Navigating the analytical supply-demand imbalance in marketing

The paradox of today's marketing: with the excess of available data, the need for more useful insights is growing. This imbalance between supply and demand continues to intensify. Therefore, the key is to build bridges between analytical supply and demand. In this article, we discuss these bridges.

1. The Paradox of Abundance

In modern marketing, we all have access to more data than ever before. Dashboards, reports, audiences, clicks, views, cookies, tags, CRM, CDP, DMP, GA4. The problem is no longer a lack of information.

The real challenge is another: the disconnect between the excess of available data (supply) and the growing need for useful answers (demand).

We live in a kind of paradox of abundance: while brands invest more in technology and data accumulation, marketing teams continue to ask the same question: How do I translate all this into actionable decisions?

To understand why this happens, we need to analyze three key elements:

• the supply of data,
• the demand for insights,
• and the bridge that needs to be built between the two.

2. Data Supply: The Triple V Syndrome

In 2001, Doug Laney defined the "3 Vs" of Big Data: Volume, Velocity, and Variety. More than two decades later, these three vectors remain at the heart of the problem:

1. Volume: More data is generated every day. Since 2020, the volume of data a marketing team manages has increased 2.3-fold, according to Supermetrics.
2. Velocity: Data arrives in real time, and decisions must also be made in real time.
3. Variety: Data no longer comes only from campaigns. It comes from social media, weather, political context, customer experiences, and even conversations with AI.

The problem is that, without a clear strategy, these 3 Vs don't add value. Rather, they generate noise. As Gartner notes in its Analytics Maturity Report (2024): “87% of organizations have low analytics maturity, despite having invested in sophisticated tools.”

The offering is growing, but it doesn't always have an integration plan, an interpretation strategy, or a culture of evidence-based decisions.

3. The Demand for Insights: Analytical Maturity vs. Operational Urgency

Now let's talk about the other side of the coin.

As the data supply explodes, the demand for insights becomes more sophisticated and more urgent. CMOs, CEOs, and marketing teams don't want more reports. They want answers.

• Which channel should I prioritize if I cut budget?
• Which campaign generated the most incremental sales?
• What will happen to my funnel if purchasing behavior changes?

Answering these questions requires a journey of analytical maturity. We explain it with a five-level pyramid:

Analytics Maturity Pyramid:

1. Basic Analytics / Simple Last-Click Attribution
2. Segmentation and Descriptive Metrics
3. Multi-Channel Models / Advanced Data-Driven Attribution
4. Predictive Models / Machine Learning
5. Prescriptive Models / Marketing Mix Modeling

This shift is clearly evident in the Supermetrics 2025 study, where the most sought-after solutions are:

• MMM (Marketing Mix Modeling): 47%
• Forecasting & Predictive Analytics: 40%
• ROI Analysis and CLV: 39% and 28%

McKinsey summarizes it this way: “Organizations that invest in predictive insights increase their marketing ROI by 20%.” Meanwhile, methods such as CPA tracking or A/B testing, which dominated digital marketing for years, are declining in priority.

4. Structural mismatch

So far, everything seems logical: more data, more expectation for insights.

But in practice, what we find is a mismatch. Because the growth rate of supply (more dashboards, more KPIs, more tools) doesn't keep pace with the maturation of demand.

This creates a phenomenon that is repeated in many organizations:

The solution isn't to keep accumulating tools. It's to start building bridges.

5. The Bridge: Analytical Capabilities as Strategic Infrastructure

There's a gap between the supply of data and the demand for insights. That gap is filled with analytical capabilities. We call this the bridge.

It's not a product. It's a combination of culture, processes, talent, and technology that enables data to be transformed into useful answers.

These are some of the bridge's key capabilities:

• Unified integration of sources
• Autonomous access to insights (without relying on analysts for everything)
• Reporting automation
• Actionable visualizations (that not only inform, but also guide)
• Adaptive prediction models
• A culture of experimentation and testing

Ultimately, the bridge is the invisible infrastructure that enables the promise of data to be transformed into real value.

6. Conclusion: cultivating insights, not accumulating data

Marketing doesn't need more tools. It needs better analytical thinking.

True transformation occurs when we stop collecting data like trophies and start cultivating insights like food: with care, with purpose, and with a system that makes them sustainable.

Because it's not just about having data. It's about knowing what to do with it.

And to do that, building a bridge between supply and demand isn't optional. It's strategic.

How is your organization today? Is it on the supply side, trapped in dashboards? Or on the demand side, pressured to respond without clarity?

Maturity isn't about having it all, but knowing how to use just the right amount. That's true insight.

References

1. Gartner. (2024). Analytics and Business Intelligence Platforms. Retrieved from https://www.gartner.com/en/newsroom
2. Supermetrics. (2025). Marketing Data Report. Retrieved from https://supermetrics.com/blog/marketing-data-report-2025
3. McKinsey & Company. (2023). The state of AI in 2023: Generative AI’s breakout year. Retrieved from https://www.mckinsey.com/capabilities/quantumblack/our-insights