Unraveling the Marketing Maze

Why MMM is a Marketer's Best Friend

Posted by Florencia Vago

on March 18, 2024 · 4 mins read

There is so much content around Marketing Mix Modeling (MMM), that it took us a minute to consider how best to contribute to the conversation. In this first post, we’ll focus on the problems marketers are facing and which of these challenges MMM can help with.

A snapshot of today’s marketing landscape 📸

Drowning in Data

In today's hyper-competitive landscape, marketers face challenges on multiple fronts. With an ever-increasing number of channels and touchpoints, it's becoming increasingly difficult to understand what's truly driving sales and revenue. Having more data doesn’t instantly translate to easier data-driven decisions. Raise your hand if you can relate 🙋

Starving for Insights 📈

"According to HubSpot’s survey of marketing professionals, more than nine out of ten marketers leverage more than one marketing channel — and 81% leverage more than three channels."¹ With so many channels in play, it's no wonder marketers are struggling to make sense of the data deluge.

But it's not just about the sheer volume of data; it's about extracting meaningful insights from it. Many marketers today find themselves data-rich but insight-poor. This is where MMM shines, helping marketers pinpoint the true drivers of success.

Ads have both short & long-term effects but the latter can be hard to track 📈

While immediate metrics such as click-through rates and conversion rates offer valuable insights into the initial response to an ad, they often fail to capture the enduring effects that ads can have over time. Ads possess both short and long-term effects, influencing brand perception, customer loyalty, and overall brand equity in the long run. However, the inability to measure these long-term effects effectively can lead marketers to overlook the true value and potential of their advertising campaigns.

Marketing is multichannel but measurement metrics are not 📺📱

While the trend has been to shift more spend towards digital channels, offline channels are still very relevant. Unfortunately, a lot of marketers struggle to integrate and compare performance data from different offline and online channels to inform planning and forecasting. Without a way to compare the impact of their different channels and campaigns, it’s challenging to identify the optimal spend for each one and avoid overspending past the point of saturation.

The Budgeting Bottleneck: Justifying Every Dollar 💸

It’s no secret that there is more and more scrutiny over marketing spend, CMOs are under immense pressure to demonstrate ROAS and to identify where spending their advertising dollars will have the most impact on their business goals. “According to Modern's report, driving revenue and short term growth is at the top of the priority list for CMOs in 2024. Nearly 75% of surveyed CMOs cited short-term company commercial growth as their most pressing priority for the next 12-18 months, above longer-term goals. This focus on immediate commercial impact indicates CMOs feel increased pressure from CEOs and boards to demonstrate ROI through metrics like monthly recurring revenue and quarterly sales results.” ²

Understandably, with this increasing pressure to make sense of the diverse data at their disposal, marketers are exploring Martech solutions. Modern’s report also indicated that “37% of CMOs are looking to increase the role of MarTech by expanding stacks, improving capabilities, and closing the skills gap”. ²

One of the Martech solutions that can help marketers address these issues is MMM.

[Refresher] Marketing Mix Modeling is a statistical technique used to analyze and quantify the impact of various marketing activities on sales or other desired outcomes.

So… how does MMM help marketers navigate these modern marketing challenges?

Imagine you're running multiple marketing campaigns simultaneously, such as TV ads, social media promotions, email campaigns, and in-store displays. Marketing Mix Modeling helps you understand how each of these different marketing tactics contributes to your overall sales or revenue.

It can help you answer questions such as:

What is the impact of each channel on a specific KPI such as sales?
What are the long-term brand effects of the ads?
Are you over or underspending on any campaigns?
What is the most efficient way to allocate your marketing budget?

Marketing Mix Modeling vs other measurement models

As if channel fragmentation and increased pressure on budgets weren’t enough, marketers face one more hurdle in their efforts to efficiently allocate and track their budgets: biased attribution.

As marketers grapple with an increasingly complex customer journey, traditional attribution models often fall short. Most marketers believe their attribution data is inaccurate or incomplete, but struggle to establish a single, reliable source of truth.

Most measurement solutions leave marketers struggling with:

Bottom of the funnel bias: Last-click or rules-based attribution usually over-credit channels closer to the bottom of the funnel such as Paid Search and under-credits top-of-funnel like TV.
Privacy regulations restrict user-level attribution: With Apple and Google making changes to protect user privacy, such as the App Tracking Transparency (ATT) protocol enforced with iOS14 and the deprecation of cookies, traditional user-level attribution on online channels is limited.
Siloed solutions: Most models don’t allow marketers to compare the performance of their online and offline marketing channels within a single unified view. This lack of an omnichannel measurement solution prevents marketers from gaining a comprehensive understanding of their overall marketing effectiveness across all touchpoints.

We’re not saying that running MMM will magically solve all your marketing problems, but… it will help you sidestep these limitations. Marketing Mix Modelling considers all touchpoints, both online and offline, and since it is not user-based it is not affected by privacy regulations.

Furthermore, combining MMM with data-based attribution will allow for a holistic view of marketing's contribution and helps resolve the attribution challenge.

TL,DR: By unraveling the complexities of the marketing mix, MMM empowers data-driven decision-making, budget optimization, and a clearer understanding of what truly drives business growth.

Coming soon

In upcoming posts, we’ll cover some of the most frequent questions we receive when chatting with marketers such as:

Does MMM work for every business? What types of businesses or industries benefit the most from Marketing Mix Modelling?
What do advertisers need in order to implement MMM in their marketing stack?
What does the MMM output look like? How can marketers leverage these insights?

And many more. As data nerds, we’ll do our best to answer straightforwardly and without the frills, so stay tuned and if you have any questions for us, don’t hesitate to reach out!