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Fable Data

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We source consumer and small business transaction data directly from European banks and credit card providers. We use anonymised data from millions of cards to deliver a daily live feed of new transactions with a 5 year history, overlaid with socio-demographic and merchant information. Our total panel of 5 million accounts informs and enhances investor strategies to make better decisions and generate alpha. Clients can see market dynamics, merchant performance, and consumer trends in real time, and model data to find close economic correlations with established sources and company data releases. Our products are available at row level or in aggregated form (with various options).

Credit/Debit Card

main data source

2018

Year Company Founded

N/A

Discretionary Asset Manager Customers
employees

40

top tickers

AMZN.US, BOO LN, DNLM.LN, EZJ.LN, HMB.SS, JUST.LN, KGF.LN, SBRY.LN, SPOT.US

client focus

Hedge Fund

sectors

Airlines, Autos, Consumer, Financial Services, Food & Beverage, Healthcare, Industrials, Internet, Restaurants & Food Delivery, Retail, Telecom, TMT & Entertainment, Travel

HQ location

UK

data delivery

Raw

website link

www.fabledata.com

pricing

Will not provide

pricing structure

Subscription prices vary depending on the chosen lag and aggregation level

Dataset Coverage start

2016

geography covered

Europe

why us?

Largest real-time pan-European panel expanding across Europe

advantages

The first company to bring real-time pan-European transaction data to market, sourced directly from banks and credit card issuers, anonymised and GDPR compliant, with unparalleled granularity. This was the biggest development in global alternative data last year. We have the largest real-time pan-European panel, continuing to expand across Europe and supplied exclusively to the buyside in different formats and levels of aggregation dependent on your data science capability. We have applied advanced machine-learning techniques to unlock real-time use cases for the first time.

use cases

Predict market-moving data releases e.g. ONS consumer expenditure, GfK, Mintel, Kantar, Predict industry performance at a category level, Understand competition, market share, and geographical patterns, Understand category level spend by country, Predict current-quarter reporting metrics against actuals and estimates, Measure the correlation to actual reported vs. consensus numbers the day before results, Identify anomalies that could flag opportunity or risk, Track market share by company and competitor performance metrics, Analyse same store sales using merchant location information, Infer customer acquisition, switching, and retention behaviours, Track aggregated consumer spend by country, Analyse spend by user location, Analyse basket size and transaction frequency trends by user and merchant location

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