This article is part of an occasional series from leading voices about key issues facing marketing today.
In the same way that the advertising industry is handcuffed by faulty attribution models, marketers are struggling to attribute conversions to campaigns that their teams have run.
The reality is, just 17% of people say purchase is their primary purpose when visiting a brand's website for the first time, according to a recent Episerver study, which means there are multiple touchpoints for marketers to lose sight of whether or not audiences took positive action from a marketing asset.
As visitors click from page to page on your site and third-party channels like social media and search engines, the attribution data that shows where they came from starts to pick up more and more characteristics—never again showing marketers clearly that their asset or campaign was what brought in the sale.
Marketers have taken on greater IT power in the last several years—with chief marketing officers outspending their chief information officer counterparts. And with great responsibility comes, as the saying goes, great responsibility. Marketing teams are feeling the pressure to prove that the technology and tactics they use are deriving monetary value for their companies. Proving return on investment (ROI) is, in fact, the second-biggest marketing challenge behind generating traffic and leads, and ahead of securing enough budget.
It is, however, marketing teams' own agendas that got them here. As digitally focused teams rightfully moved past mass media to focus on specific, high-value audiences and spent budget only on the strategies they could track, they lost the ability to move through their organizations without accountability. Heck, even the systems they fought for and implemented have worked against them by failing to connect how they were directly responsible for conversion events.
Like the ad industry's attribution models, the sale could be credited toward the channel that the person first engaged with (first touch), the channels closest to the sale (time decay), and the last item a person interacted with before the conversion, among others.
Although companies do not necessarily organize their wins and losses by those specific attribution models, there needs to be a way to use similar formats to prove ROI internally, to answer questions such as...
- What department was ultimately responsible for the conversion? For example, if a whitepaper is released, was it the team that created the asset that should be able to include conversion reporting as a win for themselves ,or was it the team that heavily promoted the asset?
- What decision ultimately showed results? For example, how long did an asset show on the homepage until conversions started happening?
Because every brand decision should be quantifiable, content generation practices should be planned with conversion in mind. Accordingly, marketing teams should have the goal of attributing every asset and block of content toward their success metrics. It should be the goal of every marketing team to get to the point where every website element is trackable toward end goals.
Metrics like time on site are easy to obtain, of course, but it is difficult to know what got a person to stay on the page, the path that got them there, and more... without seeing the full context of that person's journey.
The ideal approach to attribution in a company's data practice is to use lifetime attribution versus recency attribution. Consider these likely scenarios:
- Did a social media post generate in-store revenue? If so, this attribution toward social will likely never be made.
- Did a whitepaper cause someone to call a salesperson even though they themselves didn't download the asset? If so, the whitepaper creators will likely never get credit.
- Did a paid search ad prompt a Facebook Like, followed by a website visit, followed by a sale? Oh, boy... figure that one out.
- Did someone refer the person to the site from a social media link they posted on their private Facebook profile, but the person bought online months later after searching for the company on Google? Why should organic search get the credit?
Last click or first touch are a great start, but marketers are forced to dumb down their results with these traditional models. To get a bigger, better picture from their favorite third-party analytic systems, marketers are required to depend on developers to highly customize the product to them. And, off the shelf, some vendors provide sitewide metrics from an individual user perspective—making this product more customer journey-centric than popular analytic systems, and collecting a level of data that Google strives to get natively.
What marketers do not need more of, however, is unstructured data they must scour to glean meaningful insights, which means visualization will be key to quick understanding. Business users should be able to open a specific user's profile to see their customer journey, such as whether a specific person (with non-personally identifiable information) clicked on a certain page, and compare similar journeys. What starts to happen then is that marketers get attribution information as to what the most common path is in and out of that asset; and based on those trends, marketers might try to adjust that content and other related site content to promote similar conversion patterns to shape them.
If an asset or image typically results in a person's leaving the site, then the marketer can update it with content that resonates with customers—proven by data—to reduce abandonment. More positively, the marketers can start to get recommendations about using creative based on its results on the site. Marketers can then identify traits such as similar browsing habits or geolocation about user groups to drive them to offers, creatives, and rewards that visitors will be motivated by.
The more dashboard analysis of this type of information that business users can receive, the more the everyday marketer—sans a data scientist colleague—can report and build on this data to prove their team's ability to generate revenue.
To become a data-driven marketer the way many promise to be, marketers need to work with a system that suggests creatives and, based on what they are trying to do while building the customer journey map, identify what assets resulted in which conversions. For example, based on any asset stored in the content management system (CMS), a system can—and should—indicate that when this asset is used, it leads to conversion X percentage of time.
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The need to prove ROI individually is going to get greater as marketing teams look for additional budget to spread across the many channels they wish to market on. As marketing teams take on more, every decision will need to have an attributable value to understand who is credited for the conversion—even if no money is exchanging hands internally as would happen in an external relationship (e.g., an advertiser and a publisher).
The good news is that systems are in place to help with this challenge now; and the more marketers know about attribution data, the more they know about the consumer to personalize the site to drive further action.
You may like these other MarketingProfs articles related to Metrics & Measurement:
- The Biggest Benefits of Marketing Revenue Attribution
- Advanced Measurement Strategies: Metrics That Actually Matter
- The ROI Dilemma Marketers Face With Programmatic Advertising
- The Silver Lining to the Death of the Cookie: Better Measurement
- Six Key Metrics for Measuring Online Event Success [Infographic]
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