
Discover how algorithms predict who will click, buy, lie, or die in "Predictive Analytics" - the Freakonomics of big data. Used by 30+ universities and translated into 9 languages, it reveals why vegetarians miss fewer flights and how companies like Netflix see your future.
著者の声を通じて本を感じる
知識を魅力的で例が豊富な洞察に変換
キーアイデアを瞬時にキャプチャして素早く学習
楽しく魅力的な方法で本を楽しむ
Imagine a father storming into a Target store, furious that the retailer was sending his teenage daughter baby-related coupons. Days later, he called back with a sheepish apology: his daughter was indeed pregnant - due in August. Target's algorithms had detected subtle changes in her purchasing patterns before she'd told her family. Welcome to the world of predictive analytics, where algorithms peer "through the previously impenetrable barrier between today and tomorrow." This technology transforms our digital footprints into forecasts of remarkable accuracy - predicting what we'll buy, whether we'll quit our jobs, default on loans, or even develop diseases. These aren't vague, generalized predictions like weather forecasts, but individualized insights applied across millions of people simultaneously. The power comes not from perfect accuracy, but from being consistently better than random guessing - what Eric Siegel calls "The Prediction Effect." When organizations can make slightly better decisions at massive scale, the cumulative impact transforms industries. Consider a direct marketing campaign: without predictive analytics, you'd randomly select recipients and expect a 1% response rate. But what if you could identify a segment three times more likely to respond? You'd triple your results with the same budget. This illustrates how even modest improvements in prediction accuracy create tremendous value. Credit card companies improving fraud detection by just 2% save millions annually. Healthcare providers predicting patient readmissions with 15% better accuracy significantly reduce costs while improving care. What makes this approach transformative is that predictions directly drive decisions: doctors reviewing high-risk patients, agents contacting customers likely to cancel, marketers targeting specific prospects. Amazon's recommendation engine drives 35% of their sales. Netflix saves $1 billion annually through predictive customer retention.
『Predictive Analytics』の核心的なアイデアを分かりやすいポイントに分解し、革新的なチームがどのように創造、協力、成長するかを理解します。
『Predictive Analytics』を素早い記憶のヒントに凝縮し、率直さ、チームワーク、創造的な回復力の主要原則を強調します。

鮮やかなストーリーテリングを通じて『Predictive Analytics』を体験し、イノベーションのレッスンを記憶に残り、応用できる瞬間に変えます。
何でも質問し、声を選び、本当にあなたに響く洞察を一緒に作り出しましょう。

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