Attribution was once marketed as a silver bullet, capable of providing definitive answers to all your marketing ROI questions. The range of attribution complexity is vast; at one extreme are the organizations that believe a website form can be a proxy for attribution (it can’t), and at the other end are the ones that attempt to over-engineer their DIY attribution model into a crystal ball (they can’t).
In the fast-paced world of B2B marketing, your campaigns may appear sleek and enticing, but the ultimate question remains: Will they drive meaningful results? To unlock your organization’s full potential, it’s essential to align your strategies with the right audiences.
To power your strategy, your attribution model needs to be a fine-tuned engine that delivers clean, actionable, and reliable data. As CaliberMind’s Head of Insights, I’m here to steer you through the diverse terrain of attribution models and shed light on when B2B companies typically venture into customization. Moreover, we’ll delve into the steps to take if the intricate components of your model threaten to unravel, potentially leaving you with a heap of unreliable insights.
When organizations implement multi-touch attribution, there are often questions to answer and issues to address. You might turn it on and then discover inconsistencies and all of a sudden your data is now seen as unreliable and the confidence you have built among other departments and stakeholders is now out the window. Don’t panic. Typically when you hear someone say the data is broken, it means they don’t trust the data. Still, most of the time, you are either missing something in your model or you’re over-counting something like email sends. It’s so easy to want to put all the touchpoints in there, but for something to actually get revenue association, there has to be some sort of meaningfulness to the touchpoint, some sort of inbound response.
Third-party data has great potential of becoming incredibly useful and it comes in varying shapes, sizes, and forms. Depending on the nature of third-party datasets, it can positively impact attribution.
For too long, executives have poo-pooed marketing’s ability to understand metrics and speak the alphabet-soup business language adopted by SaaS. Many have even heard our department jokingly referred to as “the arts and crafts” department. This misconception stems from no “gold standard” for marketing key performance indicators, a lack of consistency in what investors ask from their portfolio companies to prove marketing “works,” and a lack of understanding of the challenges marketers face when summarizing their data.
Attribution is #complicated, and what makes it so difficult is organizing data in a sequential manner so that it can be analyzed. This difficult task may seem daunting, but once perfected, it unlocks several meaningful insights about your customer journey – not just how much “credit” a campaign should get.
We’ve had many conversations around requirements gathering and how you need to set attribution up differently based on what you’re trying to do. We’ve also explored data hygiene and best practices. The next stage involves discussing where we need to pull data from and where we’ll be pushing it. Misha Salkinder, Director of Customer Data Strategy, at CaliberMind, shares his insights on data connectivity in multi-touch attribution for B2B.
Camela Thompson, Go-To-Market Maven at CaliberMind, discusses why B2B attribution adoption is a challenge and how to fix this problem.
Andrew Sawusch, Head of Customer Operations & Onboarding, at CaliberMind, shares his insights on what needs to be done prior to implementing attribution, the concept of the virtual campaign, and some best practices when it comes to UTM parameters.
Boiling marketing impact down to a single number doesn’t make sense. So how do we balance what the board is asking for with fair representation of everything we do?Watch a panel of experts discuss how CMOs can prove ROI and own the boardroom.
Nic Zangre, VP of Customer Success & RevOps at CaliberMind, joins our host, Camela Thompson for this conversation on DIY Attribution. Nic shares his insights on why it’s critical for people to slow down and ask why, how those reasons change how we think about implementing attribution, and the instances where machine learning might not be the right answer and where it does fit really well.
Misha Salkinder, CaliberMind’s Director of Customer Data Strategy discusses the tools of the trade, including the pros and cons of each of your options. He also outlines the level of expertise and the time commitment that goes into attribution.