Alpha-DNA – Can digital consumer metrics predict investment winners?
Alternative data sources are becoming an instrumental new source of insight for investors. One of the most interesting types of alternative datatypes available to investors is the consumer metrics and volu-metrics used by marketing executives to track digital interaction and digital penetration. An entire ecosystem of companies have sprung on to the scene that compiles and sells this data to marketing executives to help them better understand digital penetration. Let’s refer to the collection of this data as the Digital Footprint.
Our key research question is: Can this Digital Footprint predict which companies will make good investments? In other words, can it find market winners by providing insight that the market is currently unable to identify?The answer is ‘Yes’ if we can identify companies that will surprise the markets with their near term revenue and EPS performance. To answer this question, we have converted the Digital Footprint in to Digital SurpriseSignal for the purpose of this study.
The Digital Surprise Signal is a systematic stock selection score designed to forecast revenue and earnings surprises for 2000+ companies based on changes in consumer demand estimated from their Digital Footprint trajectories. The algorithms underpinning the Digital Surprise Signal leverage alpha-DNA’s proprietary organization of near real-time commercially available online consumer behavior information across multiple web Site, Search and Social platforms. The estimated change in demand is compared to market expectations for revenue to determine how likely a company is to surprise.
alpha-DNA was founded in 2014 with the primary goal of leveraging realtime digital information within scalable consumer analytics frameworks to improve high value financial decisions. alpha-DNA client engagements span across hedge funds, private equity firms, banks, market research and strategy consulting firms, all with the primary focus on assessing digital performance of companies/brands and translating that into forward looking topline growth acceleration expectations.
The web, by its very nature, creates real-time and comprehensive data about online consumer behavior. Digital behavior is fundamentally correlated with online and offline consumer demand, both in B2C and B2B contexts. Customers not only buy products and services online, but also compare, research, seek support, recommend, and review them, extending the applicability of online behavior into the offline world. Consumer demand is a primary driver of revenue, and sharp changes in consumer demand manifest in a company’s revenue performance, but market expectations lack contemporaneous company-specific fundamental data during the course of the fiscal quarter; new fundamental data from digital sources can better “predict the present” and identify trajectory changes.
At alpha-DNA, we have collected multiple types of digital performance measures, from multiple commercially and publicly available data sources. The data is broad-based and includes various data types across web site, search and social platforms. Data is sourced from multiple providers for the same type of data to reduce noise, and data sources are continuously reevaluated and appropriately re-weighted over time. In terms of scale, on a monthly basis alpha-DNA tracks more than 75 billion digital consumer interactions to hone in on change in velocity across businesses.
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