Abstract
- Shift your focus. Understanding the limitations of attribution tools will improve your marketing strategy and effectiveness.
- Embrace collaboration. By sharing credit between sales and PR, your multi-channel marketing efforts are more likely to be successful.
- Data informs, not dictates. Use attribution data to guide your decisions without compromising your marketing intuition.
The rise of digital marketing attribution tools, combined with an overwhelming desire to validate efforts, has turned many marketers into data junkies.
In a desperate attempt to justify our budgets and prove why we deserve more money, we become obsessed with “claiming” every path of marketing attribution, trying to prove that it was our work that generated leads, drove sales, and captured new revenue. As a result, some of us lose sight of what it means to run a successful, integrated, multi-channel marketing function, which includes sharing credit with sales and PR.
We get it. Marketers have struggled to measure success for years. It's virtually impossible to know how many people actually saw a billboard or heard a radio ad, much less how many leads it generated. That's why it's no surprise that digital marketing attribution tools have become so appealing. Finally, we could directly link our audience's behavior to our efforts.
The problem is, many of us are so focused on marketing attribution, it's time to clarify what attribution can and can't do, so let's take a step back and discuss realistic expectations and why you don't need to get too hung up on attribution data to drive conversions.
Attribution measures effort, not cumulative impact
Attribution measures active efforts such as ongoing campaigns, live events, paid media placements, client gifts, or any other action your marketing department can take.
But they aren’t the only things that drive leads and move them through the funnel. Measurement of cumulative efforts like branding, word of mouth, PR, earned media, etc. can (and should) be done through market research, customer surveys, web analytics, media metrics, advertising equivalent value (AVE), and share of voice.
Branding and communications may not be attributed to a specific campaign or directly mapped to lead generation, but they contribute to overall lift and revenue impact. They are important components of any marketing toolkit and contribute to attribution, even if marketers are reluctant to split credit between PR and communications. Attribution can't measure everything, and that's okay. Either way, you need to measure them in a meaningful way and use that insight to inform your overall strategy.
Related article: Using Social Media as a Gateway to Marketing Attribution
Attribution data may not be straightforward
In some cases, marketing attribution figures can tell contradictory stories depending on your perspective.
For example, a client held an event to promote product X. In their current attribution model, marketing only gets credit for a lead if attendees start a conversation about product X. Marketing doesn't get credit if attendees have a conversation about product Y or Z or later decide they're interested in product Y or Z. Even though the event, funded by the marketing budget, was clearly the lead generation source, attribution went to the sales department or another initiative. Of course, giving all the credit to marketing wasn't the best solution.
This is a perfect example of why marketing can't rely on a one-size-fits-all attribution model. Instead, it needs to be able to calculate and configure attribution tracking from different angles, both in budgeting and in reporting across the company on its efforts. A robust attribution solution should be able to adapt to your preferences and parameters, rather than taking a broad-brush approach to measuring marketing performance.
Related article: How to do attribution correctly in Analytics
Accept the fact that you can't capture all attributes
Marketers need to be realistic about what attribution technology can do and understand its limitations. When human behavior gets involved, even the most carefully mapped out conversion paths by data-driven marketers often go awry (sorry, Barnes).
For example, since the “Forward to a Friend” button was added to Mail, I can safely say that no one has ever used it to forward an email to a friend – they simply click “Forward” in their email client, and have no idea if the email was forwarded.
Or they can look at other behaviors and trends to understand the impact of their campaigns and adjust their approach. For example, they might copy that link from your e-newsletter and paste it into their messaging platform. And if someone clicks on that link, that counts as a conversion for your campaign as well, right?
While attribution software can provide some insight into such behavior as it occurs, there's no way to know for sure how or why someone responded to your content or campaign every time. Accepting that you won't be able to perfectly track everyone's behavior will help you set more realistic expectations. Collect what you can reasonably and accurately collect, knowing that there will always be some statistical uncertainty, and use that data. Use this data to inform your decisions, but don't let it drive them.
Related article: B2B Marketers Need to Embrace a New Vision of Lift-Based Metrics
Attribution is about trends, not direct 1:1 lead generation
A few years ago, I worked for a CFO who was obsessed with the number of daily new leads, specifically the thousands of records that had no lead source associated with them. Spending time and effort tracking down why random records had no lead source was pointless and distracted from the more important issue: what was driving our net new leads and how could we maximize those sources?
This is a common trap. Relying too much on reports and data to show how marketing is contributing to the bottom line can be counterproductive as you end up spending too much time defending minor discrepancies in the numbers instead of using that data to inform your strategy. As Carey Picklesimer recently pointed out, doses are bad.
Instead, use your marketing attribution data to understand trends and behaviors over time. Realistically, aim to understand around 80% of the factors that drove participation in each digital campaign. You might not get the whole picture, but enough to feel confident about their contribution to performance. Still, it helps you make data-driven decisions without getting bogged down in the details, blending data with your everyday intuition and leaving room to incorporate your marketing instincts.
Attribution is both an art and a science. Don't let dashboards and numbers tell the whole story. Instead, use that data to tell a story about your marketing performance and its contribution to revenue, but control the story of what insights attribution brings to your business.
Attribution can't solve all your problems (but it can provide information)
Marketing attribution is a valuable tool for measuring campaign effectiveness, but it is not without limitations. Marketers need to have realistic expectations and use attribution in conjunction with other methods to get a holistic understanding of the impact of their marketing efforts. Doing so will help them make more informed decisions, deliver real, measurable impact, and optimize their strategies for long-term success.
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