The Best Alternative Dataset for Investors? Location Analytics

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Since modern investing began, one thing has remained constant: data is essential to developing the best investment strategies. Traditionally, professional investors have relied on public company disclosures, such as quarterly earnings reports and other financial statements, to evaluate a company’s performance and make investment decisions.

While a company’s financial metrics like revenue, profit, income, and expenses certainly provide valuable insight when considering an investment opportunity, this data alone may not provide a comprehensive picture of a company’s current or future performance.

Today’s investors are continuously seeking more information about companies beyond quarterly earnings reports. As a result, non-traditional datasets, known as alternative data, are increasingly being used by investors to make better decisions and reduce risk.

Alternative data can be any type of information about a company that can help guide investment strategies (e.g., public sentiment, website traffic, social media metrics, employee count, etc.). So what are the best alternative datasets for investors? Consumer foot traffic data measured through location analytics is a key alternative dataset that every investor should be using.

Foot Traffic Data from Location Analytics Can Guide Investment Decisions

Location analytics provides insight into the places consumers go in the physical world. At our company, Unacast, we leverage mobile location data to measure consumer foot traffic at places of commercial interest, such as restaurants, retailers, hotels, entertainment venues, and more.

Foot traffic data reflects real-world consumer engagement because the places that people choose to go to and spend their time and money demonstrates their interests, preferences, and priorities. As an alternative dataset for professional investors, foot traffic data can highlight changes in consumer behavior, trends, and demand, which can help investors more deeply understand a company’s performance outside of its quarterly earnings results.

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Foot Traffic Data Coupled with Other Alternative Datasets Offers Deeper Insights

Investors can derive even more insight from a company’s consumer foot traffic data by analyzing it alongside other types of data. For example, analysts can examine a brand’s foot traffic beside its quarterly revenue to determine the correlation between the two. If there is a strong correlation, then investors can use the company’s foot traffic data to estimate its potential performance in the future. Investors can leverage this information to guide their investment strategies before the company releases its next earnings report.

With the many types of alternative data available today, there are countless insights that investors can gain by incorporating foot traffic data into their analysis. For instance, if a brand launches a highly anticipated product, an investor could look at figures surrounding the launch, such as the company’s hiring rate and number of credit card transactions, along with foot traffic analytics like volume and dwell time, to get a more complete idea of how well the company prepared for its product launch, how consumers reacted to it, and what this could mean for the company’s future performance.

Better Investment Strategies with Foot Traffic Data

Foot traffic data measured through location analytics gives investors timely insight into changing consumer preferences in a post-pandemic world. By analyzing foot traffic data that reflects true consumer activity, investors can better understand a company’s performance in near real-time. Analysts can also use historical foot traffic data to create forecasts that predict future foot traffic trends and illustrate how any changes in foot traffic may impact future company performance. Through these insights, investors can identify opportunities, mitigate risks, and ultimately gain an edge in the market.

To learn how to use location analytics in your investment strategy, book a meeting with us today.


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