Prosper Insights & Analytics Unveils “Prosper AI Bundle” to Train AI/ML Algorithms with Comprehensive Consumer Datasets

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Created from a 20 year survey, the Prosper AI Bundle allows firms to quickly train AI algorithms on accurate, representative, and predictive consumer data

Prosper Insights & Analytics, a leading provider of consumer data and insights, proudly announces the launch of their AI Bundle, a tailor-made consumer dataset. The Prosper AI Bundle equips companies with the data needed to train highly predictive and representative machine learning applications, harnessing the full power of AI.

87% of data and analytics leaders across global enterprises cite data quality issues as the reason their organizations failed to successfully implement AI and machine learning initiatives. Meanwhile, bias in AI is a persistent problem, again a feature of poor data quality and unrepresentative samples. To successfully scale AI initiatives, organizations must ensure that their data is accurate, representative, and predictive.

The Prosper AI Bundle is just that. It’s built on the largest scientific consumer survey with a 20-year history of accurately measuring consumer behaviors, motivations, personal interests, and future purchase plans. The survey provides accurate, representative data that has been the source data in over 30 peer reviewed academic journal articles. The dataset has also been the resource for the National Retail Federation since 2003 to trend and track consumer spending for all retail holidays throughout the year. No PII is captured in the surveys.

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“Data quality is the great barrier to AI implementation at scale,” said Gary Drenik, CEO of Prosper Insights & Analytics. “There’s a reason that ‘garbage in, garbage out,’ is such a commonly cited phrase in AI projects: your artificial intelligence is only as smart as the data it’s trained on. What we’re seeing now, with the explosion of AI applications, is that click data, though abundant, has true limits in terms of representativeness and reliability. There’s simply a scarcity of high quality data to empower machine learning algorithms. The “Prosper AI Bundle,” is built on the most trusted consumer survey dataset in the industry, which is already seeing some amazingly predictive AI applications.”

One such application of AI.ML trained on data from the Prosper AI Bundle is CloudQuant’s Prosper Equity Sub-Industry Signals. By analyzing the consumer sentiment data and purchase intent data, CloudQuant’s proprietary modeling has been able to foresee consumer trends and behavior in the market with high accuracy. Prosper monthly signals continue to show strength in identifying stock market sub industries that outperform the S&P 500 Index as well as under-performers that are great hedges for market risks. The long/short strategy which rebalances once per month has outperformed the S&P 500 by approximately 23% since January 2022.

“Knowing how consumers will react to future events is a critical component of success for investors,” said Phil Rist, EVP of Prosper Insights & Analytics. “Prosper’s highly organized and representative consumer data has proven to be a high-quality input for helping CloudQuant generate unique and accurate predictive analytics for investment managers; and is becoming the gold standard for producing predictive models.”

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MTS Staff Writer

MarTech Series (MTS) is a business publication dedicated to helping marketers get more from marketing technology through in-depth journalism, expert author blogs and research reports.

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