Introduction

Over the past decade, alternative data has become a core input in modern investment analysis. Transaction feeds, web traffic, geolocation data, and digital behavior signals now inform everything from short-term trades to long-term portfolio strategy.

As alternative data has grown in importance, some observers have suggested that traditional market research has become less relevant. In practice, leading investment organizations have learned the opposite.

Alternative data shows what is happening.
Market research explains why it is happening.
Together, they support better judgment.

Recent studies indicate that over half of investment firms conduct primary B2B research and more than four in ten conduct primary consumer research. Let’s go into more detail on why both methods are essential to getting the full picture.

What Alternative Data Delivers

Alternative data refers to nontraditional datasets that provide insight into economic activity, company performance, and consumer behavior. These include:

• Transaction data
• Web and app usage
• Mobility data
• Satellite imagery
• Supply chain signals

These sources are timely, scalable, and behavior-based. They reflect what people actually do, rather than what they say. For investors, this enables early detection of revenue trends, shifts in demand, operational bottlenecks, and emerging risks.

However, alternative data describes activity over intention and measures outcomes over motivations. Without interpretation, it remains incomplete.

What Market Research Reveals

Market research focuses on understanding how decision-makers think, evaluate risk, form expectations, and choose between competing alternatives. While alternative data captures behavior at scale, research uncovers the reasoning that leads to that behavior.

Through structured surveys, in-depth interviews, and longitudinal studies, research provides visibility into factors that are largely invisible in behavioral datasets, including:

• How pricing changes are interpreted
• Which features or services are truly valued
• Where trust is strengthened or weakened
• How switching decisions are justified internally
• What risks are perceived as material
• Which trade-offs influence final outcomes

These elements often determine long-term performance more than short-term usage patterns.

For example, a decline in engagement may reflect dissatisfaction, rising competitive pressure, internal budget constraints, or shifting strategic priorities. Transaction data alone cannot distinguish between these drivers. Market research makes those distinctions explicit.

Research also captures forward-looking signals that behavioral data cannot yet show. Intent, confidence, and expectations often shift before behavior follows. Understanding these early indicators allows organizations to anticipate change rather than simply react to it.

Importantly, market research provides a structured way to test assumptions. It allows hypotheses to be evaluated directly with relevant decision-makers, reducing reliance on inference and speculation.

In this way, market research functions as both an explanatory and a risk-management tool.

The Central Gap: Data Without Explanation

Alternative data answers what is happening. Market research answers why.

Without both, organizations risk misinterpretation and false certainty.

Relying on behavioral signals alone can lead to overreaction to short-term noise, misattribution of causes, and premature conclusions. Research provides the context needed to distinguish between temporary disruption and structural change.

How Leading Firms Integrate Both Sources

Top firms aren’t relying on just one source or they other. They’re gathering both and interpreting them together to get the full picture.

Here’s how:

• High-performing investment teams use alternative data and market research in coordinated ways.
• Behavioral data identifies emerging patterns. Research determines whether those patterns are sustainable.
• Usage changes signal that something has shifted. Research explains what triggered the shift.
• Comparing stated intent with observed behavior improves forecasting and risk modeling.
• Operational and financial data show exposure. Research reveals sentiment and reputational risk.

Why Investment Firms Adopted This Model First

As alternative data became widely available, access alone stopped being a competitive advantage. Interpretation became the differentiator.

Data saturation increased the risk of misreads and herding behavior. Human judgment supported by structured research became more important, not less.

The Human Layer in Market Signals

Markets are driven by perception, confidence, trust, and narrative. Regulation, reputation, and leadership credibility shape capital flows.

Market research captures these dynamics directly. Alternative data reflects them indirectly. Understanding both is essential.

Implications for Investment Leaders

Leaders should avoid single-source conclusions, invest in interpretation, treat research as risk management, and build integrated intelligence systems.

Confidence should rise with corroboration, not volume.

A Practical Framework for Integrating Alternative Data and Market Research

1. Start with clear decision questions. Define the strategic or investment question before collecting data.
2. Use alternative data for detection vs. explanation. Use behavioral data to identify where and how change is occurring.
3. Use market research for interpretation and validation. Apply research to understand causal drivers and assess durability.
4. Compare stated intent with observed behavior. Evaluate gaps between what people say and what they do.
5. Integrate insights at the portfolio level. Synthesize financial, behavioral, and attitudinal inputs.
6. Establish governance and review processes. Document assumptions and track forecast accuracy.
7. Treat interpretation as a core capability. Invest in analytical judgment and research literacy.