mlsanityData to 7 Oct 2026

Customer Profiling, Segmentation, and Sales Prediction using AI in Direct Marketing

arXiv 2302.01786 ↗First posted 3 Feb 2023cs.AIcited by 3

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Abstract (arXiv)

In an increasingly customer-centric business environment, effective communication between marketing and senior management is crucial for success. With the rise of globalization and increased competition, utilizing new data mining techniques to identify potential customers is essential for direct marketing efforts. This paper proposes a data mining preprocessing method for developing a customer profiling system to improve sales performance, including customer equity estimation and customer action prediction. The RFM-analysis methodology is used to evaluate client capital and a boosting tree for prediction. The study highlights the importance of customer segmentation methods and algorithms to increase the accuracy of the prediction. The main result of this study is the creation of a customer profile and forecast for the sale of goods.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 11 of its 60 references that are in the map. First posted on arXiv 3 Feb 2023.

Builds on

11 of 60 references.

References · 11

  1. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  2. 2015Attention-Based Models for Speech Recognitioncited by 400
  3. 2020CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documentscited by 98
  4. 2014Deep Learning for Answer Sentence Selectioncited by 17
  5. 2020Attention-based Fully Gated CNN-BGRU for Russian Handwritten Textcited by 17
  6. 2021TNCR: Table Net Detection and Classification Datasetcited by 14
  7. 2022Deep learning for table detection and structure recognition: A surveycited by 14
  8. 2020HKR For Handwritten Kazakh & Russian Databasecited by 12
  9. 2021KOHTD: Kazakh Offline Handwritten Text Datasetcited by 10
  10. 2020Automated Question Answer medical model based on Deep Learning Technologycited by 9
  11. 2021Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Modelscited by 5

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Citing papers per year: 2023: 1; 2024: 2.

3 papers.