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

arXiv: https://arxiv.org/abs/2302.01786 · HTML: https://mlsanity.com/paper/2302.01786/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 60 references that are in the map.
- First posted on arXiv 3 Feb 2023.

## Builds on (most cited first, 11 of 11)

- [Dense Passage Retrieval for Open-Domain Question Answering](https://mlsanity.com/paper/2004.04906/) (2020)
- [Attention-Based Models for Speech Recognition](https://mlsanity.com/paper/1506.07503/) (2015)
- [CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents](https://mlsanity.com/paper/2004.12629/) (2020)
- [Deep Learning for Answer Sentence Selection](https://mlsanity.com/paper/1412.1632/) (2014)
- [Attention-based Fully Gated CNN-BGRU for Russian Handwritten Text](https://mlsanity.com/paper/2008.05373/) (2020)
- [Deep learning for table detection and structure recognition: A survey](https://mlsanity.com/paper/2211.08469/) (2022)
- [TNCR: Table Net Detection and Classification Dataset](https://mlsanity.com/paper/2106.15322/) (2021)
- [HKR For Handwritten Kazakh & Russian Database](https://mlsanity.com/paper/2007.03579/) (2020)
- [KOHTD: Kazakh Offline Handwritten Text Dataset](https://mlsanity.com/paper/2110.04075/) (2021)
- [Automated Question Answer medical model based on Deep Learning Technology](https://mlsanity.com/paper/2005.10416/) (2020)
- [Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models](https://mlsanity.com/paper/2102.04816/) (2021)

## Built on by (most cited first, 3 of 3)

- [A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking](https://mlsanity.com/paper/2405.05900/) (2024)
- [Enhancing Retail Sales Forecasting with Optimized Machine Learning Models](https://mlsanity.com/paper/2410.13773/) (2024)
- [AMuRD: Annotated Arabic-English Receipt Dataset for Key Information Extraction and Classification](https://mlsanity.com/paper/2309.09800/) (2023)

## 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.