2025年3月7日
Eimear Colleran
It’s no secret that marketing is evolving rapidly, with data playing a more critical role than ever in shaping strategies. In 2025, Marketing Mix Modeling (MMM) has become one of the most talked about topics in the industry, as brands and agencies seek more effective ways to measure performance and optimise marketing spend. While MMM has long been a staple in marketing analytics, its shortcomings are becoming harder to ignore. To remain competitive, marketers must embrace a more flexible and responsive approach that aligns with today’s digital landscape. This enables them to keep pace with rapidly shifting consumer behaviours, evolving media channels and even world events.
The rising reliance on and investment in marketing analytics
The global marketing analytics software market has been experiencing significant growth and is projected to continue expanding in the coming years. According to a report by Grand View Research the market was valued at approximately USD 3.78 billion in 2022 and is expected to reach around USD 12.51 billion by 2030. However, despite this surge in investment, many marketers remain frustrated with the tools currently at their disposal. The demand for real-time, data-driven experimentation continues to grow, yet traditional MMM tools often fall short of delivering the agility and precision required by marketing teams today.
The limitations of traditional MMM
Traditional MMMs face several challenges that impact marketing effectiveness:
Historical dependence
MMMs primarily rely on historical data to forecast future trends. While this approach offers a foundation based on past performance, it can limit a company's ability to adapt swiftly to emerging market dynamics. As highlighted by Harvard Business School, financial forecasting often involves predicting a company's future by examining historical performance data, such as revenue, cash flow, expenses, or sales. However, an over reliance on historical data can make it challenging to respond promptly to unexpected disruptions or rapidly evolving consumer behaviours. To enhance adaptability, organisations must integrate real-time data and advanced analytics into their forecasting models, enabling more responsive and proactive decision-making.
Lack of granularity
Marketers need more immediate insights, but traditional MMMs often analyse data over extended periods, such as weeks or months, which can hinder a marketing team’s ability to obtain immediate and actionable insights. This lack of granularity makes real-time performance tracking challenging, limiting marketers' capacity to respond swiftly to market changes. This Forrester study emphasises the importance of timely, accurate, and granular data for effective marketing measurement and optimisation.
The demand for more detailed insights is driven by the need to make faster, data-driven decisions in a rapidly evolving marketplace. Without granular data, marketers may struggle to identify specific factors influencing campaign performance, leading to less informed strategies and potential missed opportunities.
Therefore, integrating tools and methodologies that provide real-time, detailed analytics is essential for enhancing marketing effectiveness and agility.
Slow turnaround
Many traditional MMM projects take months to move from data collection to actionable insights, creating delays that hinder marketers from making timely decisions. This challenge is exacerbated by rapidly shifting market conditions, where speed and agility are crucial. According to eMarketer, 61.4% of marketers are seeking faster and more effective MMM solutions to better adapt to dynamic consumer behaviours and optimise campaign performance in real-time. Without more responsive analytics, businesses risk falling behind competitors who can swiftly adjust their marketing strategies based on real-time insights.
Attribution challenges
Nielsen’s 2023 Annual Marketing Report reveals that only 54% of marketers are confident in measuring ROI across digital channels, underscoring a broader concern around attribution accuracy. Many traditional MMM models struggle to account for the complexities of multi-touch consumer journeys, where multiple marketing channels contribute to conversions.
As marketing strategies become more integrated across digital and offline platforms, the need for more precise and holistic attribution models is greater than ever. Many traditional models struggle to account for the complexities of multi-touch consumer journeys, where multiple marketing channels contribute to conversions.
This challenge is particularly evident in the debate over last-click attribution, which often oversimplifies how credit is assigned to different touch points. As marketing strategies become more integrated across digital and offline platforms, the need for more precise and holistic attribution models is greater than ever.
Complexity
A 2022 Gartner report found that 68% of marketing teams struggle with a skills gap in advanced data modelling, creating bottlenecks in decision-making. Historically, marketing was a domain for creative minds, those who thrived on storytelling, branding, and emotional connection. Today, however, the field has become increasingly data-driven, requiring proficiency in analytics, statistical modelling and machine learning. This shift has left many traditional marketers feeling unprepared, as data-focused roles dominate the industry. The growing need for technical skills has widened the gap between creative strategists and 'data nerds,' making it harder for marketing teams to operate effectively without investing in specialised expertise or accessible, user-friendly analytics tools.
Lack of adaptability
The COVID-19 pandemic not only shut down the world and made people sick, it also exposed the limitations of rigid MMM models. The rapid shifts in consumer behaviour, supply chain disruptions, and budget reallocations rendered traditional MMM approaches ineffective. This highlighted the need for marketing models that can quickly adjust to external shocks and evolving market conditions. In today’s landscape, flexibility is no longer a luxury, it’s a necessity. Marketers require adaptive models that incorporate real-time data, scenario planning, and agile decision-making to remain effective in an unpredictable environment.
Media fragmentation
The modern marketing landscape is more fragmented than ever, with brands needing to engage consumers across numerous channels, from traditional TV and print to digital, social media, streaming platforms, and emerging spaces like the metaverse.
A survey by LiveRamp revealed that 97% of marketers face challenges in assessing their marketing impact due to data fragmentation across various tools and platforms. This challenge is compounded by the walled gardens of major digital platforms, making attribution even more complex. Marketers need holistic measurement solutions that can integrate data from various sources, providing a clearer picture of how different touchpoints contribute to overall brand and campaign performance.
Difficult reporting
A survey by Ascend2 found that 64% of marketers want clearer, more intuitive reporting from their analytics tools. As marketing data becomes increasingly complex, teams struggle to extract meaningful insights from overwhelming dashboards and dense reports. The challenge isn’t just access to data, it’s the ability to interpret it quickly and effectively. Many marketers, particularly those without deep analytical expertise, find current reporting tools cumbersome and difficult to navigate. The growing demand for simplified, customisable, and visually engaging analytics platforms underscores the need for solutions that translate raw data into actionable insights, enabling marketers to make informed decisions with confidence and speed.
Inflexible strategies
Relying too heavily on past performance can stifle innovation and prevent marketers from capitalising on new opportunities. According to Boston Consulting Group, companies that integrate effective human processes with data-driven capabilities can boost marketing effectiveness by 10 to 25 percentage points in terms of EBITDA gains relative to marketing spending. This underscores the significant opportunity cost of maintaining rigid marketing strategies in a rapidly evolving landscape.
In an environment where consumer behaviours, digital trends, and competitive landscapes are constantly shifting, sticking to what has worked before can lead to diminishing returns. A lack of flexibility prevents brands from experimenting with emerging channels, optimising budget allocation in real-time, or adapting to shifts in customer preferences.
The most effective marketing strategies today integrate agility, data-driven experimentation, and the ability to pivot quickly in response to market dynamics. Without this adaptability, businesses risk falling behind their more nimble competitors.
The next generation of MMM
As marketers demand more accurate and real-time insights, a new generation of tools is emerging to redefine how businesses measure and optimise their marketing investments. Prophet is addressing these needs by offering an advanced, data-driven approach that goes beyond the limitations of traditional MMM. The Gartner CMO Spend Survey 2024 reports that 78% of enterprise CMOs plan to increase their analytics budgets, reflecting the urgent need for tools that provide deeper, more actionable insights and predictive capabilities.
Prophet empowers marketers with proactive, insight-driven strategies by eliminating uncertainty and enabling real-time optimisation. At its core, Prophet builds sophisticated digital models that mirror real-world business dynamics, allowing marketers to test, refine, and optimise strategies in a risk-free environment before launching them in the real world.
What sets Prophet apart
Advanced modelling: Prophet leverages ARIMA, Bayesian, and SeM techniques to run multiple predictive scenarios, enabling marketers to evaluate strategies before making high-stakes decisions.
Seamless integrations: Prophet connects directly with CRM systems, eCommerce platforms, finance operations, and supply chains to provide a comprehensive view of marketing performance and its business impact.
User-friendly experimentation: Prophet has a no-code interface that allows marketers to run experiments and refine strategies in real-time, without requiring advanced data science expertise.
By integrating historical insights with predictive analytics and real-time adaptability, Prophet helps marketers navigate an increasingly complex landscape. Its machine learning and statistical modelling uncover hidden patterns, anticipate market shifts, and recommend optimal budget allocations.
Prophet ingests three core data streams - marketing and media data, organisational and commercial data, and then layers them with 86,000 macroeconomic and behavioural data points - to create a precise digital model of a business. This enables users to conduct advanced simulations, test various marketing and commercial scenarios, and evaluate potential outcomes before making real-world changes. By providing a structured, data-driven way to measure upper- and middle-funnel activities, Prophet not only clarifies channel ROI but also illustrates how different elements within the marketing ecosystem interact.
The future of marketing analytics
Traditional MMM, while still somewhat valuable, must evolve to meet today’s need for deeper insights, greater flexibility, and faster decision-making. The best approach blends established methodologies with modern tools that remove complexity and provide real-time, actionable insights.
This need is why Prophet was created - to move beyond retrospective analysis and instead simulate, predict, and optimise performance dynamically. Today, relying on static models that take months to update is no longer enough. Businesses need a solution that delivers both precision and speed to enable smarter, faster decisions.
This approach represents a fundamental shift, moving beyond simple attribution models to a dynamic, mathematical representation of the marketing funnel. For the first time, brands can build business cases demonstrating how middle and upper-funnel activities contribute to long-term success. This ensures marketing is no longer viewed as a cost centre but as a strategic driver of business growth.
With Prophet, businesses no longer have to choose between precision and speed.
Advancements in mathematics, machine learning, and AI allow organisations to test hypotheses, adjust marketing investments, and explore commercial scenarios in a controlled environment, optimising strategies with confidence.
Marketing should be effective and intuitive. With Prophet, teams can move beyond navigating complex analytics and instead focus on creativity, strategy, and driving growth with clarity and confidence.
