Alternative Data: What Is It, Who Uses It And Why It Matters

Often in business, staying ahead means looking beyond the obvious.

Alternative data, derived from non-traditional sources, offers a depth and uniqueness that traditional data sources can lack.

In this blog, we’ll cover what alternative data is, how it differs from traditional data, who uses it, its role in business, and the pros and cons of integrating it into decision-making.

Table of Contents

Jump ahead ↓

• What is Alternative Data?
• What is the Difference between Alternative and Traditional Data?
• Who uses Alternative Data?
• Pros and Cons of Alternative Data
• The True Value of Alternative Data

What Is Alternative Data?

Alternative data (or Alt data) refers to non-traditional data sources that provide unique insights and information not typically captured by conventional data sets. The depth, detail, variety and uniqueness of alternative data are what make it a source of insight.

Examples include:

• Social media sentiment analysis
• Geolocation data tracking foot traffic
• Credit card transaction volumes
• Satellite imagery
• Drone imagery
• Wearable tech data
• Web traffic data
• Mobile app usage statistics
• IoT sensor data
• Product reviews
• Weather data*
• Flight data
• App usage
• ESG (environmental, social and corporate governance) data
• Market prices*
• Company filings*
• Jet tracking

*Alternative data is context-dependent, and what is considered “alternative” in one domain may be traditional in another.

Alternative data is far from a new concept. Pre-digital signals, astute business people have sought to understand their trading environments by observing the world through different lenses. These observations often generated insights—data that, while not traditional, provided a valuable edge in navigating markets effectively.

What has changed in recent years is the remarkable accessibility of alternative data, driven by technological advancements across industries. This progress has expanded the volume and variety of data, making it easier for businesses to derive insights and make more informed decisions.

Source: Casting the Net

What is the Difference Between Alternative and Traditional Data?

Traditional data comes from established, conventional sources like financial statements, government reports and structured databases. It is typically well-organised and standardised.

Alternative data comes from unconventional, non-traditional sources. It is often unstructured or semi-structured, and thus less readily accessible or usable, and not easily searchable.

It generally requires advanced processing techniques, as well as the ability to link seemingly unrelated pieces of information to develop a holistic understanding or derive meaningful insights. Additionally, larger-scale datasets may necessitate substantial computational power and storage.

Who Uses Alternative Data?

Alternative data is often used by hedge funds, private equity firms, investment banks and retail investors to gain insights and identify opportunities beyond traditional data sources.

It is commonly used to:

• Uncover potential risks not evident from traditional financial data.
• Conduct stress tests and scenario analyses.
• Identify and manage tail risks.
• Discover new investment opportunities.
• Reduce information asymmetry.
• Optimise portfolio construction.

Other specific examples include:

• Environmental, Social and Governance (ESG)
  Alternative data like social media sentiment and news can be used to assess companies’ environmental, social, and governance (ESG) performance which can help investors incorporate ESG factors into decision-making.
• Fintech
  Alternative data can also be used by fintech firms to offer tailored financial advice, identify potential customers and develop innovative investment products accessible to retail investors.

Pros & Cons of Using Alternative Data

Pros

By using unconventional insights, businesses and investors can uncover opportunities and sharpen their strategies using alternative data. Here’s how it can help deliver an edge:

• Richer Context

Alt data provides additional data points of a business’s performance beyond traditional sources. When analysed holistically, it can potentially offer a more complete understanding of business performance and customer loyalty.

• Decisions Backed by Historical Trends

The access to historical data enables predictive analysis, helping anticipate outcomes, identify opportunities and avoid potential risks.

• Improved Investments and Partnerships

A broader range of data points allows businesses to assess compatibility with potential partners and make more strategic, mutually beneficial investment decisions.

• Enhanced Customer Relationships

Data on customer feedback, web traffic and audience demographics helps businesses refine strategies to improve customer satisfaction and loyalty.

• Competitive Advantage

Real-time insights allow quicker, more informed decisions, helping businesses stay ahead of competitors reliant on traditional data.

Cons

While alternative data offers exciting possibilities, it’s not without its hurdles. Effectively leveraging these unconventional insights requires addressing some critical challenges. Here are the key drawbacks businesses might consider:

• Inconsistent Data Quality

Due to the wide variety and the varied applications, alt data is hard to regulate. It can come aggregated or as a straight data feed. The lack of standardisation and rules around alt data means these types of data sets may contain errors, which can lead to misinterpretations which, in turn, affects decision-making.

• Transparency and Ethical Concerns

Certain types of data and data collection methods, such as tracking GPS or online activity, may erode consumer trust if it is seen as invasive or unethical.

• Privacy, Security and Regulatory Compliance

Sensitive data usage exposes businesses to breaches, legal violations and potential harm to individuals. This can pose serious risks to a brand’s reputation and business compliance.

As the use of alternative data grows, so too does regulatory scrutiny. Organisations must ensure that data collection, processing and usage align with evolving privacy laws and compliance frameworks across jurisdictions. Failure to do so can result in significant financial penalties, reputational damage and loss of customer trust.

Key regulations shaping the use of alternative data include:

• • GDPR (EU): Strict requirements around consent, processing and data rights
  • CCPA (US): Greater consumer control over personal data usage
  • Australia Privacy Act: Standards for handling personal information, with increasing enforcement focus

This is particularly relevant for alternative data sources such as geolocation tracking and behavioural datasets, where re-identification risks can arise.

• Discrimination and Bias Risks

Using personal demographics in decision-making can lead to unintentional discrimination, flawed data sets and long-term reputational damage.

• Manipulated Data Variables

Publicly available data can sometimes be intentionally skewed to serve specific interests—businesses might highlight only positive reviews, while individuals may curate information to boost their credibility. This highlights the importance of adopting a comprehensive approach, drawing from a diverse range of data channels rather than relying on a single source.

When Should You Use Alternative Data?

While alternative data offers powerful possibilities, it’s not always necessary.

The real value comes from using it strategically, when it can meaningfully enhance decision-making beyond traditional sources.

Businesses should consider alternative data when:

• Internal data is insufficient: When existing datasets don’t provide a complete view of customers, markets or operations.
• Timeliness matters: When real-time or near real-time insights are needed to respond quickly to market changes.
• Competitive differentiation is critical: When gaining an informational edge can materially impact outcomes, such as in investment, site selection or customer targeting.

In these scenarios, alternative data acts as a complementary layer: augmenting, rather than replacing, traditional data sources.

Turning Alternative Data into Actionable Insight

Accessing alternative data is only part of the equation. Deriving value from it requires the right data architecture.

To operationalise alternative data effectively, organisations need to:

• Ingest and standardise diverse data sources: Bringing together structured and unstructured datasets from multiple providers
• Integrate with existing platforms: Connecting alternative data with internal systems such as CRM, ERP or data warehouses 
• Establish strong data governance: Ensuring data quality, lineage, compliance and usability across the organisation

Without these foundations, even the most valuable data sources can fail to deliver meaningful business outcomes.

The True Value of Alternative Data

Alternative or alt data offers deeper insights, empowering businesses and investors to make more informed decisions and gain a competitive edge.

As accessibility to alt data continues to grow, so do the opportunities to utilise its potential in creative and transformative ways.

But challenges like data quality, transparency and privacy means that alt data requires careful management.

By adopting a thoughtful and ethical approach, progressive businesses can tap into alt data’s inherent value to inspire smarter investments, spark innovations and possibly even deliver groundbreaking solutions.

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