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business metrics

by Serhiy Bryl
Jun 13, 2018
3
Anomaly Detection for Business Metrics with R

The larger and more complex the business the more metrics and dimensions. One day you understand that it is impossible to track them with only your eyes.

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Author

Serhiy Bryl

Data Scientist

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TAGS

affective lexiconsanimated plotanomaliesbusiness healthbusiness metricschurncoronavirusCOVID-19delta life-cycle gridsdictionary-based approachdoc2vecevents sequencein-depth sequential analysisLTV predictionmachine learningmarketing multi-channel attribution modelmarkov chainmixed segmentationoutliersretention ratesales funnelsegmentation based on life-cycle gridsshifted-beta-geometric distributiontext analysistime seriestwitter sentiment analysisvisualization

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Categories

  • Anomaly Detection
  • Attribution Model
  • Clustering
  • Cohort analysis
  • Customer Segmentation
  • Kaggle competition
  • LifeCycle Grids
  • LTV
  • Machine learning
  • R language
  • Sales Funnel
  • Sentiment Analysis
  • Sequential analysis
  • Visualization

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Tags

affective lexicons animated plot anomalies business health business metrics churn coronavirus COVID-19 delta life-cycle grids dictionary-based approach doc2vec events sequence in-depth sequential analysis LTV prediction machine learning marketing multi-channel attribution model markov chain mixed segmentation outliers retention rate sales funnel segmentation based on life-cycle grids shifted-beta-geometric distribution text analysis time series twitter sentiment analysis visualization

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