How Do We Build an MVP Marketing Attribution Structure?
Ask these questions to begin understanding what drives results and how
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We’re in a challenging economic climate right now.
Mass layoffs.
Slowdown on purchasing.
Capital is less readily available.
And like a fierce wind fanning a spreading wildfire, this all contributes to an increased focus on the one thing all marketers are accountable for - yet few have found a means to crack.
I’m of course talking about attribution.
Figuring out how a spent dollar equates to an earned dollar (or more) is one of the toughest challenges a modern-day marketing team has to face.
This is especially true in businesses with long sales cycles or complex value propositions where - after a qualified lead has been acquired - sales takes over and inherently captures most of the closed-won credit.
And look, there is something to be said about a rising tide lifting all ships. If one of us is seen to be winning, we’re all winning, right?
My experience is that in boom times there is more appetite for this attitude. But if a belt must be tightened? You know a CFO is going to cut whatever isn’t perceived to be delivering short-term revenue.
Where does that leave us then as a marketing function?
We must find ways to point to the commercial results of our efforts. Failure to do so results in a negative impact on our available resources and overall reputation with an organisation come budget season.
And that starts by implementing an MVP Attribution Structure within our organisation.
So let’s break that down - right after this message from the sponsor of this week’s B2B Bite.
My friends over at Dreamdata - you’re going to hear from their CMO in just a minute - have published a fantastic piece of research that illustrates just how complex the B2B buyer journey is based on real-world data aggregated from their platform.
Some of the highlights include:
The average customer journey takes 192 days (that’s over 6 months!) from first touch to closed-won.
Across industries, the average number of touches before a deal closes is 31 - with mid-sized companies having 20% more touches than large B2Bs.
You should expect to see 1.9 contacts involved in researching vendors on average across industries.
It’s important to know all of this as it allows us to better understand the buying journey. And when we understand the journey, we can deliver impact.
Some of Dreamdata’s customers have grown the sales pipeline by 70% just by getting a better handle on what works and what doesn’t.
Want to read the full report? Check it out by hitting the button below.
Before we get into the components of an MVP Attribution Structure, I wanted to first get a sense of why attribution is so broken in B2B. So I spoke to Steffen Hedebrandt, CMO and Co-Founder of Dreamdata.
He was fresh from giving a presentation at the CMO Alliance on the ‘Why Most B2B Marketers Don’t Know What They’re Doing’ where he covered why customer journeys are so hard to measure.
He broke it down into two core reasons.
How a customer goes from awareness to conversion is a really complex series of steps. “Lots of people, lots of time, lots of tools, lots of all sorts of crap,” he said. “At Dreamdata, we put out some benchmarks last year on our own business where we found that on average the customer journey took 192 days from first-touch to closed-won… if you say your customer journey is a certain length, it’s probably twice that.”
The various systems we use to measure attribution are a hot mess. “On top of this, you’re facing a really messy tech stack set-up where you have a lot of different silos. You have a CRM system, and tracking software on your website, you buy ads, you gain traffic from Google… some of them speak to each other, some don’t, and some create duplicates. It’s a mess. So how does a B2B marketer have a chance at understanding the customer journey?”
This leads to a bunch of poor habits when it comes to attribution, from an over-reliance on Google Analytics and ad platforms to using the wrong metrics to determine marketing success (i.e. loosely qualified ‘MQLs’).
You can check out the full talk given by Steffen here if you register your email.
“OK Jason - you’ve given us a lot of problems. Let’s get to the solutions.”
Great idea.
How do we get started when it comes to mapping commercial success to our efforts?
When I joined a global technology solutions provider as the first marketing hire back in 2018, I started by asking questions in three places - People, Processes and Technology - to help guide the build-out of an MVP Attribution Structure.
People
Questions include:
Is the wider commercial team aligned on core metrics? What you’re looking for: Everything breaks down when marketing and sales operate in a silo. Alignment can only start when teams are measured against the same North Star metrics - pipeline and revenue.
Who is responsible for attribution? What you’re looking for: Attribution is a team sport but it needs a leader to ensure the initiative remains a priority. I want to know who that person is and what other stakeholders are involved - and where their responsibility begins and ends.
Is there regular communication between stakeholders? What you’re looking for: Marketing and sales (and any other commercial-focused function) need to talk to one another to understand what is working and what isn’t. Ensure there is a weekly touchpoint for analysing attribution and making amendments as needed.
Processes
Questions include:
What attribution model will we use - and how often do we review and adjust? What you’re looking for: Last-touch, first-touch, time-decay, U-shaped… picking the right one can be a minefield. But we need to start somewhere if we want to begin to understand the buyer journey.
Do we have a disciplined data culture, and how can we ensure accuracy and consistency? What you’re looking for: Any attribution strategy is only as good as the data that feeds it. Companies must not only deeply understand the customer journey and what touchpoints to measure, but also adopt robust data hygiene practices and insist they be followed across the board.
Are we utilising UTM links? What you’re looking for: Many companies only use UTMs sporadically, missing out on an opportunity to capture the data that will lead to sound investments. We must use UTMs on everything - online and offline - to build up a picture of what works and what doesn’t.
What is our experimentation strategy? What you’re looking for: We don’t want to throw spaghetti at the wall here - testing and experimentation have to be considered. As we’re collecting data and gleaning insights, we need a process to ensure that opportunities for improvement are put into action.
Technology
Questions include:
How are we collecting and integrating data? What you’re looking for: After we’ve built out the customer journey - online and offline - we need to determine whether we have the relevant mechanisms in place to capture that data and centralize it for analysis.
Are we using the same systems? What you’re looking for: There are many companies where teams are using different platforms (like CRM) to manage commercial strategy. It should go without saying - you need to minimise technology misalignment across departments!
What can be digitised? What you’re looking for: We need to ruthlessly cut out any manual work that can be handled by technology. Every hour spent harmonising data sets or doing data entry is another hour not spent doing a higher ticket value activity - like winning deals.
Do we have a platform to make sense of all the noise? What you’re looking for: Something like Dreamdata take automatically extract, clean and simplify data across systems to give a complete picture of the B2B customer journey - in turn generating insights that help improve performance across the board.
Implementing a strong marketing attribution strategy is crucial for businesses to understand the impact of their marketing efforts, allocate resources effectively, and demonstrate commercial results.
By focusing on answering these questions across people, processes, and technology, businesses can align teams, establish the right attribution models, ensure data accuracy, and gain valuable insights for improved decision-making.
PS.
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Without data everyone trusts, people won’t believe the attribution breakdown.
In fear-based companies, attribution is especially hard because people want to promote their achievements over someone else’s.