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In our previous article, <a data-mce-href="https://morethandata.biz/blog/why-small-and-medium-sized-media-agencies-haven-t-used-mmm" href="https://morethandata.biz/blog/why-small-and-medium-sized-media-agencies-haven-t-used-mmm" target="_blank" rel="noopener">Why Small and Medium-Sized Media Agencies Haven’t Used MMM</a>, we explored the challenges faced by media agencies in adopting MMM. These challenges range from limited resources and expertise to the high costs associated with implementing MMM solutions. In this follow-up article, we delve deeper into one of the core hurdles that many agencies face when attempting to leverage MMM: the limitations of traditional Software-as-a-Service (SaaS) platforms used to build and execute MMM.While SaaS platforms promise convenience, scalability, and cost-effectiveness, they often fall short when it comes to providing the flexibility, transparency, and support that small and medium-sized agencies need to succeed with MMM. Below, we examine the key limitations of these traditional SaaS solutions and why they may not always be the best fit for agencies seeking to maximize the impact of their marketing strategies.<h3>Limited Customization </h3>Customization is a significant challenge when building MMM, as it requires modelers to adjust and recalibrate the model to align with both commercial and marketing practices, as well as statistical assumptions and tests. While SaaS platforms may allow users to tweak certain inputs or settings, the core logic and algorithms are often hidden. This lack of visibility prevents businesses from fully tailoring the model to their specific needs and unique marketing nuances. Consequently, they are often forced to rely on a one-size-fits-all approach, which may not be well-suited for complex or specialized marketing strategies.Without a clear understanding of the underlying model, making informed, data-driven adjustments or fine-tuning the analysis becomes increasingly difficult. This ultimately hinders the ability to achieve optimal, actionable results. When customization is restricted, businesses miss the opportunity to optimize the model to suit their unique needs and leverage data more effectively.In our previous article, <a data-mce-href="https://morethandata.biz/blog/building-mmm-the-traditional-way--why-it-s-so-time-consuming" href="https://morethandata.biz/blog/building-mmm-the-traditional-way--why-it-s-so-time-consuming" target="_blank" rel="noopener">Building MMM the Traditional Way: Why It’s So Time-Consuming</a>, we discussed the reasons why building an MMM in the traditional way can be time-consuming and inefficient. One of the key challenges is that the model often requires iterative adjustments to align the media contribution with the sales outcomes. Achieving a satisfactory percentage-wise (%) media contribution to sales typically takes considerable time, as it involves multiple rounds of recalibration and fine-tuning. This iterative process is a typical example and representation of customization in action.<h3>Hidden Backend Processes</h3>Another key limitation of traditional SaaS platforms for MMM is the obscurity of critical backend processes. These platforms often make it challenging for users to understand how their data is being processed, integrated, and analyzed. Data cleaning, normalization, and transformation are essential steps for ensuring the accuracy and quality of the data that feeds into the model. However, when these processes are not transparent, users lack insight into how their data is being handled.As a result, it becomes difficult to verify that the data is reliable and aligned with business objectives. Without visibility into the data flow, businesses risk working with flawed or inconsistent data, leading to inaccurate models and misguided decisions. The lack of transparency ultimately undermines the trust users have in the platform and the insights it provides, which can have a detrimental effect on marketing decisions and outcomes.<h3>Data Integration Challenges</h3>Effective MMM requires the integration of various data sources, such as media spend, sales data, competitor activity, and external factors like weather or economic conditions. While many SaaS platforms offer pre-built integrations with popular data sources, users often have limited control and visibility into how this data is processed once it’s uploaded.For agencies managing large volumes of diverse data, ensuring seamless integration and alignment with the business’s marketing objectives becomes a significant challenge. Lack of control over how data is managed within these platforms can lead to inefficiencies, errors, and missed opportunities to draw meaningful insights.<h3>Self-Service Tools Are Too Complicated</h3>One of the primary appeals of SaaS platforms is their promise of self-service tools that allow users to manage and execute complex processes without needing specialized expertise. However, many traditional SaaS platforms offering MMM have self-service tools that can overwhelm non-technical users.Steep Learning CurveWhile SaaS platforms are marketed as user-friendly, the reality is that the complexity of MMM requires a certain level of expertise to operate effectively. Non-technical users, such as marketers or media planners, often struggle to navigate the sophisticated analytics features, configure the right settings, or interpret the results. The steep learning curve associated with these tools can lead to frustration, inaccurate analysis, and underutilization of the platform’s capabilities.We browsed through customer and user feedback on <a data-mce-href="https://www.capterra.com/p/178761/MassTer-Predictive-Marketing-Analytics/" href="https://www.capterra.com/p/178761/MassTer-Predictive-Marketing-Analytics/" target="_blank" rel="noopener">MASS Analytics</a>, and while many users offered positive comments about the software, they also mentioned some challenges. Some users pointed out that the software is not particularly convenient to use. They highlighted that the numerous features can be overwhelming, and the process often feels like a back-and-forth, requiring constant adjustments and navigating between different buttons, screens, and windows. This feedback indicates that while the tool offers valuable functionality, the user experience could be improved. Streamlining the interface for greater ease of use and efficiency would be particularly beneficial for users without extensive technical expertise, allowing them to leverage the software’s full potential without unnecessary complexity.<figure id="figure-2977aurgdm5z6xi77" class=""><img id="2977aurgdm5z6xi77" src="https://cdn.durable.co/blocks/22BtABrqPr3hPWdSEFgcK9XCvNqhNK11S40bP1RmdMsXrgqfSuqJD5BQ42ph3LMj.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: undefined undefined;" data-corners="default" data-aspect="16:9" data-caption="Source: https://www.capterra.com/p/178761/MassTer-Predictive-Marketing-Analytics/" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/22BtABrqPr3hPWdSEFgcK9XCvNqhNK11S40bP1RmdMsXrgqfSuqJD5BQ42ph3LMj.png" data-mce-style="aspect-ratio: 16/9; object-position: undefined undefined;"><figcaption class="body-normal text-gray-500 mt-2">Source: https://www.capterra.com/p/178761/MassTer-Predictive-Marketing-Analytics/</figcaption></figure>We also noticed that most of the users of MASS Analytics software are analytics professionals, such as analysts, analytics managers, consultants, and lead data scientists. This indicates that the tool is more suited for technical users who have the expertise to navigate its complex features and functionalities. However, for non-technical users, this software may present a challenge, making it a difficult choice for those without specialized data skills. To truly unlock the power of MMM, non-technical users need a more intuitive, user-friendly solution that allows them to manage the process without the steep learning curve and technical complexities.Limited Support and GuidanceMost traditional SaaS platforms offer limited or no personalized support for users, relying instead on automated tutorials or knowledge bases. While these resources can be helpful, they often fall short for non-technical users who may require more hands-on assistance. In the absence of effective support, users can become stuck or make errors in their analysis, which can ultimately undermine the value of the platform.For businesses that do not have dedicated data science teams or specialized personnel, the complexity of self-service tools can become a significant barrier. Without proper assistance, users may avoid using the platform to its full potential or, worse, misuse it entirely.<h3>The Expense of Current SaaS Solutions</h3>While SaaS platforms are often marketed as cost-effective alternatives to traditional software or custom-built solutions, they can still be quite expensive, especially for businesses that require more advanced features or higher levels of support.Subscription Fees and Hidden CostsMany SaaS platforms operate on a subscription-based pricing model, where businesses pay recurring fees for access to the software. While this can be more affordable upfront compared to building an in-house solution, the costs can quickly add up over time. In addition to basic subscription fees, many platforms charge extra for advanced features, increased data storage, or additional users. These hidden costs can make the overall expense of using a SaaS platform much higher than initially anticipated.Resource AllocationIn addition to subscription fees, businesses must also factor in the time and resources required to fully utilize a SaaS platform. For non-technical teams, the need for additional training or external support services can increase operational costs. Companies may need to hire third-party consultants or data experts to manage the platform and ensure accurate modeling, further increasing the overall expense.For smaller businesses or those with limited budgets, these cumulative costs can make traditional SaaS solutions less cost-effective in the long term, particularly when compared to more tailored or in-house approaches that offer greater flexibility and control.<h3>Conclusion: Rethinking the Approach to MMM</h3>While traditional SaaS platforms offer a convenient way to build and execute MMM, they come with several limitations that may hinder the effectiveness of businesses trying to optimize their marketing strategies. The lack of customization, hidden backend processes, complex self-service tools, and high costs are significant challenges, particularly for businesses without specialized technical expertise.As marketing continues to become more data-driven, businesses must carefully assess whether traditional SaaS solutions are truly the right fit for their needs. The limitations of these platforms—ranging from restricted flexibility to the challenges of working with opaque processes—suggest that alternative approaches may offer more tailored solutions, greater customization, and a more cost-effective path toward effective MMM.Ultimately, the future of MMM will likely lie in solutions that strike a better balance between ease of use, customization, and cost-efficiency. Such solutions will empower businesses to unlock the full potential of their data, making informed, data-driven decisions without being constrained by the limitations of traditional SaaS platforms. By embracing more flexible, transparent, and user-friendly models, businesses can stay ahead in an increasingly competitive marketing landscape.If you're looking for an easy-to-use, customizable, DIY-enabled, and cost-efficient solution for MMM, please <a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank" data-mce-selected="inline-boundary">contact us</a>!

Why Traditional SaaS Solutions for Marketing Mix Modelling Have Limitations

<h2>Understanding the Importance of AI in Marketing</h2>
In today's rapidly evolving digital landscape, Artificial Intelligence (AI) is no longer a futuristic concept but a present-day necessity. For Sydney marketers, leveraging AI can transform how they understand and engage with their customers. The integration of AI in marketing strategies not only enhances customer experience but also drives business growth. By harnessing the power of AI, marketers can gain deeper insights into consumer behavior, enabling them to tailor their campaigns more effectively.

<figure id="figure-uoqqi3nglbm5xf6qst"><img id="uoqqi3nglbm5xf6qst" src="https://media.gettyimages.com/id/1889510378/photo/ai-enhanced-social-networking.jpg?b=1&s=2048x2048&w=0&k=20&c=9qP8sQkkkRHC2roYuoQ4gVejwcqrLOyWVADVOd-iUZY=" alt="ai marketing" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Enhancing Customer Segmentation with AI</h2>
One of the most significant advantages of using AI in marketing is the ability to enhance customer segmentation. Traditional segmentation methods often rely on broad categories, but AI allows for more precise and granular segmentation. By analyzing data patterns and customer interactions, AI can identify specific segments based on behavior, preferences, and demographics. This allows Sydney marketers to craft personalized messages that resonate with individual customers, increasing the likelihood of conversion.

AI-powered tools can process vast amounts of data in real-time, offering insights that were previously unattainable. As a result, marketers can create highly targeted campaigns that speak directly to the needs and desires of their audience. This level of personalization not only improves customer satisfaction but also fosters brand loyalty.

<h2>Predictive Analytics for Better Decision Making</h2>
Predictive analytics is another area where AI can significantly benefit marketers. By analyzing past customer behavior and predicting future actions, AI helps marketers make informed decisions that drive results. This capability is especially valuable in planning marketing strategies and allocating resources efficiently.

<figure id="figure-g5penx9etim5xf6qst"><img id="g5penx9etim5xf6qst" src="https://media.gettyimages.com/id/2160041298/photo/a-financial-analyst-using-ai-powered-predictive-analytics-to-forecast-market-trends-and.jpg?b=1&s=2048x2048&w=0&k=20&c=sFmaE98koZXGDJSOF5sSu5TtHGG440z3F3KnDGdha5U=" alt="predictive analytics" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

For example, by understanding which products a customer is likely to purchase next or which channels they prefer for communication, marketers can optimize their strategies accordingly. Predictive analytics can also help in identifying trends and patterns that might not be evident through traditional analysis methods.

<h2>Improving Customer Engagement Through Chatbots</h2>
AI-driven chatbots have revolutionized how businesses interact with their customers. These intelligent virtual assistants provide instant support and information, enhancing customer engagement and satisfaction. For Sydney marketers, implementing chatbots can streamline customer service processes and provide 24/7 assistance without the need for human intervention.

Chatbots can handle various tasks, from answering frequently asked questions to assisting with product recommendations. By integrating chatbots into their marketing strategy, businesses can ensure a seamless and responsive customer experience, ultimately leading to higher customer retention rates.

<figure id="figure-eo6ct4yu5qm5xf6qst"><img id="eo6ct4yu5qm5xf6qst" src="https://media.gettyimages.com/id/1933417108/photo/ai-chatbot-artificial-intelligence-concept.jpg?b=1&s=2048x2048&w=0&k=20&c=8GDNbLpA9t0cu-nQwo2NRJBl2_Rf5jtBx92JzpvWA50=" alt="chatbot customer service" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Leveraging AI for Content Creation</h2>
AI is also making waves in content creation, offering tools that can generate high-quality content quickly and efficiently. For Sydney marketers, this means they can produce a steady stream of engaging content without overwhelming their creative teams. AI tools can assist in creating everything from blog posts to social media updates, ensuring consistency in messaging and tone.

Moreover, AI can analyze which types of content perform best with specific audiences, allowing marketers to refine their content strategies for maximum impact. By understanding what resonates with their audience, marketers can create content that drives engagement and fosters a deeper connection with their brand.

<h2>Conclusion: Embracing AI for Future Success</h2>
The integration of AI into marketing strategies is no longer optional for Sydney marketers who wish to remain competitive in today's market. By leveraging AI, businesses can gain valuable insights into their customers' needs and preferences, enabling them to deliver more personalized and effective marketing campaigns.

As AI technology continues to advance, its applications in marketing will only grow more sophisticated. Marketers who embrace these innovations will be well-positioned to lead the way in delivering exceptional customer experiences and achieving long-term success.

How Sydney Marketers Can Leverage AI for Better Customer Understanding

In our previous article, <a data-mce-href="https://morethandata.biz/blog/why-small-and-medium-sized-media-agencies-haven-t-used-mmm" href="https://morethandata.biz/blog/why-small-and-medium-sized-media-agencies-haven-t-used-mmm" target="_blank" rel="noopener">Why Small and Medium-Sized Media Agencies Haven’t Used MMM</a>, we discussed some barriers preventing agencies from adopting Marketing Mix Modeling (MMM). Another significant reason is the time-consuming nature of building MMM using traditional methods. Let’s explore why this process takes so much time.<h3>Slow Data Collection</h3>Data collection is one of the biggest bottlenecks in traditional MMM processes. For digital channels like search, social media, and online advertising, gathering data is relatively quick and straightforward. However, offline channels—such as TV, Out-of-Home (OOH), and radio—are a completely different story.Offline data often arrives in inconsistent formats, mingled across Excel and PDF files with ever-changing table structures and headings. For example, one file might label OOH data as “outdoor,” while another uses “out of home.” While the meaning is clear, the lack of standardization creates delays as teams must spend significant time reconciling and cleaning the data.If the data comes in a PDF format, it often leaves us questioning—how do we even begin to extract the numbers accurately? Take this example from a client case: A media agency received a 90-page PDF from Channel 9 after booking TV ads. Despite requesting an Excel version, none was provided, and attempts to use online PDF-to-Excel converters failed to produce accurate results, leaving the agency frustrated and overwhelmed. That’s where we stepped in. Leveraging our software, we transformed the PDF into a clean, structured Excel file, turning an otherwise daunting task into a seamless process.<figure id="figure-tzsl2y716nm5x9wwno"><img id="tzsl2y716nm5x9wwno" src="https://cdn.durable.co/blocks/2224sjxX2Gfa4OaACQMEzHuLRVXv0h8yILUw65isBdD9clEhboBGI9JRO0xZsW1q.png" alt="90-page-tv-pdf" title="90-page-tv-pdf" class="object-cover bg-gray-100" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/2224sjxX2Gfa4OaACQMEzHuLRVXv0h8yILUw65isBdD9clEhboBGI9JRO0xZsW1q.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><h3>Slow Data Processing</h3>Even after the data is collected, processing it can be another hurdle. Many media agencies rely on Excel for this step, using pivot tables and manual indexing. This manual work is prone to errors and inefficiencies. While some advanced users leverage VBA (Visual Basic for Applications) for automation, most marketers find it too complex and time-consuming to learn and implement effectively.<a data-mce-href="https://learn.microsoft.com/en-us/office/vba/library-reference/concepts/getting-started-with-vba-in-office" href="https://learn.microsoft.com/en-us/office/vba/library-reference/concepts/getting-started-with-vba-in-office" target="_blank" rel="noopener">Excel VBA</a> enables powerful data processing through coding and workflow design. While it can present a learning curve, many non-technical users and media agencies have successfully leveraged it to streamline their data operations with the right guidance and resources. Should additional support be needed, we are always here and happy to assist.<figure id="figure-u3tpnhjz6km5xa5hkx" class=""><iframe id="u3tpnhjz6km5xa5hkx" src="https://www.youtube.com/embed/G05TrN7nt6k" class="w-full bg-gray-100 " style="aspect-ratio: 16/9;" allowfullscreen="" data-url="https://www.youtube.com/watch?v=G05TrN7nt6k" data-corners="default" data-fullwidth="false" data-mce-src="https://www.youtube.com/embed/G05TrN7nt6k" data-mce-style="aspect-ratio: 16/9;"></iframe></figure>Furthermore, while <a data-mce-href="https://www.r-project.org/" href="https://www.r-project.org/" target="_blank" rel="noopener">R</a> and <a data-mce-href="https://www.python.org/" href="https://www.python.org/" target="_blank" rel="noopener">Python </a>are widely used in data analytics and processing, the key consideration is how non-technical users and media agencies can be empowered to effectively leverage these programming languages to achieve their goals. And, if additional support is needed, we are always here and ready to assist.<h3>Tedious Data Quality Checks and Validation</h3>Data validation often becomes an endless loop of back-and-forth updates. Agencies frequently revise datasets multiple times, signing off on one version only to find errors that require new updates.In one of our experiences with a media agency, we collaborated on tracking 10+ iterations of a dataset over six months. These updates reflected the evolving nature of their operations, including adjustments to media spend, special offers, competitor activity, and even KPI sales figures, which were refined four times. This dynamic environment underscores the complexity of maintaining a stable foundation for effective MMM while adapting to real-world changes.<h3>Complex Model Building Process</h3>Once the data is processed and validated, building the MMM itself introduces additional complexities. The model must satisfy both commercial and marketing criteria, as well as adhere to statistical assumptions and tests.In this article, we focus solely on commercial and marketing practice criteria. Readers interested in the statistical aspects can refer to the previous article, <a data-mce-href="https://morethandata.biz/blog/building-mmm-the-traditional-way--why-it-s-way-too-expensive" href="https://morethandata.biz/blog/building-mmm-the-traditional-way--why-it-s-way-too-expensive" target="_blank" rel="noopener">Building MMM the Traditional Way: Why It’s Way Too Expensive</a>.&nbsp;For example, in the FMCG industry, agencies might estimate that TV contributes 5% of sales, paid social 3%, paid search 1–2%, and OOH 6%. Meanwhile, discounts and promotions account for 12% and 11%, respectively. These percentage-based criteria require the modeler to validate each media variable one by one, transforming raw media spend data using techniques like diminishing returns and adstocking.However, the process is highly sensitive: adjusting one variable often disrupts the balance of others, requiring constant recalibration. This iterative cycle can feel like a frustrating game of "whack-a-mole," where solving one issue creates new ones.<figure id="figure-u54nfnrdijm5xaldlj"><img id="u54nfnrdijm5xaldlj" src="https://cdn.durable.co/blocks/214Q12WTgiQ64HKkFf6gtu6elZDK6LNtSxSYglWdrRXwT2QHJp8x1joT5GWo1Z99.png" alt="whack-a-mole" title="whack-a-mole" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/214Q12WTgiQ64HKkFf6gtu6elZDK6LNtSxSYglWdrRXwT2QHJp8x1joT5GWo1Z99.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><h3>Why This Matters</h3>Traditional MMM methods are simply too slow and inefficient for fast-paced scenarios. For instance, if a media agency needs to create a small-scale pitch model to win a new client, the lengthy MMM process makes it impossible to meet tight deadlines.As a result, many agencies opt to partner with freelancers for specialized expertise or focus on highlighting their strengths in creative capabilities and the experience of their teams in their pitch decks. While data-driven insights may not always be the focal point, agencies often incorporate carefully selected data visuals or dashboard screenshots to demonstrate their understanding of analytics and provide a comprehensive view of their approach.&nbsp;<h3>Conclusion</h3>The traditional way of building MMM is plagued by inefficiencies at every step—data collection, processing, validation, and modeling. For media agencies to truly embrace MMM, they need faster, more streamlined solutions that align with the time-sensitive nature of their work.If this resonates with your challenges, why not chat with us at <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" rel="noopener">More Than Data</a>? We’re here to help! Our solutions streamline the MMM process, addressing inefficiencies in data collection, processing, validation, and modeling. With our expertise, you can focus on delivering impactful insights without the headaches of traditional methods.Let’s work together to make your data-driven marketing a reality—quickly and effectively. <a data-mce-href="https://morethandata.biz/contact-us" href="https://morethandata.biz/contact-us" target="_blank">Contact us today</a>!

Building MMM the Traditional Way: Why It’s So Time-Consuming

In our previous article, we explored why small and medium-sized media agencies have yet to adopt marketing mix modelling (MMM). One key reason stood out: the high cost of building MMM the traditional way. Let’s break down why this cost is so significant.<h3>What is MMM?</h3>At its core, <a data-mce-href="https://en.wikipedia.org/wiki/Marketing_mix_modeling" href="https://en.wikipedia.org/wiki/Marketing_mix_modeling" target="_blank" rel="noopener">MMM</a> is a multivariate regression model designed to explain variations in a key performance indicator (KPI), such as sales, by analyzing multiple predictor variables like media spend, promotions, pricing, competitor actions, and more. However, MMM isn’t just a simple regression model—it must meet specific marketing and statistical criteria:<ul><li>Media Variables: Typically have a positive impact, but their contribution needs to be quantified. </li><li>Promotions &amp; Discounts: Positive, as they boost customer engagement. </li><li>Pricing: Higher prices may deter customers, while lower prices attract them. </li><li>Product Distribution: Greater availability enhances sales. </li><li>Competitor Activity: Often negative, as competitors can pull customers away. </li><li>External Factors: Variables like public holidays, weather, economic trends, natural disasters, or pandemics can have diverse impacts.</li></ul>The challenge lies in balancing these variables, assigning reasonable impact levels (positive or negative, strong impact or weak), and combining marketing expertise with rigorous statistical standards.<h3>The Complexity of MMM</h3>Building MMM involves more than just handling statistics. It requires passing various statistical tests—like multicollinearity checks and goodness-of-fit evaluations—while ensuring the model aligns with real-world marketing dynamics. You can refer <a data-mce-href="https://en.wikipedia.org/wiki/Linear_regression" href="https://en.wikipedia.org/wiki/Linear_regression" target="_blank" rel="noopener">here </a>for details on the specific statistical tests involved in building an MMM. This dual complexity of statistical rigor and marketing insights is what drives up costs.&nbsp;<h3><img id="vfpi54pdmfm5vq6lcx" src="https://cdn.durable.co/blocks/25VUp4pEBbukce8KP1P3NETN3zd3aLatDVd7SRy3zx8prs9l5XJLzXMdUIUjys6G.png" alt="regression-statistical-test" title="regression-statistical-test" class="object-cover bg-gray-100" style="aspect-ratio: 16/9; object-position: undefined undefined;" data-corners="default" data-aspect="16:9" data-caption="Search on Google to show the assumptions and statistical tests required for building a regression model" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/25VUp4pEBbukce8KP1P3NETN3zd3aLatDVd7SRy3zx8prs9l5XJLzXMdUIUjys6G.png" data-mce-style="aspect-ratio: 16/9; object-position: undefined undefined;">Why is MMM So Expensive?</h3>Given MMM’s complexity, skilled data analysts or data scientists are indispensable. But finding the right talent comes with challenges:<ul><li>Talent Scarcity: Skilled analytics professionals are in high demand. </li><li>High Costs: Hiring a skilled data analytics expert can be a significant expense. Outsourcing to vendors or consultants is often just as costly. </li><li>Quality Risks: Without attractive salaries or fees, agencies risk hiring average talent, leading to subpar models and results.</li></ul>We recently looked into an MMM service vendor called <a data-mce-href="https://www.cassandra.app/prices" href="https://www.cassandra.app/prices" target="_blank" rel="noopener">Cassandra</a>, and their pricing list reveals that their MMM services start at a minimum cost in the four-figure range.<figure id="figure-pxu1sdmiz8m5vqf4dz"><img id="pxu1sdmiz8m5vqf4dz" src="https://cdn.durable.co/blocks/4eRYlXPIKqOvl59OOFObOVuSJF6FDcXd5cSBwl7BppX396gLPCjcm99euLx96RTt.png" alt="mmm-cassandra-price" title="mmm-cassandra-price" class="object-cover bg-gray-100" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="Source: https://www.cassandra.app/prices" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/4eRYlXPIKqOvl59OOFObOVuSJF6FDcXd5cSBwl7BppX396gLPCjcm99euLx96RTt.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">Source: https://www.cassandra.app/prices</figcaption></figure>Another MMM service provider, <a data-mce-href="https://mass-analytics.com/marketing-mix-modeling-software-plans-mass-analytics/" href="https://mass-analytics.com/marketing-mix-modeling-software-plans-mass-analytics/" target="_blank" rel="noopener">Mass Analytics</a>, offers software-as-a-service solutions for users to build their own MMMs. However, their pricing is not listed publicly, suggesting it may not be a cost-effective or budget-friendly option.<figure id="figure-k511wau1odm5vqi2x3"><img id="k511wau1odm5vqi2x3" src="https://cdn.durable.co/blocks/10qOQ7i1WPEHgyclovSMFIUSXKqEEMa1ff5nyjvzUExeCmpJ41NLzTsslsQOvsCX.png" alt="mmm-mass-analytics-price" title="mmm-mass-analytics-price" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="Source: https://mass-analytics.com/marketing-mix-modeling-software-plans-mass-analytics/" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/10qOQ7i1WPEHgyclovSMFIUSXKqEEMa1ff5nyjvzUExeCmpJ41NLzTsslsQOvsCX.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"><figcaption class="body-normal text-gray-500 mt-2">Source: https://mass-analytics.com/marketing-mix-modeling-software-plans-mass-analytics/</figcaption></figure>For many small and medium-sized agencies, these barriers make MMM feel like an unattainable luxury.<h3>A Smarter Solution with More Than Data</h3>At <a data-mce-href="https://morethandata.biz/" href="https://morethandata.biz/" target="_blank" rel="noopener">More Than Data</a>, we believe that where there’s a will, there’s a way. That’s why we’ve created <a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank">Minute MMM</a>: a budget-friendly, easy-to-use, customizable, and fast MMM solution tailored to agencies of all sizes.With Minute MMM, you can:<ul><li>DIY your marketing mix models with ease. </li><li>Incorporate your unique industry knowledge for actionable insights. </li><li>Save time and reduce costs without sacrificing accuracy.</li></ul>If this sounds like the solution you’ve been waiting for, <a data-mce-href="https://morethandata.biz/contact-us" href="https://morethandata.biz/contact-us" target="_blank">let’s connect</a>! We’re here to make MMM accessible, effective, and affordable for all.

Building MMM the Traditional Way: Why It’s Way Too Expensive

Marketing Mix Modelling (MMM) is not a new concept. For over half a century, it’s been used to measure the impact of marketing and media efforts. Online, you’ll find countless blogs, articles, videos, and posts discussing MMM. Several vendors even offer SaaS solutions.Try a quick Google search using the keywords "<a data-mce-href="https://en.wikipedia.org/wiki/Marketing_mix_modeling" href="https://en.wikipedia.org/wiki/Marketing_mix_modeling" target="_blank" rel="noopener">Marketing Mix Modelling</a>" and see the countless results that pop up!<figure id="figure-knbld7bmfim5uer8lh" class=""><img id="knbld7bmfim5uer8lh" src="https://cdn.durable.co/blocks/30iFAjCOUQtX8xqwhdwearHMI4xno70n7kFsJlu11ilxSfs95gz3kg6DUkDcMegO.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/30iFAjCOUQtX8xqwhdwearHMI4xno70n7kFsJlu11ilxSfs95gz3kg6DUkDcMegO.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure>MMM is proven to work—helping agencies and marketers understand how their media mix drives results like sales. Yet surprisingly, very few media agencies actually use it. Why?Over the past few years, we’ve worked with small and medium-sized media agencies. While they were all familiar with MMM and its methodology, none had implemented it. Here’s why:<ul><li>High costs: Engaging with an MMM service vendor can cost five figures for a single KPI model.</li><li>Time-consuming: It takes weeks to collect, validate, and analyze data, then build, refine, and finalize models. </li><li>SaaS limitations: While cheaper, many SaaS platforms lack transparency, hide backend processes, or offer complex self-service tools that overwhelm non-technical users. </li><li>Outsourcing challenges: Outsourcing MMM isn’t practical for agencies needing continuous and up-to-date insights. </li><li>In-house constraints: Building an internal analytics team is expensive—hiring just one data scientist could cost $100K annually (In the Sydney labor market, an annual salary of $100K typically corresponds to a junior-to-mid-level analytics role), which many agencies can’t afford.</li></ul>We use <a data-mce-href="https://www.seek.com.au/" href="https://www.seek.com.au/" target="_blank" rel="noopener">SEEK</a>, the most popular job search engine in Australia, to browse data and analytics job opportunities in the Sydney market. By setting the salary band between $100K and $120K per year, we can find media measurement job opportunities listed <a data-mce-href="https://www.seek.com.au/analytics-jobs-in-advertising-arts-media/in-Sydney-NSW-2000?daterange=7&amp;salaryrange=100000-120000&amp;salarytype=annual&amp;sortmode=ListedDate&amp;jobId=81201582&amp;type=standard" href="https://www.seek.com.au/analytics-jobs-in-advertising-arts-media/in-Sydney-NSW-2000?daterange=7&amp;salaryrange=100000-120000&amp;salarytype=annual&amp;sortmode=ListedDate&amp;jobId=81201582&amp;type=standard" target="_blank" rel="noopener">there</a>. <figure id="figure-etkp9u7q44m5ufcg3e"><img id="etkp9u7q44m5ufcg3e" src="https://cdn.durable.co/blocks/1aTRgtViS6jBfYviOpoXac3akgREXtBhxZHOBhDOt7hviFZarflyNPcjwJCJV8T4.png" alt="" title="" class="object-cover bg-gray-100" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/1aTRgtViS6jBfYviOpoXac3akgREXtBhxZHOBhDOt7hviFZarflyNPcjwJCJV8T4.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><figure id="figure-yemlfmhmy9m5ufdgep"><img id="yemlfmhmy9m5ufdgep" src="https://cdn.durable.co/blocks/3btQ2bdxStUYkQWTNAfRhDBh6TaOqU9IHRXgzrd6sSFSGbK7ZAYakPRrQJr75xwH.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/3btQ2bdxStUYkQWTNAfRhDBh6TaOqU9IHRXgzrd6sSFSGbK7ZAYakPRrQJr75xwH.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure>However, how many small and medium-sized agencies in Australia can afford such analytics roles at the level of a Netflix-sized enterprise?In short, MMM has traditionally been expensive, time-consuming, overly complex, and inaccessible for small and medium-sized agencies.Can MMM Be Budget-Friendly, Transparent, and Easy? The answer is YES. That’s why we created <a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank">Minute MMM</a>—to make MMM acceptable and accessible to smaller agencies.<figure id="figure-cj866lgngqm5uetexh"><img id="cj866lgngqm5uetexh" src="https://cdn.durable.co/blocks/25U3FnpJV1JUB8ZvqfGqTpzo3LyTize2mg2fQGJolgU0tBh55rlS1ZyxY0NSap1t.png" alt="" title="" class="object-cover bg-gray-100 " style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/25U3FnpJV1JUB8ZvqfGqTpzo3LyTize2mg2fQGJolgU0tBh55rlS1ZyxY0NSap1t.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><ul><li>No cost: We don’t charge a single penny. </li><li>DIY-friendly: You’re in full control, customizing your models with ease. </li><li>Transparent: Your domain knowledge is part of the process. </li><li>Simplified: The process is streamlined, saving you time and effort. </li><li>Quick: Measure your media mix in just 10 minutes.</li></ul><a data-mce-href="https://morethandata.biz/minute-mmm" href="https://morethandata.biz/minute-mmm" target="_blank">Minute MMM</a> is designed to eliminate the barriers of traditional MMM, empowering agencies to integrate media measurement as part of their daily operations.If you’re tired of the challenges of MMM and want a solution tailored for your agency, <a data-mce-href="https://morethandata.biz/contact-us" href="https://morethandata.biz/contact-us" target="_blank">let’s connect</a>!

Why Small and Medium-Sized Media Agencies Haven’t Used MMM

Technology and communication network in city concept. Technology and media icon over city.

<h2>Introduction to Business Intelligence Tools</h2>
In today's fast-paced business world, the ability to make data-driven decisions is crucial for success. Companies in Sydney, like in many other major cities, rely heavily on business intelligence (BI) tools to analyze data and gain insights into their operations. These tools help organizations turn raw data into actionable insights, enhancing performance and strategic decision-making.

Business intelligence tools are designed to help businesses collect, process, and analyze large volumes of data efficiently. By using these tools, companies can identify trends, uncover patterns, and make informed decisions that drive growth and profitability.

<figure id="figure-ku2dgi4svm5t4ve7s"><img id="ku2dgi4svm5t4ve7s" src="https://media.gettyimages.com/id/1954841243/photo/data-analysis-chart-graph-3d-statistics-background.jpg?b=1&s=2048x2048&w=0&k=20&c=JqlWDrRuqpKotSJiWlw9XEKfqmlar9qw3g5TGMGWdVk=" alt="data analysis" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

<h2>Top BI Tools Used in Sydney</h2>
Sydney's business landscape is diverse, and so are the BI tools used by professionals in the region. Here are some of the top business intelligence tools available in Sydney:

<ul>
 <li>Tableau: Known for its powerful data visualization capabilities, Tableau allows users to create interactive and shareable dashboards that showcase trends and insights.</li>
 <li>Microsoft Power BI: This tool offers robust reporting and analysis features, integrating seamlessly with other Microsoft products to provide a comprehensive BI solution.</li>
 <li>Sisense: An intuitive platform that combines data from multiple sources to deliver deep insights through interactive dashboards and reports.</li>
</ul>

<h2>Key Features to Consider</h2>
When selecting a BI tool, it's important to consider the specific features that will best meet your organization's needs. Some key features to look for include:

<ol>
 <li>Data Connectivity: The ability to connect to various data sources is essential for comprehensive analysis.</li>
 <li>Ease of Use: User-friendly interfaces make it easier for non-technical users to generate reports and insights.</li>
 <li>Customization Options: Flexible tools allow businesses to tailor reports and dashboards to their specific requirements.</li>
</ol>

<h2>The Importance of Data Visualization</h2>
Data visualization is a critical component of any BI tool. It transforms complex data sets into easy-to-understand visuals, making it easier for stakeholders to grasp key insights. Effective visualizations can reveal patterns and trends that might otherwise go unnoticed.

<figure id="figure-h6930gdkvim5t4ve7s"><img id="h6930gdkvim5t4ve7s" src="https://media.gettyimages.com/id/2096475191/photo/data-analytics-automated-with-ai-technology-big-data-business-analytics-and-artificial.jpg?b=1&s=2048x2048&w=0&k=20&c=oPpIjc9QyOBlajkf-NkhIN8XRVJCpyVMKeMi75Um__U=" alt="data visualization" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

Sydney businesses often rely on tools like Tableau and Power BI because they excel in providing rich visual representations of data. These tools enable users to create dynamic charts, graphs, and maps that facilitate better understanding and communication of data-driven insights.

<h2>Integrating BI Tools into Business Strategy</h2>
Integrating business intelligence tools into your company's strategy can significantly enhance decision-making processes. By incorporating BI solutions, businesses can:

<ul>
 <li>Improve Operational Efficiency: Identify areas for improvement and streamline processes.</li>
 <li>Enhance Customer Experience: Analyze customer data to tailor services and products.</li>
 <li>Drive Revenue Growth: Uncover new opportunities and optimize sales strategies.</li>
</ul>

<h2>The Future of BI Tools in Sydney</h2>
As technology continues to evolve, so too will business intelligence tools. Emerging trends such as artificial intelligence (AI) and machine learning are set to enhance the capabilities of BI platforms, offering even deeper insights and predictive analytics.

<figure id="figure-am0gtciv6um5t4ve7s"><img id="am0gtciv6um5t4ve7s" src="https://media.gettyimages.com/id/79327759/photo/woman-with-a-french-bulldog.jpg?b=1&s=2048x2048&w=0&k=20&c=7AOUbTqYuDAEkY5D2NHD2rImVNr5y82Re5yvRnta78M=" alt="business technology" class="object-cover bg-gray-100" style="aspect-ratio: 16/9"></figure>

Sydney's businesses are well-positioned to leverage these advancements, ensuring they remain competitive in a rapidly changing market. By staying ahead of the curve, organizations can harness the full potential of their data to drive innovation and success.

<h2>Conclusion</h2>
Business intelligence tools are indispensable for companies looking to thrive in Sydney's dynamic business environment. By choosing the right BI solution and integrating it into their strategy, organizations can unlock valuable insights that lead to better decision-making and improved performance. Whether you're a small startup or a large corporation, investing in BI tools is a step towards a more informed and successful future.

Exploring Top Business Intelligence Tools Available in Sydney

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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This website delivers the media measurement &amp; budget optimization tools that big MMM providers charge premium prices for—only now, they're free.

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Why Traditional SaaS Solutions for Marketing Mix Modellin...

How Sydney Marketers Can Leverage AI for Better Customer ...

Building MMM the Traditional Way: Why It’s So Time-Consuming

Building MMM the Traditional Way: Why It’s Way Too Expensive

Why Small and Medium-Sized Media Agencies Haven’t Used MMM

Exploring Top Business Intelligence Tools Available in Sy...