the same number of leads and sales.
The Nail in the Coffin: You’ve Been Spending Money Based on Data That’s Not True
Beyond the financial implications of linear data analysis, there’s an often-overlooked truth about conversion attribution: your attribution data might be misleading you. If you rely too heavily on attribution to tell the story of your customer, performance, and investments, you might miss crucial layers of data that need to be addressed.
