Alternative Data

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FAQs

What is Alternative Data?

Alternative data is any data that is gathered from nontraditional sources. For investors and companies, this is any financial data beyond company filings, press releases, earnings reports, and broker research.

This kind of data is valuable because it provides a much more granular view of a market, industry, or trend and often contains critical insights that will help an investor make more accurate and well-informed investment decisions and generate alpha. Because not all companies or investors rely on alternative data, it can also help those that do use it to stay ahead of the curve, anticipate market trends before they happen, and see opportunities they would otherwise miss if they were only relying on traditional data.

What Are the Types of Alternative Data?

There are three main subsets of alternative data:

Generated through individuals
Generated through business processes
Generated by sensors

Let’s go through each one in more detail.

Individuals

For the most part, data generated by individuals is unstructured. It comes primarily from social media, web traffic, and app usage, and it provides key insights into consumer sentiment and behavior. The insights from this data are integral for brands to understand brand performance and increase customer loyalty.

Individual-generated alternative data also encompasses expert interviews, such as those that can be found in an expert call transcript library.

Expert Insights is an expert call transcript library for financial services and corporate professionals, housed within the AlphaSense platform. It offers first-hand perspectives from seasoned subject matter experts—such as thought leaders, former executives, customers, competitors, and partners—from a specific company or industry that would otherwise be inaccessible to professionals.

Another example of individual-generated alternative data is sentiment—social and market. If an investor or corporate professional is simply relying on mention counts as they skim a particular company’s documents and transcripts, they may risk missing the underlying meaning in what is being said about a topic. Sentiment is key to understanding the nuance behind what an executive leader, news source, or customer is saying—which can help with strategy and smarter decision-making.

But sentiment can be challenging for humans to always get right, particularly when working with pages and pages of data. Sentiment analysis is a natural language processing (NLP)-based feature that automatically parses out the tone and language nuance in a given document and helps you quickly pick up on the subtext of what is being said. Sentiment analysis is built into the AlphaSense platform, so you can easily recognize the positive, neutral, or negative sentiment in the source you are analyzing, and use that knowledge to make more informed decisions.

To learn more about Expert Insights, or to start your free trial with AlphaSense, click here.

Business Processes

This is data that businesses generate and includes bank records, commercial transactions, credit card transaction records, and data from government agencies. This data is usually structured and provides a good indication of business performance and company sales forecasts.

Sensors

Alternative data gathered from satellite images, weather forecasts, and geolocation falls into this category. This data is unstructured, and it can be used to give companies insight into consumer behavior and sociological patterns. Examples include foot traffic, property details, and a business’s ambiance environment—all of which can be helpful for investors looking to gain insight into the profitability of an opportunity.

What are the main use cases for alternative data?

Alternative data is useful because it’s immediate, frequently updated, and provides added context to certain trends or performance indicators that are otherwise ambiguous. It is most often used by scrappy investors looking for outside-the-box investment strategies, but it can also be highly useful for corporations and private equity firms to gain a better sense of the market and make strategic decisions.

Here are some of the most common use cases:

Due Diligence

Buy-side analysts use alternative data to validate a potential investment and gain a 360 degree view of all potential benefits and risks associated with that investment. Expert calls are particularly useful here, as industry experts are often able to shed light on the inner workings of a company or industry and offer a perspective you won’t find anywhere else.

Portfolio Management

When keeping tabs on assets and investments, timeliness is the name of the game. Alternative data sources provide frequent and timely updates, allowing analysts to spot, assess, and take action on any changes quickly before they result in a huge loss.

The AlphaSense platform takes this a step further, allowing you to set up alerts and watch lists for specific companies and topics, so that you are notified immediately when anything in your portfolio requires your attention.

Competitive Landscaping

Alternative data can fill in the gaps in competitive research, whether you are a corporation looking to build a winning strategy, or a sell-side investor trying to get the full picture of a market before your competition does. Because alternative data is current and updated more frequently than traditional financial data, it can empower more informed decision making and give you a competitive edge.

Alt data such as social media commentary, smartphone geolocation data, and product reviews can help with strategic idea generation and keeping tabs on competitors. Beyond those alt data sources, expert calls are conducted by buy-side analysts, so you can be sure they go deep on what matters. Competitive moats, tech stacks, industry headwinds and tailwinds—and most importantly, they ask the questions you didn’t think to ask.

Deal Sourcing

Buy-side analysts, private equity firms, and hedge funds use alternative data to help them find deals with the biggest potential ROI and smallest risk. Consumer data like foot traffic, social media activity, and purchasing preferences (gleaned by web scraping and social listening tools) can give insight into how consumers truly feel about a business, and how the business stacks up against its competitors.

AlphaSense helps you discover winning investment opportunities faster with our patented AI search technology, which allows you to bypass any irrelevant data and get to the most crucial insights, no matter the document or source you are perusing. Expert transcripts also equip you with every perspective you need to make the most informed decision on a potential investment.

Forecasting & Risk Management

Alternative data offers one of the best ways to keep ahead of stock price movement and assess the risks associated with a particular public company. Online social sentiment and transaction data provide quick and current insight into how a company is performing or how it may be affected by certain social trends or movements.

Expert Insights can be particularly useful in predicting outcomes for particular companies. These experts have been there and can contextualize raw data and explain whether or to what extent a particular market-moving event can affect your bottom line.

Alternative Data Frequently Asked Questions

What is the difference between alternative data and traditional data?

In the investment world, traditional data is normally distributed by the firm’s investor relations department and includes financial statements, earnings calls, investment management guidance, fundamental data sets, company presentations, and broker research.

Alternative data encompasses all financial data sources outside of these that contain information capable of moving market share prices–common examples include social media, expert call transcripts, product reviews, and satellite imagery.

Who can benefit from using alternative data?

Historically, alternative data was catered toward wealthy traders, and its steep cost only made it accessible to hedge funds. In today’s age, alternative data is used by investment firms around the world, as well as corporations and private equity firms.

Algorithmic traders, aka quants, at investment firms rely on alternative data to build models for trading equities. Corporations base many of their strategic decisions on insights gleaned from alternative data, and private equity firms rely on alternative data to assess targets and close new deals.

“Companies and consultants are beginning to turn to these newer alt data sets, like transaction data and web pricing data, to fill in their data mosaic and gain a fuller understanding of their markets.” – Michael Maloof, Earnest Analytics, in discussion with Nick Mazing, Director of Research at AlphaSense in the Signals podcast episode, Alternative Data for Corporations

What are the drawbacks of using alternative data?

Alternative data is extremely effective in telling a story, but it’s important to remember that it’s only telling part of the story. Though technology serves as a lucrative means of gathering and aggregating information, it cannot fully replace the kind of nuanced due diligence that only humans are capable of.

Another drawback is that much of alternative data is acquired in questionable ways, particularly as it pertains to privacy. While there is currently limited regulation on these invasive forms of data collection, this may not always be the case.

“As the data sets that financial institutions utilize expand beyond traditional consumer credit histories, data privacy will become a growing concern, as will data ownership and whether or not the consumer has any say over how these data are used and shared or whether they can review it for accuracy.” – Lael Brainard, a member of the US Federal Reserve’s Board of Governors where she serves as Chair of the Committees on Financial Stability, Federal Reserve Bank Affairs, Consumer & Community Affairs, and Payments, Clearing & Settlements

Why should you combine alternative data with fundamental data?

Alternative data can effectively reinforce your research, but it’s not detailed or reliable enough to totally replace fundamental data. Bridging fundamental research with technology and alternative data is how you can minimize risk and maximize confidence in your ideas.

AlphaSense is unique in that it’s an all-in-one solution that provides access to both fundamental and alternative data sources, and it uses patented AI technology to help you glean crucial insights from all those sources faster. Our platform does the work for you by giving you access to a wide variety of traditional sources—such as company and SEC filings, ESG reports, and broker research—as well as alternative datasets, such as expert calls, patent data, and sentiment.

Armed with both fundamental and alternative data, you have everything you need for a full-scale research process that informs smart data-driven decisions and produces real results.

How should you choose an alternative data provider?

Alternative data providers are not all made equal—depending on the purpose and scope of your investment research, you may want to invest in a data provider that does not merely hold the data, but also separates the signal from the noise by understanding the kinds of insights you are looking for. Additionally, some alternative data vendors are better for consumer-facing corporations, while others are better suited for financial services companies.

If you plan on utilizing alternative data heavily in your research and workflow process, you may want to select a provider that specializes specifically in alt data and thus offers access to a wide variety of it. If, however, you are looking for a more robust multi-faceted approach to research, which allows you to incorporate alternative data but also offers access to a vast content universe of fundamental research, you may benefit from an all-in-one market intelligence platform like AlphaSense.

AlphaSense allows you to seamlessly add alternative data to your research process with our expert transcript library and our built-in sentiment analysis feature, so that you can conduct more thorough and efficient research.

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