Blog

<h3>The Beginning: Parallel Lines</h3>For years, one of our founders worked in the media industry, sitting right next to a media planner. Day in and day out, they shared the same office space, breathing the same recycled air, and yet, their worlds couldn’t have been more different. It was a relationship defined by routine but not by connection—until time had its way of bringing them together.<h3>“What Are You Doing?”</h3>As a marketing analytics professional inside a media agency, our founder’s computer screen was always in view of his media-planning desk neighbor. One day, curiosity (or perhaps sheer frustration) got the better of the planner.Media Planner: “What the hell is that on your screen?”&nbsp;Data Scientist: “It’s coding.”&nbsp;Media Planner: “Why are you coding?”&nbsp;Data Scientist: “I’m analyzing last quarter’s campaign.”&nbsp;Media Planner: “Why analyze it?”&nbsp;Data Scientist: “Because I need to support your media planning.”&nbsp;Media Planner: “Well, thanks for your kindness… but I really don’t need it.”&nbsp;Data Scientist: “… I know, but if I don’t do it, I’ll be in trouble. This is why they hired me.”Media Planner: “Alright… You do your thing, I’ll do mine.”&nbsp;Data Scientist: “Cool.”And so they moved forward, like two parallel lines, seemingly destined never to cross.<h3>“What Are You Doing?”</h3>But curiosity is a two-way street.One day, the data scientist glanced over at his neighbor’s screen.Data Scientist: “What the hell are you doing?!”&nbsp;Media Planner: “I’m replicating this quarter’s TV plan from the previous quarter.”&nbsp;Data Scientist: “Why not start fresh? TV markets and audiences change all the time.”&nbsp;Media Planner: “Ideally, yeah… but I have a lot to do. After TV, I have to do Radio, then OOH…”&nbsp;Data Scientist: “But does copying an old plan really make sense?”&nbsp;Media Planner: “Well, last quarter’s plan got approved. If I keep it similar, this one will probably get approved too.”&nbsp;Data Scientist: “Wow. That’s… an efficient way to work.”Like a snake biting its tail, they were chasing the same problem from different angles, stuck in a loop of habit and expectation.<h3>Breaking Bread, Breaking Barriers</h3>Their professional worlds remained distant, but their lunch breaks brought them together. Every day, over hurried bites of food, they complained about their jobs, their workload, and the absurdities of agency life.One day, the conversation took a turn.Media Planner: “You know, I actually think your data could be useful. It could tell me which TV genres and programs perform best—by audience size, timing, network, all that.”&nbsp;Data Scientist: “Exactly! That’s why I analyze it and build automation for the process.”&nbsp;Media Planner: “Can I see what you’ve got? If it’s as objective as you say, I want to check it out.”&nbsp;Data Scientist: “Absolutely. Let’s finish lunch and I’ll show you.”Back at the office, the data scientist presented two things:<ul><li>An Excel file—a meticulously crafted dataset with every TV program’s network, station, genre, timing, ad placements, audience size, and even sales impact. The media planner was stunned. </li><li>A software tool—a model built to simulate different TV ad settings and predict their future impact. This one left the media planner speechless.</li></ul>After a moment of silence, he spoke: “We need to show this to the strategist.”<h3>The Turning Point</h3>The media planner integrated the tool into his planning. Together, they presented it to the head of strategy. After rigorous testing, tweaks, and validations, the entire media planning team adopted it into their workflow.The data scientist was shocked—his once-skeptical desk neighbor had become a champion for data-driven planning.The media planner was equally surprised—planning didn’t have to be based on instinct and past approvals; it could be guided by real insights.They were no longer parallel lines.They were now part of the same process, each depending on the other to refine their craft. The media planner needed insights to shape future plans, and the data scientist needed feedback to refine the models.They worked shoulder to shoulder, making things happen.<h3>Where Are They Now?</h3>You already know how this story ends. The data scientist became one of the founders of <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" rel="noopener" data-mce-selected="inline-boundary">More Than Data</a>, building core media measurement solutions.And the media planner? He climbed the ladder—from junior planner to senior planner, to account manager, to strategy director.No matter where he worked, he always brought his old desk neighbor with him. To him, that data scientist was still the same guy—his lunch buddy, his sounding board, the one who made media planning better.Sometimes, time doesn’t just change things. It connects them.

A Data Scientist Sitting Next to a Media Planner

<h2>Understanding Media Mix Modelling</h2>
In today's dynamic marketing landscape, understanding the impact of various media channels is crucial for creating effective strategies. Media Mix Modelling (MMM) serves as a statistical analysis technique that helps marketers determine how different marketing channels contribute to their goals. By examining historical data, MMM provides insights into where to allocate resources for maximum impact.

Media Mix Modelling analyzes past performance to predict future outcomes. It takes into account various factors, including traditional and digital media, to give a comprehensive view of a campaign's effectiveness. This model helps businesses optimize their marketing spend by identifying which channels yield the best return on investment (ROI).

<figure id="figure-nkwz3vjh18m7002yah"><img id="nkwz3vjh18m7002yah" src="https://media.gettyimages.com/id/2157709105/photo/data-fabric-ai-artificial-intelligence-powered-analytics-data-data-verse-big-data-data.jpg?b=1&s=2048x2048&w=0&k=20&c=gYImeeQslIntNzWrO8iIyRALiovJOudFMtQ4GEeUQm8=" alt="data analysis" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Benefits of Implementing Media Mix Modelling</h2>
Implementing MMM offers several advantages for businesses aiming to enhance their marketing strategies. One of the primary benefits is the ability to make data-driven decisions. With MMM, companies can move away from guesswork and leverage concrete data to guide their marketing efforts.

Another significant benefit is the optimization of budget allocation. By understanding which channels drive the most impact, businesses can allocate their budgets more efficiently, ensuring that every dollar spent contributes to achieving their marketing objectives. This targeted approach leads to increased efficiency and effectiveness across campaigns.

<h3>Enhancing Marketing Effectiveness</h3>
MMM also plays a pivotal role in enhancing overall marketing effectiveness. By providing insights into consumer behavior and media interactions, it allows marketers to create more personalized and relevant campaigns. This not only improves customer engagement but also strengthens brand loyalty.

<figure id="figure-sa3v8xxzf9m7002yah"><img id="sa3v8xxzf9m7002yah" src="https://media.gettyimages.com/id/629303228/photo/im-happy-to-explain.jpg?b=1&s=2048x2048&w=0&k=20&c=WEmzS8V0sMIhn9i-_wyF5Cs9Iyk4Ye2AfzGK4jmkLt4=" alt="marketing strategy" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Steps to Implement Media Mix Modelling</h2>
Implementing MMM involves several key steps that ensure its effectiveness. Below is a simplified process that can guide businesses through successful implementation:

<ol>
 <li>Data Collection: Gather historical data from various marketing channels, including sales data, media spend, and other relevant metrics.</li>
 <li>Model Development: Use statistical techniques to develop a model that represents the relationships between media channels and business outcomes.</li>
 <li>Analysis: Analyze the model results to identify which media channels are driving the most value and where adjustments are needed.</li>
 <li>Optimization: Use insights gained from the analysis to optimize your media mix and adjust future marketing strategies accordingly.</li>
</ol>

<figure id="figure-9zhajumcgm7002yah"><img id="9zhajumcgm7002yah" src="https://media.gettyimages.com/id/2164071283/photo/communication-concept.jpg?b=1&s=2048x2048&w=0&k=20&c=R2oBtFvsq3OOipDQtGrOGIISRoFhla0BK7Dp3xTNk_o=" alt="teamwork" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h3>Challenges in Media Mix Modelling</h3>
While MMM offers numerous benefits, it also presents certain challenges. One common challenge is data quality and availability. Ensuring that the data used is accurate and comprehensive is crucial for reliable modelling outcomes. Inaccurate data can lead to misleading insights and suboptimal decision-making.

Another challenge is the complexity of integrating diverse data sources, especially in organizations with numerous marketing channels. Effective MMM requires seamless integration of data from both online and offline platforms, which can be resource-intensive.

<h2>The Future of Media Mix Modelling</h2>
The future of MMM is bright with advancements in technology and data analytics. As artificial intelligence and machine learning continue to evolve, they will further enhance the capabilities of MMM, making it more precise and easier to implement.

Businesses that invest in sophisticated MMM techniques are likely to gain a competitive edge by being able to quickly adapt to changes in consumer behavior and market dynamics. As a result, they will be better positioned to achieve their marketing goals and drive growth in an increasingly competitive environment.

Implementing Media Mix Modelling for Effective Marketing Strategies

In today’s ever-evolving media landscape, marketing professionals face increasing pressure from brands to deliver effective and data-driven strategies. Media agencies must integrate various data sources—spend, post-campaign metrics, audience insights, consumer behaviors—into their workflows to stay competitive. Marketing Mix Modeling (MMM) is emerging as a powerful tool to support this transformation. But who inside a media agency would benefit the most from MMM? Is it the media strategist, the media planner, or someone else?<h3>The Role of a Media Strategist and Why MMM Matters</h3>A media strategist is responsible for designing high-level media strategies that align with brand objectives. They analyze market trends, consumer behavior, and competitive activities to develop media frameworks that maximize campaign effectiveness.Why MMM is Essential for Media Strategists:<ul><li>Data-Driven Decision Making: MMM allows strategists to quantify the impact of past media investments, ensuring their recommendations are backed by historical performance data rather than just intuition. </li><li>Optimizing Cross-Channel Strategies: With the fragmentation of media channels, MMM helps strategists identify which media touchpoints contribute most to the KPI, enabling better allocation of budgets. </li><li>Justifying Strategies to Clients: Brands are demanding more accountability and ROI insights from agencies. MMM provides a structured approach to demonstrate how different media investments drive business results.</li></ul>Example Without MMM: A strategist develops a media plan based on prior experience and industry trends. However, without MMM, they struggle to quantify which media channels truly drive sales. If the client questions their recommendations, the strategist lacks solid data to support their claims, potentially leading to budget cuts or loss of trust.<h3>The Role of a Media Planner and Why MMM is a Game-Changer</h3>Media planners translate strategic vision into actionable media plans. They decide on media buying tactics, channel mix, budget allocation, and campaign execution.Why MMM is Essential for Media Planners:<ul><li>Precision in Media Buying: MMM helps planners fine-tune budget allocations by revealing the most effective media investments. </li><li>Forecasting Performance: With predictive modeling, planners can anticipate how adjustments in media spend will impact KPIs, reducing guesswork. </li><li>Reducing Wasted Spend: MMM highlights underperforming channels, allowing planners to reallocate budgets efficiently and avoid wasteful spending.</li></ul>Example Without MMM: A media planner distributes a client’s budget across different channels based on standard benchmarks. However, without MMM insights, they may over-invest in underperforming channels, leading to inefficient spend and missed opportunities to maximize impact. This results in lower ROI, and the agency risks losing the client.<h3>Beyond Strategists &amp; Planners: Who Else Can Benefit from MMM?</h3>While media strategists and planners are the primary users of MMM, other professionals inside and outside of media agencies can also benefit:<ul><li>Account Directors &amp; Client Leads: They need strong data-backed narratives to retain and grow client relationships. </li><li>Marketing Analysts: They analyze media impact and require robust attribution models for campaign effectiveness reporting. </li><li>Brand Marketers &amp; CMOs: On the client side, brand marketers increasingly demand sophisticated measurement tools to justify their media investments. </li><li>Marketing Technology Specialists: Responsible for tool adoption, they ensure the agency remains competitive in measurement capabilities.</li></ul><h3>MMM: A Competitive Edge for Media Agencies</h3>We understand that media agencies have been operating successfully without MMM. However, the landscape has shifted. Brands are demanding more accountability, competition among agencies is fierce, and media fragmentation makes decision-making more complex. Agencies that adopt MMM will have an edge in optimizing media strategies, justifying their work, and retaining clients. Those that don’t risk falling behind.At <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" rel="noopener" data-mce-selected="inline-boundary">More Than Data</a>, we don’t just provide an MMM tool—we deeply understand the media agency business model and operational workflows. Our solution seamlessly integrates into your processes, ensuring a smooth transition without disrupting your current way of working.MMM isn’t a mandatory choice, but it’s a strategic one. The agencies that leverage it will outpace their competitors. Don’t be left behind—take action now and <a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank" rel="noopener">get started with us</a>!

Is MMM for Media Strategists, Media Planners, or Someone Else?

<h2>Understanding the Importance of Marketing Analytics Software</h2>In today's digital age, marketing analytics software has become an essential tool for businesses looking to thrive in competitive markets. For businesses, understanding how to leverage these tools effectively can mean the difference between stagnation and growth. Marketing analytics solutions provide insightful data that can help tailor strategies, optimize campaigns, and ultimately drive better results.<figure id="figure-3gc15sx48mm6vprdhf"><img id="3gc15sx48mm6vprdhf" src="https://media.gettyimages.com/id/917844420/photo/financial-and-technical-data-analysis-graph-showing-search-findings.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=CnA_8UcYKgPbWeN82hy1GkNRTCM6Ps3rYysgf4aYEpo=" alt="marketing analytics" class="object-cover bg-gray-100" style="aspect-ratio: 16/9;" data-mce-src="https://media.gettyimages.com/id/917844420/photo/financial-and-technical-data-analysis-graph-showing-search-findings.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=CnA_8UcYKgPbWeN82hy1GkNRTCM6Ps3rYysgf4aYEpo=" data-mce-style="aspect-ratio: 16/9;"></figure>With an abundance of options available, choosing the right marketing analytics software can be overwhelming. It's crucial to understand your business's specific needs and goals before making a decision. Whether you're a small startup or an established enterprise, selecting the right tool can enhance your marketing efforts significantly.<h3>Key Features to Consider</h3>When evaluating marketing analytics software, consider the features that align with your business objectives. Here are some critical aspects to look for:<ul><li>Data Integration: Ensure the software can integrate with other tools you use, such as CRM systems and social media platforms.</li><li>User-Friendly Interface: A simple, intuitive dashboard can save time and reduce the learning curve for your team.</li><li>Real-Time Analytics: Access to up-to-date data allows for timely decision-making and strategy adjustments.</li></ul><h3>Comparing Popular Options</h3>Businesses have access to a range of marketing analytics tools, each with unique strengths. Some popular choices include:<ol><li>Google Analytics: A comprehensive, free tool ideal for tracking website traffic and user behavior.</li><li>HubSpot: Offers robust integration capabilities and is particularly beneficial for inbound marketing strategies.</li><li>Tableau: Known for its powerful data visualization features, helping businesses make sense of complex data sets.</li></ol><figure id="figure-h2dyiebo0fm6vprdhf"><img id="h2dyiebo0fm6vprdhf" src="https://media.gettyimages.com/id/1577017327/photo/graph-stock-chart-stock-market-digital-fui.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=My_GyVNC2htzDmCH0gWxI705kX8Vw1V8N1FLA_GaxVE=" alt="data visualization" class="object-cover bg-gray-100" style="aspect-ratio: 16/9;" data-mce-src="https://media.gettyimages.com/id/1577017327/photo/graph-stock-chart-stock-market-digital-fui.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=My_GyVNC2htzDmCH0gWxI705kX8Vw1V8N1FLA_GaxVE=" data-mce-style="aspect-ratio: 16/9;"></figure>Each of these options offers distinct advantages depending on your business's size, industry, and specific needs. Conducting a thorough comparison based on these factors can help narrow down your choices.<h3>The Role of Budget in Decision-Making</h3>Budget is a critical factor when choosing marketing analytics software. While some tools offer free versions or tiers, others might require a significant investment. Consider the return on investment (ROI) that the software is likely to provide. Investing in a more expensive solution could be justified if it offers advanced features that align with your long-term business goals.It's also worth exploring any potential hidden costs, such as training fees or additional support costs. Ensure that you have a clear understanding of the total financial commitment before making a decision.<figure id="figure-gg0046e6hhm6vprdhf"><img id="gg0046e6hhm6vprdhf" src="https://media.gettyimages.com/id/1168618923/photo/japanese-man-calculating-financial-bills-at-home.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=C0gKVZstqh-Gj_O611ytQKOTmRqU7Symac-mlAXzy7Q=" alt="budget planning" class="object-cover bg-gray-100" style="aspect-ratio: 16/9;" data-mce-src="https://media.gettyimages.com/id/1168618923/photo/japanese-man-calculating-financial-bills-at-home.jpg?b=1&amp;s=2048x2048&amp;w=0&amp;k=20&amp;c=C0gKVZstqh-Gj_O611ytQKOTmRqU7Symac-mlAXzy7Q=" data-mce-style="aspect-ratio: 16/9;"></figure><h3>Trial Periods and Demos</h3>Most marketing analytics software providers offer trial periods or demos. Taking advantage of these opportunities allows you to test the software's functionality and determine if it meets your needs. Engage your marketing team in this process to gather diverse feedback and ensure that the chosen software is user-friendly and effective across different departments.During trials, pay attention to how easily the software integrates with your existing systems and whether it offers the insights you need to improve your marketing strategies.<h3>Making the Final Decision</h3>Once you’ve thoroughly evaluated your options, it's time to make a decision. Choose a solution that not only meets your current needs but also has the scalability to support future growth. A well-chosen marketing analytics tool will empower your business to make data-driven decisions, optimize campaigns, and ultimately achieve better results.Remember, the right tool can provide invaluable insights into customer behavior, campaign performance, and overall marketing effectiveness, setting your business on a path to success in vibrant market.

Choosing the Right Marketing Analytics Software for Your Business

When preparing for a Marketing Mix Modeling (MMM) project, media agencies often struggle with messy and chaotic workflows. The data itself isn’t inherently disorganized, but the way it is handled causes quality issues, delays, and inefficiencies. In this article, we explore why this happens and provide simple, effective solutions to overcome these challenges—without diving into large-scale cloud storage systems like GCP, AWS S3, or Azure. Since most data management within media agencies revolves around Excel, our solutions focus on practical Excel-based methods.<h3>Scattered Files: The Library Analogy</h3>Multiple Excel files related to the same client and project are often stored in different locations. This is similar to how we save personal files on our computers without a clear archive system—eventually, we forget what’s been saved and where. Media agencies frequently spend excessive time searching for and confirming the correct Excel files.Solution: Think of a well-organized library with a cataloging system. Media agencies should adopt a structured approach to file storage, using designated folders with clear naming conventions. A centralized directory (even if just on a shared drive) can significantly improve efficiency.<h3>Multiple Versions of the Same Data: The Versioning Problem</h3>It’s common to find multiple versions of the same dataset across different Excel files. While each version contains some correct data, inconsistencies creep in, making it difficult to determine which records are accurate.Solution: Maintain only two core Excel files:<ul><li>A working Excel file for daily updates and modifications. </li><li>A validated archive Excel file, updated only after receiving formal confirmation and sign-off from a designated person. This serves as the source of truth.</li></ul>By separating these two functions, media agencies can eliminate unnecessary versions and confusion.<h3>The Missing Documentation: Data Traceability</h3>Without proper documentation, it’s difficult to track the origin, updates, and modifications of datasets. This leads to inefficiencies and confusion when retrieving past data.Solution: Maintain a simple documentation file (e.g., a Word document or Excel log) that records:<ul><li>File names and locations </li><li>Creation and last edited dates </li><li>Data processing steps </li><li>Any changes in data structure or metrics</li></ul>This document acts as a "data diary," providing a clear history of all data updates and making it easier to onboard new team members.<h3>Developing Good Data Management Habits</h3>Media agencies operate in a fast-paced environment with frequent meetings and tight deadlines. This often leads to neglecting structured data management practices.Solution: Cultivate daily habits for data organization. Media strategists and planners—who use data extensively—should take responsibility for:<ul><li>Organizing and archiving data consistently </li><li>Maintaining the two core Excel files </li><li>Updating documentation regularly</li></ul>Since this process doesn’t require advanced tools—just Excel and Word—it’s easy to start immediately.<h3>A Simple Framework for Evaluating Data Management</h3>Media agencies should assess their data management practices using the following criteria:<ul><li>Do they maintain only two key Excel files (dynamic and static)? </li><li>Do they keep clear documentation of data sources and changes? </li><li>Can they quickly retrieve necessary files without confusion?</li></ul>If the answer is yes, congratulations! If not, now is the time to take action and implement structured data management processes.<h3>Partner with Us for Better Data Management</h3>At <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank">More Than Data</a>, we specialize in helping media agencies streamline data handling, making their work easier and improving the accuracy of media measurement. We’ve partnered with several agencies across Australia and New Zealand, bringing expertise in data governance and management.If these challenges sound familiar, <a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank" data-mce-selected="inline-boundary">reach out to us</a>. We’re here to help you take control of your data and optimize your MMM projects effortlessly.

Taming the Chaos: How Media Agencies Can Streamline Data Management for MMM Projects

Marketing Mix Modeling (MMM) has become an essential tool for businesses looking to optimize their marketing investments. However, selecting the right MMM partner is not as straightforward as it may seem. Many vendors claim to provide the best solutions, but the reality is that MMM is a complex process requiring careful consideration. Here’s how to properly choose your MMM partner.<h3>Understanding Data Requirements: Comprehensive but Not Perfect</h3>MMM relies on multiple data sources, including key performance indicators (KPIs), media spend, marketing activities, and external factors such as seasonality and economic indicators. However, ensuring that data is 100% comprehensive and complete is virtually impossible. No vendor can guarantee absolute completeness.A more reasonable approach is to collect as much logically and conceptually relevant data as possible. The goal is not to achieve perfect data coverage but to use the available data to explain the variations in the KPI effectively. MMM is an approximation process, where insights are drawn from a limited but meaningful dataset. An MMM partner who understands this and works to maximize the utility of known data is far more valuable than one making unrealistic claims of data perfection.<h3>Different Modeling Approaches: There’s No One-Size-Fits-All</h3>Different MMM vendors employ different modeling techniques. Some may use traditional linear regression, while others might leverage Bayesian models. The key question isn’t which method is superior; rather, it is whether the model logically and reasonably explains the KPI variations.Unlike some fields with definitive ground truth and governing bodies, MMM lacks a universally accepted methodology or regulatory authority. This means that as long as the modeling approach provides a reasonable and transparent way to approximate KPIs, it is a valid option. A good MMM partner will be open about their approach and explain their reasoning in a clear and understandable way.<h3>Model Assessment: No Standardized Evaluation</h3>Since there is no universally accepted gold standard for assessing MMM models, different vendors use different validation techniques. Some emphasize traditional statistical tests to ensure model validity and reliability, while others prioritize metrics such as R-squared, p-values, mean squared error, or hold-out testing.The right MMM partner should not just focus on one or two metrics but rather take a holistic approach to model evaluation. They should be able to justify their choice of validation methods and demonstrate how these ensure the accuracy and reliability of the model.<h3>Balancing Statistical Rigor with Business Relevance</h3>MMM is not just a statistical exercise; it must also align with business and commercial considerations. The ultimate users of MMM insights are media strategists and planners, who need practical and actionable insights to inform their strategies.A model that meets all statistical criteria but fails to provide actionable recommendations for marketing decision-makers is of little value. The best MMM partners balance statistical rigor with commercial applicability, ensuring that the model’s outputs are both reliable and useful for business strategy.<h3>Beware of AI-Driven Hype</h3>Artificial Intelligence (AI) has become a buzzword in marketing analytics, but it’s important to remain skeptical. Some vendors overstate AI’s role, using it as a catch-all term to obscure a lack of transparency in their models. If an MMM vendor cannot clearly explain their model and instead attributes its performance to AI, this is a red flag.MMM has been around for decades, long before AI became a mainstream technology. While AI may help automate certain aspects of modeling, it does not replace the fundamental principles of MMM. A trustworthy MMM partner should be able to explain their approach without relying on vague AI jargon.<h3>The Ultimate Test: Reproducibility</h3>One of the most important aspects of any MMM model is its reproducibility. A well-documented model should allow users to reproduce results using the same input data and transformation formulas. Transparency in modeling parameters and mathematical transformations is crucial to ensure credibility.If an MMM vendor provides a "black-box" solution where the methodology is unclear or non-reproducible, this is a major warning sign. The best way to verify an MMM model is to rerun it with the same inputs and obtain the same or highly similar results. A reputable MMM partner will provide all necessary details to facilitate this process.<h3>Conclusion: Finding the Right MMM Partner</h3>Choosing the right MMM partner requires careful consideration of their approach to data, modeling methodologies, validation techniques, business relevance, and transparency. Beware of vendors who overpromise on data completeness, rely on AI buzzwords, or offer black-box solutions with no reproducibility.The best MMM partners understand that modeling is an approximation process, that different methodologies can be valid, and that statistical rigor must be balanced with business needs. They provide transparent, reproducible models that empower businesses to make informed marketing decisions.By focusing on these criteria, you can select an MMM partner who truly adds value to your marketing strategy rather than one who simply follows industry hype.If you are looking for an MMM partner but are unsure about where to start, why not just talk to us? <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" data-mce-selected="inline-boundary">We are here to help</a>!

How to Properly Choose Your Marketing Mix Modeling Partner

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!

Mulish

Sora

Merriweather

Thank You to Our First 100 Clients and Users.
Your support helped shape our products and services—built to make media impact measurement accessible and affordable.
Starting 1 July 2025, Minute MMM and Budget Optimizer move to a paid model with monthly subscription and upfront payment options.
We're no longer free—but we're still powerful, affordable, and focused on your success.

Blog

A Data Scientist Sitting Next to a Media Planner

Implementing Media Mix Modelling for Effective Marketing ...

Is MMM for Media Strategists, Media Planners, or Someone ...

Choosing the Right Marketing Analytics Software for Your ...

Taming the Chaos: How Media Agencies Can Streamline Data ...

How to Properly Choose Your Marketing Mix Modeling Partner