English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The value of raw data is unlocked by converting it into information andknowledge that drives decision-making. Machine Learning (ML) algorithms arecapable of analysing large datasets and making accurate predictions. Marketsegmentation, client lifetime value, and marketing techniques have all made useof machine learning. This article examines marketing machine learningtechniques such as Support Vector Machines, Genetic Algorithms, Deep Learning,and K-Means. ML is used to analyse consumer behaviour, propose items, and makeother customer choices about whether or not to purchase a product or service,but it is seldom used to predict when a person will buy a product or a basketof products. In this paper, the survival models Kernel SVM, DeepSurv, SurvivalRandom Forest, and MTLR are examined to predict tine-purchase individualdecisions. Gender, Income, Location, PurchaseHistory, OnlineBehavior,Interests, PromotionsDiscounts and CustomerExperience all have an influence onpurchasing time, according to the analysis. The study shows that the DeepSurvmodel predicted purchase completion the best. These insights assist marketersin increasing conversion rates.

Buy when? Survival machine learning model comparison for purchase timing