Conceptio › Archive › arXiv (OAI Expanded)
arXiv (OAI Expanded) open access

B2B Customer Conversion Prediction: A Document Representation, Graph Theory, and CatBoost Driven Methodology

Wang, Tianqi et al.
arXiv (OAI Expanded) · Papers
Open Source ↗Direct PDF ↓
machine-learning
In the one-time selling B2B context, the buying cycle may last months or even years. During the long process, targeting customers that have a high potential to make purchases and recommending personalized campaigns accordingly are important for effective marketing. For this goal, we study the follow
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1070924
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive