PredictHQ built QSPD: the industry standard for event data quality
Without QSPD standards, event data will break your models. QSPD – Quality Standards for Processing Demand Causal Factors – is a robust framework to ensure data is forecast-grade.
Intelligent event data is complex and costly to create.
QSPD is essential to quality.
Of sources required to get depth for coverage and verification
Of data science time wasted finding and cleaning data rather than spent on data science
Events change location, date, time after their first published date
Gold standard for processing demand causal factors
- Depth + VarietyDepth and variety of data sources is critical to confirming event information is accurate.
- VerificationEach event needs to be verified for reliable data, as many events are misleading.
- Accuracy + DetailAll event details such as geolocation and attendance must be confirmed or corrected.
- Categories + CoverageMeaningful results requires many categories.
- Spam RemovalSpam events must be identified and deleted or they will cause fake demand signals.
- De-DupingAll duplicate events must be found and deleted. Some event APIs have ~30% duplicates.
- Rank by Size + ImpactA high volume of events requires a reliable way to organize by size and impact.
- MaintenanceEvent data needs constant maintenance as it is dynamic with event details changing often.
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Demand intelligence is a new tool for businesses, so categorizing PredictHQ and finding comparable services is hard. We've created this Request for Product guide so your team can get their hands on our data and start seeing value ASAP.
Processing demand causal factors depends on data pipeline capabilities
Our data scientists have built more than 1000 machine learning models to aggregate, standardize, verify and rank event data from hundreds of disparate sources.