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COPY LINK : https://fastpdf.bookcenterapp.com/yump/0692142606 P.D.F Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations F.R.E.E Book synopsis : Introduction to Algorithmic Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. It summarizes various techniques tested by major technology, advertising, and retail companies, and it glues these methods together with economic theory and machine learning. The book covers the main areas of marketing that require prog
COPY LINK : https://fastpdf.bookcenterapp.com/yump/0692142606
P.D.F Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations F.R.E.E
Book synopsis :
Introduction to Algorithmic Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. It summarizes various techniques tested by major technology, advertising, and retail companies, and it glues these methods together with economic theory and machine learning. The book covers the main areas of marketing that require prog
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Introduction to Algorithmic Marketing: Artificial Intelligence
for Marketing Operations
Description :
Introduction to Algorithmic Marketing is a comprehensive guide to
advanced marketing automation for marketing strategists, data
scientists, product managers, and software engineers. It
summarizes various techniques tested by major technology,
advertising, and retail companies, and it glues these methods
together with economic theory and machine learning. The book
covers the main areas of marketing that require programmatic
micro-decisioning - targeted promotions and advertisements,
eCommerce search, recommendations, pricing, and assortment
optimization.Table of ContentsChapter 1 - IntroductionThe Subject
of Algorithmic MarketingThe Definition of Algorithmic
MarketingHistorical Backgrounds and ContextProgrammatic
ServicesWho Should Read This Book?SummaryChapter 2 - Review of
Predictive ModelingDescriptive, Predictive, and Prescriptive
AnalyticsEconomic OptimizationMachine LearningSupervised
LearningRepresentation LearningMore Specialized
ModelsSummaryChapter 3 - Promotions and
AdvertisementsEnvironmentBusiness ObjectivesTargeting
PipelineResponse Modeling and MeasurementBuilding Blocks:
Targeting and LTV ModelsDesigning and Running
CampaignsResource AllocationOnline AdvertisementsMeasuring the
EffectivenessArchitecture of Targeting SystemsSummaryChapter 4 -
SearchEnvironmentBusiness ObjectivesBuilding Blocks: Matching
and RankingMixing Relevance SignalsSemantic AnalysisSearch
Methods for MerchandisingRelevance TuningArchitecture of
Merchandising Search ServicesSummaryChapter 5 -
RecommendationsEnvironmentBusiness ObjectivesQuality
EvaluationOverview of Recommendation MethodsContent-based
FilteringIntroduction to Collaborative FilteringNeighborhood-based
Collaborative FilteringModel-based Collaborative FilteringHybrid
MethodsContextual RecommendationsNon-Personalized
RecommendationsMultiple Objective OptimizationArchitecture of
Recommender SystemsSummaryChapter 6 - Pricing and
AssortmentEnvironmentThe Impact of PricingPrice and ValuePrice
and DemandBasic Price StructuresDemand PredictionPrice
OptimizationResource AllocationAssortment OptimizationArchitecture
of Price Management SystemsSummary