You’ve probably seen this stat around the last few years: the average tenure of a CMO is 2 years; the shortest of the c-suite. I don’t know if this is true or how to validate it. But it’s probably directionally correct.
B2B CMOs are under immense pressure to perform on many fronts. They must creatively grow the brand, analytically drive revenue, keep sales leaders happy, forecast for the CFO, collaborate with the CRO, all while leading their eclectic teams. In this fast-paced world of marketing, CMOs and marketing executives are struggling to do it all.
I dare suggest that ability to successfully accomplish these duties is being significantly hampered by rules-based attribution models. It’s a bold statement and a lot of blame to put on a single tool that thinks it’s helping. But let’s walk through it.
I’ll highlight six pains, why attribution makes it worse, and a better alternative.
1. Demonstrating ROI:
The Challenge:
Demonstrating ROI is a top priority for CMOs, yet many struggle to confidently produce this metric. Traditional rules-based attribution models fall short, failing to account for lift or incrementality and unable to measure all marketing channels comprehensively. This ultimately crushes the CMOs ability to confidently stand in front of their peers and explain the impact of marketing’s efforts.
The Solution:
Leaving rules-based attribution for machine learning approaches, like media mix models, offers a paradigm shift in ROI measurement. B2B media mix models analyze the entire marketing ecosystem, measuring all channels and accurately quantifying their impact on key performance indicators (KPIs). Unlike attribution models, media mix models provide a realistic assessment of lift to calculate ROI, empowering CMOs to show the true impact of their marketing efforts.
For years, my “ROI” was based on taking credit for an opportunity that marketing took sourcing credit for. This led to sourcing battles when sales asked us to peel back the curtain. These conversations were never productive. Media mix models stay at the macro level when explaining how marketing creates incremental revenue. So, you don’t end up in individual opportunity level sourcing battles.
2. Data Overload:
The Challenge:
In an era of data abundance, CMOs are overwhelmed with dashboards, tools, and KPIs, making it challenging to find actionable insights from the noise. The sheer volume of data can overwhelm even the most seasoned marketing professionals, limiting their ability to identify effective marketing efforts and allocate resources strategically.
The Solution:
B2B media mix models cut through the clutter by providing a clear, prescriptive approach to data analysis. Instead of drowning in a sea of reports, CMOs can rely on media mix models to produce many of the most important KPIs from a single tool and deliver actionable recommendations for optimizing those KPIs. By focusing on what channels to invest more in and which to scale back on, media mix models streamline decision-making while maximizing ROI and marketing contribution.
3. Fragmented Customer Journey:
The Challenge:
The modern customer journey is complex and fragmented, spanning many touchpoints and channels. Marketers try to understand it so they can improve and optimize it. But traditional approaches, including rules-based attribution, struggle to capture the full scope of the customer experience, leading to incomplete insights and missed opportunities for optimization.
The Solution:
Instead of taking a micro path-based view that is hard to glean insights from, take a macro approach. Media mix models take a holistic view of marketing activity, bypassing the need to stitch together individual paths. Instead, these models analyze aggregated data to identify macro-level relationships between marketing spends and KPIs. By focusing on overall trends rather than individual touchpoints, media mix models provide an actionable understanding of marketing effectiveness across the entire funnel.
4. Balancing Short-term and Long-term Goals:
The Challenge:
CMOs face the dual challenge of driving short-term pipeline while also building long-term brand equity. Traditional attribution models often prioritize short-term metrics at the expense of long-term brand building, leading to a skewed view of marketing effectiveness and leaving CMOs to think separately about these efforts.
The Solution:
Media mix models don’t require forms and leads to measure a channel. So, efforts like brand spend can now be measured for their impact on pipe creation, allowing CMOs to simultaneously drive short-term results and invest in long-term brand strength. With the impact of brand spend now connected to pipeline creation, CMOs can do what-if scenario planning of their brand spend to find the maximum amount they can spend in it to drive long-term brand equity while still hitting short-term targets.
For example, one of our customers knew that about 5% of their pipe creation could be explained by spend in their brand efforts. Of course, other channels had a bigger impact on pipe creation. So, the CMO was able to do what-if scenario planning, increasing the brand spend as much as possible until the forecast no longer met the short-term pipe targets. Doing this they were able to balance the two objectives all within the same model.
5. Budget Constraints:
The Challenge:
Limited marketing budgets and the pressure to grow with less present a significant challenge for CMOs. Without clear visibility into the ROI of their marketing investments, CMOs struggle to allocate resources effectively and justify budget allocations. Rules-based attribution models provide no allocation recommendations, so what-if scenario planning becomes a manual spreadsheet process.
The Solution:
B2B media mix models empower CMOs to optimize their budgets with precision and confidence. By conducting scenario planning and forecasting, media mix models enable CMOs to understand the potential outcomes of different budget allocations and make informed decisions to maximize ROI. They can show the CFO what down budgets will do to forecasts and communicate realistic targets based on final budgets.
I’ve seen many models where a down budget still produces a flat to slightly up revenue forecast by pushing money to marketing channels that have a stronger statistical relationship. CMOs can be good team players by finding these opportunities to save money that shouldn’t impact revenue significantly.
6. Speed:
The Challenge:
Let’s be honest, B2B marketing optimization doesn’t move like B2C. But speed is still paramount. CMOs need to communicate the quarterly and annual plans without spending an entire quarter or year making those plans. Attribution models don’t create forward-looking recommendations. They just produce a backwards looking descriptive statistic. This leaves CMOs and their teams to take many steps to convert that descriptive statistic into a “what now” action. I’ve seen this take entire months in prep for quarterly business reviews and entire quarters for annual planning, resulting in MANY sync and planning meetings.
The Solution:
Media mix models provide CMOs with the prescriptive recommendations they need to achieve their most important KPIs. With the ability to do what-if scenario planning with budget allocations and marketing strategies, media mix models enable CMOs to quickly decide what they plan to do differently in the coming quarters and years to ensure their marketing efforts remain relevant and effective.
I used to run the analytics side of this B2B marketing planning process at Adobe. It took days to translate my attribution model to forward looking recommendations. And even then, they were ultimately guesses based on cost-pers. Then if a new budget scenario came our way, I had to rework my spreadsheets. Once I took on media mix modeling, updating scenarios was as simple as entering a new budget value and letting the model refresh. Usually, it was a matter of minutes. In our current solution at Align BI, it’s as simple as toggling a slider to a new budget value.
Conclusion:
Media mix models offer a powerful solution to the many challenges facing CMOs and marketing executives today. There are few tools that can single handedly impact so many areas of a CMO’s life. By quickly producing important KPIs, actionable insights, and optimized budget allocations, media mix models help CMOs increase their confidence with their peers, speed up their decision making, and improve their communication of marketing’s impact. As the marketing landscape continues to evolve, embracing media mix modeling is essential for staying ahead of the curve and unlocking the full potential of marketing ROI.