7 Things CMOs Should Know About Attribution

If your knowledge of marketing attribution is murky, you're not alone. Columnist Scott Rayden lays out the key points every CMO should understand.

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Marketing attribution — assigning credit to a marketing touchpoint — has never been more complicated. The explosion of marketing channels and devices has added layers of complexity to what was, a few years ago, a relatively simple funnel.

If you don’t have much of a foothold in your understanding of attribution — or if you have what you feel is a shaky one — you are most definitely not alone.

The majority of marketers (digital or otherwise) can’t say with certainty exactly how valuable each channel or touchpoint is during each customer’s purchase process. That means they can’t say they’re effectively spending their budget and optimizing revenue, which is the entire goal of attribution.

In this post, I’ll break down seven things CMOs need to know about attribution that can make a difference in how you approach your marketing budget — without giving you a headache in the process. (Big hat tip to 3Q’s Ron Fusco and Big Squid Interactive’s Chris Knoch, who flesh out these points in an awesome webinar.)

Let’s get started.

1. There’s A Low Barrier To Entry

Let’s say you haven’t really even thought about attribution, and you’re “only” set up to understand the performance of specific marketing channels — Facebook, Google, Twitter, etc. Believe it or not, you’ve already got a lot of the mechanics in place to do some basic attribution if you’re using Google Analytics and tracking data correctly within each channel.

For each channel, you’re tracking specific KPIs (key performance indicators). Thanks to Google Analytics, you’re also tracking how users engage with your site — where they enter, where they bounce, how long it takes them to convert.

And if you’re on a B2B model, you’ve (hopefully) tied that info to your CRM (customer relationship management) or other database and can tie that activity to revenue. That means that you’re already assigning value to marketing interactions — and that you have the elements in place to dive deeper.

For instance, using just the data in these tools, you can understand where the channels fall in the purchase process. Do Google clicks lead only directly to conversions, or can they be a cost-effective way to feed the top of the funnel? Do Facebook mobile ads work for direct response? (In both cases, the answer is often yes.)

You can set up basic attribution models (first-click, last-click, even distribution across clicks) using just this data.

2. You Can Accomplish A Lot For Free

When you think of what’s possible with attribution — all the technologies and advanced models out there — things start seeming very complex and very expensive. (We partner with Convertro for our advanced modeling.)

But all that stuff we just talked about in the first section? That’s free. And with the data you glean from those sources, you can do things like set up your funnel touchpoints across channels; deduplicate conversions (e.g., make sure both Google and Facebook aren’t both taking credit for the same conversion); and develop and test hypotheses about how and where users interact with your brand.

3. Communication Is Key

Whether or not your digital teams are working in channel/device silos (note that one of the side effects of good attribution is removing those silos altogether), one of the absolute requirements of attribution is for all parties to agree on the goals of the attribution program, the key metrics involved, and the models being tested.

The goal of attribution is to produce more revenue by spending more effectively, but without clear communication, some teams may fear that they’ll lose budget — and therefore status — and get territorial.

4. Attribution Requires An Alignment Of Teams

Attribution isn’t just a marketing issue! Installing more complex models will involve tech teams, and at the higher levels, the finance teams should be in on the goals of the program from the beginning.

It’s generally acknowledged that over-crediting the bottom of the funnel (e.g., Google or Bing) means that funds will be unnecessarily tight for upstream channels.

If you can use attribution to show the value in those upstream channels, the finance folks might be persuaded to open up the purse strings a little — but those folks need to be included in the attribution talks from the onset to understand the significance of the data.

5. LTV Is Crucial

Among the metrics your teams need to understand, the most important, and the fulcrum of a good attribution program, is the lifetime value (LTV) of a customer.

If you rely only on single-conversion events as the ultimate goal, upstream clicks get undervalued. The traffic coming in at the top of the funnel looks a whole lot more important if the end result is measured over time, not one single purchase.

This matters in B2B just as much as ecommerce, by the way — even one-time purchasers can add value with access to, say, a referral rewards program.

6. Nothing Replaces Testing

Even if you somehow manage the perfect attribution scenario, where each click and impression is magically translated into an accurate value that informs a gold-plated marketing budget, you’ve got work to do.

As with everything else in digital marketing, nothing replaces testing. Those clicks could be more valuable with better ad copy; that conversion rate from a mobile click to a desktop search could be boosted by a sharper product image or more streamlined lead gen form.

The goal of attribution, again, is to assess the value of each marketing touchpoint so you can spend more effectively. But that doesn’t inherently increase the value of those touchpoints; that’s still on you and your team.

7. Perfection Is Not The Goal

That perfect attribution scenario mentioned above? You might as well accept the fact that you’re never going to get there — or, at least, not for the foreseeable future (and beware the tech provider that says otherwise). Every model, no matter how advanced, has its flaws.

U-shaped, Game Theory, econometric, Time Delay, etc., are all nuanced and complex, and they give you more insights than simple last-click. But none of them paints an exact picture, so part of the secret of “mastering” attribution is knowing when good is good enough and when the pursuit of the ideal is just a dangerous rabbit hole.

Clear as mud, right? Hopefully the attribution picture is a little sharper than it was before you started reading. The fun part is that, like everything else in digital marketing, attribution changes a little every week as new technologies and channels emerge.

You can be sure, though, that the tenets of good communication between teams, agreement on key metrics, and consistency of goals will be important as you go forward.

Good luck!

Marketing attribution and predictive analytics: A snapshot

What it is. Marketing attribution and predictive analytics platforms are software that employ sophisticated statistical modeling and machine learning to evaluate the impact of each marketing touch a buyer encounters along a purchase journey across all channels, with the goal of helping marketers allocate future spending. Platforms with predictive analytics capabilities also use data, statistical algorithms and machine learning to predict future outcomes based on historical data and scenario building.

Why it’s hot today. Many marketers know roughly half their media spend is wasted, but few are aware of which half that is. And with tight budgets due to the economic uncertainty brought about by the COVID-19 pandemic, companies are seeking to rid themselves of waste.

Attribution challenges. Buyers are using more channels and devices in their purchase journeys than ever before. The lack of attributive modeling and analytics makes it even more difficult to help them along the way.

Marketers continuing to use traditional channels find this challenge magnified. The advent of digital privacy regulations has also led to the disappearance of third-party cookies, one of marketers’ most useful data sources.

Marketing attribution and predictive analytics platforms can help marketers tackle these challenges. They give professionals more information about their buyers and help them get a better handle on the issue of budget waste.

Read Next: What do marketing attribution and predictive analytics tools do?

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.

About the author

Scott Rayden
Scott Rayden is the Chief Revenue Officer for 3Q Digital, and is responsible for leading marketing, sales, and the overall revenue growth of 3Q Digital nationwide. Scott spent the past 7.5 years as the Founder and President of iSearch Media, a leading digital marketing agency focused on consumer behavior, search marketing, analytics, and data visualization. iSearch Media was acquired by 3Q Digital in 2014.

Scott brings 14 years of experience in digital marketing, management, M&A, and business development to 3Q Digital. Prior to founding iSearch Media in 2006, Scott worked at Quinstreet and LeadClick Media (acquired by First Advantage for $150MM), two of the largest digital marketing agencies in the country

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