A difficult conversation is unfolding between marketing leaders and the C-suite. CMOs realize that static, deterministic metrics like attribution create false narratives. Many worry that CEOs will blame or shame them if they reveal that new insights debunk much of their previous reporting.
The fear is real, but the bigger risk is that you’ll get stuck with bad metrics once you know they don’t work. It’s better to embrace the complexity of marketing and apply measurement methods that reflect how customers actually buy.
I asked marketing experts who have guided companies through this transition to share their best strategies for earning executive buy-in. Here’s what they recommend.
Position the shift as a strategic evolution, not an admission of failure
Marketing measurement exists to bring data-driven clarity to what works and what doesn’t. This insight enables smarter budget decisions and strengthens the customer journey to drive more revenue. Marketing automation has taken the first meaningful step toward this goal by incorporating data into marketing decisions. It also provided a partial view of the steps customers go through on their way to a purchase.
But with attribution, companies went too far with data. It tries to make data do more than is possible and creates false stories in the process. Customer journeys look less like a linear funnel and more like a child’s doodle.
Markets are complex systems, not predictable machines embedded by attribution. As a result, companies often make worse marketing decisions with attribution than without, causing more pain than necessary.
Reasons for going beyond attribution include:
Attribution requires predefined rules (e.g. first touch, last touch, multitouch or time decay)
In the messy real world, it’s impossible to know with certainty in advance what customers will do. Markets are semi-predictable in the way the weather trends and patterns, and marketers can use data to gain insight into this – but nothing is guaranteed in the way attribution implies. Interactions between billions of people and businesses create feedback loops within market systems, introducing uncertainty into every situation.
Attribution favors what is measurable, not what is important
Not every point of contact can be tracked. The influence of brand, PR, word of mouth and loyalty is completely missing. Lower-funnel channels that drive clicks (like email and paid search) get more credit than upper-funnel engagement, even though mounting evidence shows that early interactions are often more influential.
Attribution obscures the interdependencies of marketing
Marketing cannot be reduced to the sum of its parts. When you buy a car, how can you attribute part of the price you paid to the billboard you saw last month, your brother-in-law’s recommendation from two weeks ago, last week’s TV ad, the Instagram ad from the day before and the location of the dealer?
Attribution prevents marketers from discovering the real contributors to sales growth. Simplistic conclusions from complex situations lead to incorrect decisions.
Dig deeper: It’s time to move away from multi-touch attribution
Document your entire customer-centric buying process
To get the most accurate story, you need to collect a broader range of data. The customer buying process is much more extensive than most companies realize. Once executives see the bigger, more complex reality, they are less likely to rely on simplistic short-term metrics like attribution.
When documenting, focus on three areas that are often overlooked.
Make sure that the purchasing process really runs from the outside in
Your sales funnel is not the customer journey. The funnel represents an internal process, and while measuring it can reveal where waste is occurring, it doesn’t help you understand actual customer journeys or markets.
Expand the purchasing process as completely as possible
Dig into what is hidden. A company’s sales process may only overlap a third – or even less – of what customers actually think and do. The journey can take years and involve multiple buying cycles, double-digit purchasing teams and hundreds of interactions. Pay close attention to identifying conversion moments.
Watch for holes
Organizational silos cause even the smartest teams to miss steps in the customer journey that fall between functional boundaries. Journeys often stall when customers need content that isn’t captured in marketing metrics (because they don’t generate leads) or sales metrics (because they don’t close deals).
Consider this documentation – and the data collection behind it – a work in progress. Early versions may be incomplete and inaccurate, but as your data improves and analytics mature, you refine the picture until it becomes a useful GPS for an ever-changing, probabilistic market.
Dig Deeper: How Attribution Masks What Actually Drives Growth
Connect new marketing metrics and methods to the business
Metrics help coordinate functions within the business, and evolving marketing metrics will inevitably impact other areas. Before finalizing your plan and presenting it to the CEO, consult with the CFO and CRO about how current methods are working for them.
Marketing measurement is moving toward analytical approaches used in probability effects environments such as economics. These methods can reveal trends and causes in messy real-world systems in ways that attribution cannot. However, these insights differ from what companies are used to. You should discuss how these changes impact business decision-making and how new marketing data can support more accurate financial guidance.
Today, the leading method for advanced marketing analytics is marketing mix modeling (MMM), a form of multivariate regression analysis. MMM examines potential causal relationships between multiple factors simultaneously – an ability that is essential for marketing.
Data specialists look for relationships between a single dependent measure (for ROI, this would be the financial ‘R’ mark) and two or more independent variables (in marketing, a range of possible contributing tactics). Using this method, analysts identify the best match that connects current results to past interactions.
Causal inference is another advanced option. It goes beyond the associations and patterns that MMM can reveal, and identifies more accurate and lasting relationships. The use of AI and related technologies makes these methods increasingly affordable and accessible.
Dig deeper: Why causal AI works when other prediction models fail
Perform a silent proof of concept (POC) before rolling out new methods
Once the marketing team has a few months of experience with the new methods, they will be better prepared to answer the many questions the CEO and CFO will inevitably have.
Consider running a silent POC in addition to existing methods for a period of time. Because buying cycles often include time lags between activities and the outcomes they impact (sometimes months or even years), incorporating several months of data will increase clarity.
Empathize and keep the conversation going
As you develop new capabilities, continue the dialogue with the CEO and CFO. Understand what they are trying to achieve and how your changes impact their goals. Don’t assume you know their perspectives – and don’t force alignment. The CEO will have the final say, so their support is essential to the journey.
Marketing metrics are best used as fuel for collaboration, not as performance scores. This shift will take time, and everyone will learn and adapt as they go. Most will also need occasional reminders of why the change matters. The old deterministic mentality runs deep – and it can be difficult to let go.
Dig deeper: the smarter approach to marketing measurement
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