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The 20/80 Rule of Marketing Mix Modelling: Why Your Data Matters More Than You Think

From ChatGPT Prompt to Global Reach: The Story of More Than Data and Minute MMM

<h2>Introduction: When Clients Ask the Tough Questions</h2><p>It started with a phone call. You know, the kind that makes your coffee taste suddenly bitter.</p><p>Our client, a well-known alcohol FMCG brand, had one burning question:</p><p><strong>“We spent a fortune on OOH two months ago. Where’s the laggy effect? Why can’t we see how those giant billboards are still working today? If your marketing science is as good as you say, prove it.”</strong></p><p>Ouch. That one stung. Because honestly, they were right. Traditional Marketing Mix Modelling (MMM) had a bad habit of sweeping OOH into a single “overall” bucket. Useful for quick dashboards, sure, but useless if you actually want to know how a Sydney metro large-format billboard in February is nudging sales in March, or even April.&nbsp;</p><p>That was the punch in the face we needed. Instead of defending the old way, we built something new—a <strong>high-resolution modelling method</strong> designed to track, position, and measure the carry-over and time-decay effect of media spend at a granular level.</p><figure id="figure-c58gggbv7hmfhxadh5"><img id="c58gggbv7hmfhxadh5" src="https://media.gettyimages.com/id/1939988805/photo/an-empty-billboard-stands-on-the-side-of-a-highway-in-a-rural-area-the-billboard-is-large-and.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=7NJUEA-_heeYNh16BQCa3gir5g8sHq3T7lTsezgIclg=" alt="When it comes to roadside OOH, nothing grabs attention like a massive billboard. That’s why most brands turn to large-format OOH to boost awareness and make sure their message can’t be missed. Our client, however, wanted to dig deeper. They asked about OOH billboards in metro city centres, especially those in prime city locations. This request adds an extra layer of granularity and challenge to the modelling project, since urban billboards often require more precise measurement of audience reach and effectiveness" title="When it comes to roadside OOH, nothing grabs attention like a massive billboard. That’s why most brands turn to large-format OOH to boost awareness and make sure their message can’t be missed. Our client, however, wanted to dig deeper. They asked about OOH billboards in metro city centres, especially those in prime city locations. This request adds an extra layer of granularity and challenge to the modelling project, since urban billboards often require more precise measurement of audience reach and effectiveness" class="object-cover bg-gray-100 " style="aspect-ratio: 3/2; object-position: center center;" data-corners="default" data-aspect="3:2" data-caption="Large-format roadside out-of-home (OOH) advertising is one of the most eye-catching ways to capture attention. Many brands rely on these billboards to create strong brand awareness and stand out in crowded markets. In this case, the client raised specific questions about metro city OOH billboards located in high-traffic urban areas. This makes the marketing mix modelling project more granular and complex, as it requires analysing detailed local exposure and measuring the real impact on brand visibility." data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://media.gettyimages.com/id/1939988805/photo/an-empty-billboard-stands-on-the-side-of-a-highway-in-a-rural-area-the-billboard-is-large-and.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=7NJUEA-_heeYNh16BQCa3gir5g8sHq3T7lTsezgIclg=" data-mce-style="aspect-ratio: 3/2; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">Large-format roadside out-of-home (OOH) advertising is one of the most eye-catching ways to capture attention. Many brands rely on these billboards to create strong brand awareness and stand out in crowded markets. In this case, the client raised specific questions about metro city OOH billboards located in high-traffic urban areas. This makes the marketing mix modelling project more granular and complex, as it requires analysing detailed local exposure and measuring the real impact on brand visibility.</figcaption></figure><h2>Why We Needed a New MMM Method</h2><h3>From Client Complaints to Innovation</h3><p>Our client’s frustration wasn’t unique. Brands everywhere are asking:</p><ul><li>Which exact OOH placements are working?<br></li><li>How long does their effect really last?<br></li><li>Does a February campaign in Sydney still echo in April’s sales numbers?<br></li></ul><p>It wasn’t enough to say “OOH works overall.” Clients wanted proof, broken down, geo by geo, board by board, month by month.</p><p>And frankly, if MMM couldn’t answer those questions, why call it marketing science?</p><h3>The Four Big Challenges We Faced</h3><p>Building a new MMM method wasn’t just flipping a switch. It came with four main hurdles.</p><p><strong>1. Granular Data Collection</strong></p><p>We had to track not just “OOH spend” but what kind of OOH, in which geo, and at what time. Shopping-centre ads, street furniture, large-format billboards—they all needed to be separated, labelled, and tied to sales data in matching geographies.</p><p><strong>2. Data Processing and Labelling</strong></p><p>Here’s where it gets tricky. It’s not enough to know an ad existed. We had to label:</p><ul><li>Which OOH did what<br></li><li>Where it appeared<br></li><li>When it ran</li></ul><p>Without this, you’re just staring at a blurry mess of numbers that could never answer the client’s questions.</p><p><strong>3. Adstocking Transformation</strong></p><p>Ads don’t work like instant noodles—you don’t just “add spend and get sales.” They linger. They fade. Different channels decay at different rates.</p><p>OOH tends to hang around in people’s heads longer than, say, a digital display banner. To model this, we used adstock transformations (fancy math functions that simulate carry-over and time-decay).</p><p>The kicker? Choosing the right function and fine-tuning parameters is a lot of work. Too much manual tweaking, and you’ll lose a week of your life.</p><p><strong>4. Constrained Modelling</strong></p><p>Finally, we had to make sure the sum of all these new granular OOH contributions still added up to the original “total OOH” from the old model. Otherwise, clients would think we were cooking the books.</p><p>No one wants to see a Sydney billboard magically explaining 10% of national sales when its spend share was only 3%. That’s too good to be true—and we all know what happens when clients smell “too good to be true.”</p><figure id="figure-0on1evusbmfhxiugv"><img id="0on1evusbmfhxiugv" src="https://cdn.durable.co/blocks/81lAnw4H2wRago3CfSQ2EWrixk3RutRSRFu8SYvHkOCisRkWj38rvP5pgPriCt6A.png" alt="Here’s an example of how geometric adstock transformation works on weekly OOH ad spends. This approach uses just one key parameter—the decay rate—to model how ads linger in audience memory. On the chart, the blue line shows the original OOH spends, while the red line highlights the carry-over and time-decay effect, making it clear how advertising impact extends beyond the week it ran" title="Here’s an example of how geometric adstock transformation works on weekly OOH ad spends. This approach uses just one key parameter—the decay rate—to model how ads linger in audience memory. On the chart, the blue line shows the original OOH spends, while the red line highlights the carry-over and time-decay effect, making it clear how advertising impact extends beyond the week it ran" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="This example demonstrates how adstock transformation is applied to weekly OOH advertising spends. The adstock method used here is a geometric function, which relies on a single parameter known as the decay rate. In the chart, the blue line represents the raw weekly OOH spends, while the red line illustrates the carry-over and time-decay effect of the ads, showing how past advertising continues to influence audience exposure over time." data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/81lAnw4H2wRago3CfSQ2EWrixk3RutRSRFu8SYvHkOCisRkWj38rvP5pgPriCt6A.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">This example demonstrates how adstock transformation is applied to weekly OOH advertising spends. The adstock method used here is a geometric function, which relies on a single parameter known as the decay rate. In the chart, the blue line represents the raw weekly OOH spends, while the red line illustrates the carry-over and time-decay effect of the ads, showing how past advertising continues to influence audience exposure over time.</figcaption></figure><h2>Our New High-Resolution MMM Method</h2><p>Here’s how <strong>More Than Data</strong> cracked it.</p><h3>Step 1: Collecting and Splitting the Data</h3><p>We gathered spend data by OOH type, geo, and time. Sales KPIs were split the same way. If a customer bought in Sydney, that purchase was attributed back to Sydney’s OOH campaigns—not Melbourne or Brisbane.</p><h3>Step 2: Smart Data Processing</h3><p>We structured the data in a wide-format table, with columns for each OOH type and spend. Add in date and geo-market columns, align them perfectly with KPIs, and voilà: we had a dataset ready for high-resolution modelling.</p><h3>Step 3: High-Resolution Adstock Algorithm</h3><p>Instead of manually tuning 38 OOH variables (yes, 38), we built a self-tuning adstock algorithm. It automatically adjusts decay parameters by following the sales pattern.</p><p>Result? No late-night coffee-fuelled parameter tweaking. Just clean, data-driven simulations of how long each campaign carried over.</p><h3>Step 4: Constrained Modelling</h3><p>We fed the adstocked data into <a data-mce-href="https://morethandata.biz/blog/upgrading-google-meridian--a-constrained-bayesian-approach-for-robust-marketing-mix-modelling" href="https://morethandata.biz/blog/upgrading-google-meridian--a-constrained-bayesian-approach-for-robust-marketing-mix-modelling" target="_blank" rel="noopener"><strong>our constrained Bayesian modelling engine</strong></a>. This ensured:</p><ul><li>Granular OOH variables added up to the total OOH share.<br></li><li>Contribution shares stayed in line with spend shares.<br></li><li>The math was transparent, defensible, and client-ready.<br></li></ul><p>The following table displays specific OOH advertising types alongside their corresponding adstock transformation parameters. In this example, we apply a geometric adstock function with a single parameter, the decay rate. Note that different OOH types may require different decay rates, reflecting variations in carry-over and time-decay effects across ad formats.</p><table style="border-collapse: collapse; width: 100%;" border="1" data-mce-selected="1" data-mce-style="border-collapse: collapse; width: 100%;"><tbody><tr><td style="width: 25%;" data-mce-style="width: 25%;"><strong>Media&nbsp;</strong></td><td style="width: 25%;" data-mce-style="width: 25%;"><strong>Specific Type</strong></td><td style="width: 25%;" data-mce-style="width: 25%;"><strong>Decay Rate Lower Bound</strong></td><td style="width: 25%;" data-mce-style="width: 25%;"><strong>Decay Rate Higher Bound</strong></td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Programmatic</td><td style="width: 25%;" data-mce-style="width: 25%;">0.5</td><td style="width: 25%;" data-mce-style="width: 25%;">0.61</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Large Format</td><td style="width: 25%;" data-mce-style="width: 25%;"><p>0.72</p></td><td style="width: 25%;" data-mce-style="width: 25%;">0.8</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Retail</td><td style="width: 25%;" data-mce-style="width: 25%;">0.56</td><td style="width: 25%;" data-mce-style="width: 25%;">0.67</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Running Boards</td><td style="width: 25%;" data-mce-style="width: 25%;">0.56</td><td style="width: 25%;" data-mce-style="width: 25%;">0.67</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Airport</td><td style="width: 25%;" data-mce-style="width: 25%;">0.63</td><td style="width: 25%;" data-mce-style="width: 25%;">0.77</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Digital Panel</td><td style="width: 25%;" data-mce-style="width: 25%;">0.53</td><td style="width: 25%;" data-mce-style="width: 25%;">0.68</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Other</td><td style="width: 25%;" data-mce-style="width: 25%;">0.6</td><td style="width: 25%;" data-mce-style="width: 25%;">0.7</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Stadium Signage</td><td style="width: 25%;" data-mce-style="width: 25%;">0.67</td><td style="width: 25%;" data-mce-style="width: 25%;">0.83</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Street Furniture</td><td style="width: 25%;" data-mce-style="width: 25%;">0.61</td><td style="width: 25%;" data-mce-style="width: 25%;">0.74</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Transit</td><td style="width: 25%;" data-mce-style="width: 25%;">0.61</td><td style="width: 25%;" data-mce-style="width: 25%;">0.74</td></tr><tr><td style="width: 25%;" data-mce-style="width: 25%;">OOH</td><td style="width: 25%;" data-mce-style="width: 25%;">Workplace</td><td style="width: 25%;" data-mce-style="width: 25%;">0.61</td><td style="width: 25%;" data-mce-style="width: 25%;">0.74</td></tr></tbody></table><h2>Case Study: The Alcohol FMCG Brand</h2><p>Let’s circle back to our client.</p><p>First, we gave them the old MMM report: one big “overall OOH” line item. They weren’t impressed.</p><p>Then, we reran the model with our new method. Suddenly, we could show:</p><ul><li>Sydney metro large-format OOH from February impacted March and April sales.<br></li><li>Shopping-centre OOH had shorter carry-over, fading quicker.<br></li><li>Street furniture played a supporting role, nudging awareness in local neighbourhoods.</li></ul><p>The client’s reaction? Relief. Finally, they could see which placements were worth the money, and how long the effects lasted.</p><p>It wasn’t just about keeping the client happy. It was a technical breakthrough that turned frustration into innovation.</p><h2>Why This Matters for the Future of MMM</h2><p>High-resolution MMM isn’t just a shiny toy. It’s a survival tool.</p><ul><li><strong>For brands</strong>: It answers the tough questions about spend effectiveness.<br></li><li><strong>For agencies</strong>: It builds trust and avoids those painful “why can’t you show me?” conversations.<br></li><li><strong>For MMM itself</strong>: It proves we can evolve, adapt, and stay relevant in a world demanding more transparency.</li></ul><figure id="figure-t0vwignd6rmfhy625o"><img id="t0vwignd6rmfhy625o" src="https://media.gettyimages.com/id/892387598/photo/liquor-store-sign.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=eir8pdIWO6SH8JA6I65DMTQtn8ngFtMd2NnFOQkg_O8=" alt="The Alcohol FMCG brand can be reassured, as every question around their OOH ads—from type and location to timing, spend, and sales attribution—has been clearly answered. Using our high-resolution MMM method, we go beyond standard analysis to satisfy the client’s granular demands, showing that More Than Data is always ready to help, guide, and deliver results they can trust" title="The Alcohol FMCG brand can be reassured, as every question around their OOH ads—from type and location to timing, spend, and sales attribution—has been clearly answered. Using our high-resolution MMM method, we go beyond standard analysis to satisfy the client’s granular demands, showing that More Than Data is always ready to help, guide, and deliver results they can trust" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="he Alcohol FMCG brand can now be confident, as all concerns and uncertainties regarding their OOH advertising—including ad type, geographic location, timing, spend, and attributed sales measurement—have been fully addressed. By leveraging our high-resolution Marketing Mix Modelling (MMM) approach, we not only meet the client’s detailed and granular requirements but also demonstrate that More Than Data consistently provides reliable support and actionable insights." data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://media.gettyimages.com/id/892387598/photo/liquor-store-sign.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=eir8pdIWO6SH8JA6I65DMTQtn8ngFtMd2NnFOQkg_O8=" data-mce-style="aspect-ratio: 16/9; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">he Alcohol FMCG brand can now be confident, as all concerns and uncertainties regarding their OOH advertising—including ad type, geographic location, timing, spend, and attributed sales measurement—have been fully addressed. By leveraging our high-resolution Marketing Mix Modelling (MMM) approach, we not only meet the client’s detailed and granular requirements but also demonstrate that More Than Data consistently provides reliable support and actionable insights.</figcaption></figure><h2>Conclusion: Punches Can Be Good for You</h2><p>Getting called out by a client hurts. But sometimes, that’s the best thing that can happen.</p><p>Their questions pushed us to move beyond “overall OOH” into a world of granular, trackable, position-able media measurement.</p><p><strong>Now, when clients ask, “Can you prove those billboards are working?”</strong></p><p><strong>We don’t flinch. We show them the numbers.</strong></p><p>And if you’re ready to move past the blurry “overall” metrics into sharp, high-resolution marketing science—well, <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" rel="noopener"><strong>More Than Data</strong></a> is here for you.</p>

Cracking the Code of OOH: How High-Resolution MMM Finally Solved the Carry-Over Mystery

Marketing Mix Modelling Meets MTA: A New Approach to Customer Journey Mapping

<h2>Introduction to the 4 Ps of Marketing</h2>

<p>When it comes to crafting successful digital marketing campaigns, understanding the fundamental principles of marketing is crucial. At the heart of these principles lie the 4 Ps of Marketing: Product, Price, Place, and Promotion. These elements serve as the cornerstone of any marketing strategy, providing a comprehensive framework for marketers to effectively reach their target audience and achieve their business objectives.</p>

<p>The digital landscape has transformed how these elements are applied, offering new opportunities and challenges. This post delves into how the 4 Ps adapt and function within digital campaigns.</p>

<figure id="figure-3tl15j4e3kmfd6m0lk"><img id="3tl15j4e3kmfd6m0lk" src="https://media.gettyimages.com/id/2204690878/photo/marketing-team-analyzing-world-map-puzzle-during-brainstorming-session.jpg?b=1&s=2048x2048&w=0&k=20&c=ERw6PnR9Wc_igryiKIrdQa7pQ1-DI29v8g8MqVo2oPM=" alt="marketing campaign" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Product: Tailoring Offerings for Digital Platforms</h2>

<p>The first P, Product, involves the goods or services that a company offers to its customers. In digital marketing, this extends beyond physical products to include digital products such as software, e-books, and online courses. Understanding your product's unique selling propositions (USPs) and how they fit into the digital marketplace is essential.</p>

<p>Digital platforms allow for greater customization and personalization, enabling businesses to tailor their products to meet specific customer needs. This means leveraging data analytics to refine product offerings and improve customer satisfaction continuously.</p>

<h3>Considerations for Product Development</h3>

<ul>
    <li>Identify customer needs through online surveys and feedback.</li>
    <li>Utilize A/B testing to determine which product variations perform best.</li>
    <li>Ensure easy accessibility and user-friendly experiences for digital products.</li>
</ul>

<figure id="figure-f51cj03idmfd6m0lk"><img id="f51cj03idmfd6m0lk" src="https://media.gettyimages.com/id/2204690878/photo/marketing-team-analyzing-world-map-puzzle-during-brainstorming-session.jpg?b=1&s=2048x2048&w=0&k=20&c=ERw6PnR9Wc_igryiKIrdQa7pQ1-DI29v8g8MqVo2oPM=" alt="product development" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Price: Strategies for Competitive Advantage</h2>

<p>Price is a critical component of any marketing strategy, directly influencing consumer purchasing decisions. In the digital marketplace, pricing strategies can be more dynamic and competitive. Businesses can employ techniques such as competitive pricing, psychological pricing, and freemium models to attract and retain customers.</p>

<p>Additionally, digital campaigns can leverage real-time data to adjust prices based on demand, competitor actions, and market conditions. This flexibility allows businesses to remain competitive and maximize profitability.</p>

<h3>Effective Pricing Tactics</h3>

<ol>
    <li>Conduct thorough market research to understand pricing trends.</li>
    <li>Utilize promotional discounts and offers strategically to drive sales.</li>
    <li>Monitor competitor pricing and adjust accordingly.</li>
</ol>

<figure id="figure-ug8j4smbjnmfd6m0lk"><img id="ug8j4smbjnmfd6m0lk" src="https://media.gettyimages.com/id/2213220847/photo/pricing-strategy-analysis-and-business-planning-concept-businessperson-working-on-pricing.jpg?b=1&s=2048x2048&w=0&k=20&c=4GJnxtO-_nGxH6pK-2BB6GS63M3lS6FSfFPUaldVoEg=" alt="pricing strategy" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Place: Optimizing Distribution Channels</h2>

<p>The P of Place refers to the distribution channels through which a product reaches the consumer. In digital marketing, this encompasses online platforms such as e-commerce websites, social media channels, and mobile apps. Selecting the right channels is vital for reaching your target audience effectively.</p>

<p>Understanding where your audience spends their time online allows you to optimize your digital presence and ensure your products are accessible to potential customers. This means leveraging search engine optimization (SEO) strategies and targeted advertising to enhance visibility.</p>

<h3>Selecting the Right Channels</h3>

<ul>
    <li>Analyze consumer behavior data to identify popular platforms among your target audience.</li>
    <li>Utilize a mix of owned, paid, and earned media channels for a balanced approach.</li>
    <li>Regularly assess channel performance and adapt strategies as needed.</li>
</ul>

<h2>Promotion: Crafting Impactful Campaigns</h2>

<p>The final P, Promotion, involves the tactics used to communicate with potential customers about your product. In the digital realm, promotion extends beyond traditional advertising methods to include social media marketing, email campaigns, content marketing, and influencer partnerships.</p>

<p>Creating engaging content that resonates with your audience is vital. This requires a deep understanding of your audience's preferences and behaviors. Additionally, leveraging data analytics can help refine promotional strategies and measure the effectiveness of campaigns.</p>

<figure id="figure-6og2dtd1srhmfd6m0lk"><img id="6og2dtd1srhmfd6m0lk" src="https://media.gettyimages.com/id/2171092251/photo/digital-marketing-commerce-online-sale-concept-businessman-using-laptop-with-ads-dashboard.jpg?b=1&s=2048x2048&w=0&k=20&c=z0ZWuhBgjkKR89tT-1wW61oWSktDeSScSlp07fN1wqg=" alt="digital advertising" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h3>Enhancing Promotional Efforts</h3>

<ol>
    <li>Create targeted content that addresses specific customer pain points.</li>
    <li>Leverage automation tools to streamline promotional activities.</li>
    <li>Continuously monitor campaign performance and make data-driven adjustments.</li>
</ol>

<h2>Conclusion: Integrating the 4 Ps in Digital Marketing</h2>

<p>Understanding and effectively integrating the 4 Ps of Marketing in digital campaigns is essential for businesses looking to thrive in today's competitive landscape. By focusing on Product, Price, Place, and Promotion, marketers can create comprehensive strategies that resonate with their audience and drive success.</p>

<p>The digital world offers endless opportunities for innovation and expansion. By thoughtfully applying these principles, businesses can enhance their marketing efforts and achieve lasting results in an ever-evolving marketplace.</p>

Understanding the 4 Ps of Marketing in Digital Campaigns

<h2>Introduction: A Real Story Behind the Numbers</h2><p>Not long ago, one of our media agency clients reached out with a curious inquiry while using Minute MMM, our self-service marketing mix modelling (MMM) SaaS platform.</p><p>This agency had been exploring the tool for some time and genuinely appreciated its simplicity, flexibility, and the control it gave them over their own marketing data. <strong>They described it as “handy, easy-to-use, and surprisingly adjustable.”</strong></p><p>But during one of their experiments, something fascinating happened: they adjusted the settings so that<strong> nearly every media channel contributed 100% impact to sales outcomes.</strong></p><p>On the surface, it looked like a confidence move. But in reality, it opened the door to an important conversation about what MMM is, what it is not, and how agencies and brands can use it responsibly.</p><p>This article will take you through that story, what it reveals about MMM as a methodology, and the bigger lessons for both media agencies and brands.</p><figure id="figure-lju95zagnmmfb3w62e"><img id="lju95zagnmmfb3w62e" src="https://media.gettyimages.com/id/2185900505/photo/funny-surprised-looking-man.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=KaDT8_-2ohm4Xfj-JE1SMu1EyOwteBr9648jZQ_zyq4=" alt="Reviewing the user’s screenshot, I was stunned to see almost all media variable impacts set to 100%. In marketing mix modelling, this kind of assumption can be alarming, because it ignores the reality that no single channel—or even all channels together—can realistically account for 100% of business outcomes" title="Reviewing the user’s screenshot, I was stunned to see almost all media variable impacts set to 100%. In marketing mix modelling, this kind of assumption can be alarming, because it ignores the reality that no single channel—or even all channels together—can realistically account for 100% of business outcomes" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: undefined undefined;" data-corners="default" data-aspect="16:9" data-caption="When I first saw the screenshot from the user’s MMM setup—where nearly every media variable impact was set to 100%—I was genuinely shocked. It was the kind of moment that makes your jaw drop, because no realistic marketing mix modelling scenario should ever assume every channel drives 100% of results." data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://media.gettyimages.com/id/2185900505/photo/funny-surprised-looking-man.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=KaDT8_-2ohm4Xfj-JE1SMu1EyOwteBr9648jZQ_zyq4=" data-mce-style="aspect-ratio: 16/9; object-position: undefined undefined;"><figcaption class="body-normal text-gray-500 mt-2">When I first saw the screenshot from the user’s MMM setup—where nearly every media variable impact was set to 100%—I was genuinely shocked. It was the kind of moment that makes your jaw drop, because no realistic marketing mix modelling scenario should ever assume every channel drives 100% of results.</figcaption></figure><h2>What Makes Minute MMM Different</h2><p>Before diving into the specifics, let’s set the stage.</p><p>Minute MMM is designed as a self-service MMM tool that empowers marketers and agencies to measure and optimise their media investments without needing a PhD in data science.</p><p>One of its key features is a customisable setting that allows users to define their expectations about media variables and their impact on key performance indicators (KPIs).</p><p>In practice, this means:</p><ul><li>If you believe search contributes 10% to your sales, you can set it that way.<br></li><li>If you’re uncertain, you can leave the system to provide a model-driven suggestion.</li></ul><p>This flexibility is a powerful way to bridge data with human judgment and domain expertise. But it also brings responsibility.</p><h2>The Reality Check: MMM Has No “Ground Truth”</h2><p>One of the most important lessons in marketing science is this: <strong>MMM does not come with a built-in ground truth.</strong></p><p>Unlike a physics experiment where gravity always pulls at 9.8 m/s², marketing systems are messy, interconnected, and ever-changing.</p><p>MMM works by creating a statistical approximation of reality. It can be shaped by:</p><ul><li>The quality of input data<br></li><li>The assumptions you make<br></li><li>The expectations you set</li></ul><p>That’s why the customisable expectations in Minute MMM directly reflect the truth of the discipline: <strong>MMM can be anything you make it.</strong></p><p>And that’s both empowering and risky.</p><figure id="figure-472atrrndmfb42gxi"><img id="472atrrndmfb42gxi" src="https://cdn.durable.co/blocks/1aDkSMTXAdxE0CXtV1F9ZZo2yeguSZVpHkPLgnxULiDpSwsQVMKMr0t33FrGvPJf.png" alt="In the screenshot shared by my Minute MMM user, the media variable expected impact shares appear unusually elevated, with several values nearly touching 100%. This highlights a common challenge in marketing mix modelling: setting assumptions too high can create misleading insights about media performance" title="In the screenshot shared by my Minute MMM user, the media variable expected impact shares appear unusually elevated, with several values nearly touching 100%. This highlights a common challenge in marketing mix modelling: setting assumptions too high can create misleading insights about media performance" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: 100% 45%;" data-corners="default" data-aspect="16:9" data-caption="This is the screenshot I received from the Minute MMM user—showing media variable expected impact shares set unreasonably high, in some cases even reaching 100%. In marketing mix modelling, such extreme assumptions can distort results and lead to unrealistic outcome." data-positionx="100%" data-positiony="45%" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/1aDkSMTXAdxE0CXtV1F9ZZo2yeguSZVpHkPLgnxULiDpSwsQVMKMr0t33FrGvPJf.png" data-mce-style="aspect-ratio: 16/9; object-position: 100% 45%;"><figcaption class="body-normal text-gray-500 mt-2">This is the screenshot I received from the Minute MMM user—showing media variable expected impact shares set unreasonably high, in some cases even reaching 100%. In marketing mix modelling, such extreme assumptions can distort results and lead to unrealistic outcome.</figcaption></figure><h2>Why People Think MMM Is a “Magic Box”</h2><p>Many marketers and even seasoned agencies fall into a common trap: they treat MMM as a black box.</p><p>The thinking goes like this:</p><ul><li>Feed in your marketing spend data.<br></li><li>Press the button.<br></li><li>Out comes the “truth” about media effectiveness.<br></li></ul><p>But that’s not how it works. MMM is not a vending machine that returns the answer you desire. It is a modelling approach that requires careful interpretation, judgment, and sometimes, humility.</p><p>When our agency client set every media channel to 100%, it wasn’t a failure. It was a reminder of how easy it is to slip into the mindset of “the model will prove whatever I need it to prove.”</p><h2>The 100% Setting: What It Tells Us</h2><p>So why would someone set every channel to 100%?</p><p>There are several possible reasons:</p><ul><li><strong>Optimism bias</strong>: Believing that every channel works equally well.<br></li><li><strong>Pressure</strong>: Agencies often need to prove their value to clients.<br></li><li><strong>Misunderstanding</strong>: Confusing potential impact with guaranteed impact.<br></li></ul><p>Whatever the motivation, the result highlights a knowledge gap. No media channel can realistically be responsible for 100% of sales.</p><p>This is not just an academic point. It has real consequences.</p><figure id="figure-wl3lidhnebmfb4bi9h"><img id="wl3lidhnebmfb4bi9h" src="https://cdn.durable.co/blocks/fGFJFNHcBcYntRa3USsNLMcHqqPJPQsjICwGRaQ3caEDZGs8zG2D1JQbVOO3M6C4.png" alt="The KPI sales decomposition from this marketing mix modelling (MMM) output highlights the impact of each media channel. When nearly all media variables are set to extremely high levels or 100%, the organic base (black bar) is pushed into negative territory, which defies realistic marketing science principles. In MMM, the organic base reflects natural, ad-free sales growth, and it cannot be negative for actual sales KPIs" title="The KPI sales decomposition from this marketing mix modelling (MMM) output highlights the impact of each media channel. When nearly all media variables are set to extremely high levels or 100%, the organic base (black bar) is pushed into negative territory, which defies realistic marketing science principles. In MMM, the organic base reflects natural, ad-free sales growth, and it cannot be negative for actual sales KPIs" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: 100% 50%;" data-corners="default" data-aspect="16:9" data-caption="This is the modelling output showing KPI sales decomposition by individual media channels. Because almost all media channels were set very high—or even 100%—the organic base (represented by the black bar) becomes negative, which is unrealistic. In marketing mix modelling, the organic base represents natural sales growth without advertising influence, and for KPI = sales, it can never be negative." data-positionx="100%" data-positiony="50%" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/fGFJFNHcBcYntRa3USsNLMcHqqPJPQsjICwGRaQ3caEDZGs8zG2D1JQbVOO3M6C4.png" data-mce-style="aspect-ratio: 16/9; object-position: 100% 50%;"><figcaption class="body-normal text-gray-500 mt-2">This is the modelling output showing KPI sales decomposition by individual media channels. Because almost all media channels were set very high—or even 100%—the organic base (represented by the black bar) becomes negative, which is unrealistic. In marketing mix modelling, the organic base represents natural sales growth without advertising influence, and for KPI = sales, it can never be negative.</figcaption></figure><h2>The Risks of Unrealistic Assumptions</h2><p>When assumptions don’t align with reality, two risks emerge:</p><h3>1. Business Risk</h3><p>If a marketer or agency claims that one or more media channels deliver 100% of the sales, they create unrealistic expectations.</p><p>When the numbers inevitably fall short, the client relationship is strained. Trust is eroded. And in the worst cases, business partnerships collapse.</p><h3>2. Reputation Risk</h3><p>Agencies want to be seen as credible, trusted partners. But setting media impacts to extreme, unrealistic levels can make them look disconnected from reality.</p><p>Instead of being celebrated for hard work, they risk being questioned—or even replaced.</p><h2>The Critical Role of Judgment</h2><p>That’s why <strong>critical thinking is essential when using self-service MMM tools.</strong></p><p>Every media assumption should be:</p><ul><li><strong>Justified with reasoning or evidence.</strong><br></li><li><strong>Grounded in business context.</strong><br></li><li><strong>Flexible enough to adapt when data tells a different story.</strong><br></li></ul><p>The role of MMM is not to flatter existing beliefs, but to challenge and refine them.</p><figure id="figure-fl3xiyjm3vmfb4vva2"><img id="fl3xiyjm3vmfb4vva2" src="https://cdn.durable.co/blocks/2fzPu7FeBlA18RTJRinkcjLTVqvY1TKETqwoQU8Oo6njzHb4BsdCGpEAEUgoaiTr.png" alt="The share of spend compared to the share of media contribution indicates an exceptionally high ROI. Even with minimal budget spent on certain media channels, the reported impact seems 10x greater than expected, which is a clear red flag in marketing mix modelling, as results this extreme are unlikely to be realistic" title="The share of spend compared to the share of media contribution indicates an exceptionally high ROI. Even with minimal budget spent on certain media channels, the reported impact seems 10x greater than expected, which is a clear red flag in marketing mix modelling, as results this extreme are unlikely to be realistic" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: 100% undefined%;" data-corners="default" data-aspect="16:9" data-caption="This analysis of share of spend versus share of media contribution reveals an unbelievably high return on investment. Despite a limited budget allocated to the media, it appears to generate a tenfold impact—an outcome that is far beyond what’s realistically achievable in marketing mix modelling." data-positionx="100%" data-positiony="undefined%" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/2fzPu7FeBlA18RTJRinkcjLTVqvY1TKETqwoQU8Oo6njzHb4BsdCGpEAEUgoaiTr.png" data-mce-style="aspect-ratio: 16/9; object-position: 100% undefined%;"><figcaption class="body-normal text-gray-500 mt-2">This analysis of share of spend versus share of media contribution reveals an unbelievably high return on investment. Despite a limited budget allocated to the media, it appears to generate a tenfold impact—an outcome that is far beyond what’s realistically achievable in marketing mix modelling.</figcaption></figure><h2>Independent Validation: Why Brands Look Elsewhere</h2><p>In past articles, we’ve written about how brands often seek third-party MMM vendors to validate or challenge the insights provided by their media agencies.</p><p>These articles discuss how brands’ trust can erode when media metrics are tracked and measured improperly, often resulting in wasted marketing budgets and disappointing outcomes.</p><p><em><a data-mce-href="https://morethandata.biz/blog/from-radio-waves-to-landing-pages--measuring-2gb-radio-ads-with-google-analytics-for-a-sydney-apartment-launch" href="https://morethandata.biz/blog/from-radio-waves-to-landing-pages--measuring-2gb-radio-ads-with-google-analytics-for-a-sydney-apartment-launch" target="_blank" rel="noopener">From Radio Waves to Landing Pages: Measuring 2GB Radio Ads with Google Analytics for a Sydney Apartment Launch</a></em></p><p><em><a data-mce-href="https://morethandata.biz/blog/the--10-million-lesson--when--promising-media-performance--masks-a-revenue-disaster" href="https://morethandata.biz/blog/the--10-million-lesson--when--promising-media-performance--masks-a-revenue-disaster" target="_blank" rel="noopener">The $10 Million Lesson: When "Promising Media Performance" Masks a Revenue Disaster</a></em></p><p><em><a data-mce-href="https://morethandata.biz/blog/the-pitfalls-of-vanity-metrics--how-an-online-flower-brand-wasted--500-000-on-misguided-marketing" href="https://morethandata.biz/blog/the-pitfalls-of-vanity-metrics--how-an-online-flower-brand-wasted--500-000-on-misguided-marketing" target="_blank" rel="noopener">The Pitfalls of Vanity Metrics: How an Online Flower Brand Wasted $500,000 on Misguided Marketing</a></em></p><p>This isn’t because they distrust agencies outright. Rather, it’s because they need reassurance that the story they’re being told matches a more neutral, independent perspective.</p><p>By turning to external providers, brands gain:</p><ul><li><strong>Clarity </strong>– a second opinion that either confirms or corrects assumptions.<br></li><li><strong>Transparency </strong>– insight into the logic behind the numbers.<br></li><li><strong>Confidence </strong>– the assurance that investment decisions are based on more than just optimistic reporting.<br></li></ul><h2>Agencies as Heroes, Not Victims</h2><p>The point here is not to criticise agencies. In fact, it’s the opposite.</p><p>We want agencies to be seen as heroes of the media world—proving impact, demonstrating value, and earning the trust of the brands they work with.</p><p>MMM, when used responsibly, can be the tool that makes this possible. It provides the data backbone that shows a brand:</p><ul><li>“Here’s where your marketing spend really makes a difference.”<br></li><li>“Here’s why the work we’re doing is driving results.”<br></li><li>“Here’s how we can optimise for even greater growth.”</li></ul><figure id="figure-627k7xiwmdimfb50f67"><img id="627k7xiwmdimfb50f67" src="https://media.gettyimages.com/id/2198405992/photo/confident-business-superhero-man-in-cape-and-mask-giving-thumbs-up.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=Mv7N0erF44npBdKgMUHk3Qjwwgfcbuu-ROaJapiM6Lw=" alt="Media agencies have the potential to be heroes by effectively planning, trading, and measuring ad campaigns. To achieve this, they must rely on accurate marketing mix modelling (MMM), proper tools, and realistic assumptions—ensuring their efforts truly deliver measurable impact" title="Media agencies have the potential to be heroes by effectively planning, trading, and measuring ad campaigns. To achieve this, they must rely on accurate marketing mix modelling (MMM), proper tools, and realistic assumptions—ensuring their efforts truly deliver measurable impact" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="Media agencies can become heroes when their advertising campaigns are carefully planned, executed, and measured. However, this success depends on using the right tools and making assumptions grounded in reality—without proper support, even the best campaigns can fall short." data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://media.gettyimages.com/id/2198405992/photo/confident-business-superhero-man-in-cape-and-mask-giving-thumbs-up.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=Mv7N0erF44npBdKgMUHk3Qjwwgfcbuu-ROaJapiM6Lw=" data-mce-style="aspect-ratio: 16/9; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">Media agencies can become heroes when their advertising campaigns are carefully planned, executed, and measured. However, this success depends on using the right tools and making assumptions grounded in reality—without proper support, even the best campaigns can fall short.</figcaption></figure><h2>A Shared Mission: Supporting Agencies and Brands Alike</h2><p>At More Than Data, our mission is not to take sides. Whether you are a media agency or a brand/SME, we are here to support you.</p><ul><li>For agencies, we provide a platform to prove the value of your work.<br></li><li>For brands, we offer a transparent, independent measure of media effectiveness.</li></ul><p><strong>Ultimately, both sides want the same thing: clarity, confidence, and business growth.</strong></p><h2>Key Lessons From This Story</h2><p>This agency’s journey with the 100% setting wasn’t a mistake—it was a learning opportunity. From it, we can extract three big lessons:</p><ul><li><strong>MMM is not a magic box.</strong> It requires thoughtful setup and critical thinking.<br></li><li><strong>Assumptions matter.</strong> Setting unrealistic expectations can harm trust and credibility.<br></li><li><strong>Transparency builds relationships.</strong> Independent validation strengthens both agencies and brands.<br></li></ul><h2>Conclusion: Facing Reality, Building Trust</h2><p>Marketing is complex. Media impact is rarely clear-cut. And no model, however advanced, can replace the need for sound judgment and honest communication.</p><p>When used responsibly, MMM is not just a measurement tool—it’s a bridge of trust between agencies and brands.</p><p>That’s why at More Than Data, we celebrate both the curiosity of agencies experimenting with our platform and the brands who seek clarity. Together, we can create a marketing ecosystem where insights are realistic, investments are transparent, and growth is shared.</p>

Marketing Mix Modelling Is Not a Magic Box: Lessons From a Media Agency’s Journey With Minute MMM

More Than Data

An Australia Sydney-based pioneer in marketing analytics, offering a free, fast, and user-friendly marketing mix modelling platform. We help marketers build actionable marketing mix models in under 10 minutes for instant insights. Our software Minute MMM is free, DIY, and simple—no costly consultants, complex tools, or data expertise needed. Optimize marketing investments with ease!

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