Proceedings of the Conference on Social and Sustainable Innovation in Technology & Engineering (SASI-ITE 2025)

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Analyzing Customer Conversion Patterns: A Survival Analysis Approach to Multi-Channel Attribution

Authors
Preetish Panda1, *
1Passage Inc., Kitchener, N2G 1H6, ON, Canada
*Corresponding author. Email: preetish88@gmail.com
Corresponding Author
Preetish Panda
Available Online 31 December 2025.
DOI
10.2991/978-94-6463-940-7_10How to use a DOI?
Keywords
Customer Conversion; Marketing Analytics; Survival Analysis; Attribution Models
Abstract

This report explores the dynamics of customer conversion by examining the relationship between visit behaviour and conversion outcomes across various marketing channels. By condensing customer visit data into a singular representation for each customer, we capture the time intervals from their first visit to either a conversion or their last recorded visit, thereby categorizing customers as converters or non-converters. The analysis utilizes survival analysis techniques to estimate conversion probabilities over time for different marketing channels, allowing for insights into the effectiveness of each channel in driving conversions. Furthermore, the report introduces a causal inference framework to assess the impact of offline marketing interventions, specifically television advertising, on web traffic. By employing Bayesian structural time-series models, we generate counterfactual predictions to isolate the uplift attributable to marketing efforts. This comprehensive approach highlights the interplay between digital and offline marketing strategies and provides actionable insights for optimizing customer engagement and conversion.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Conference on Social and Sustainable Innovation in Technology & Engineering (SASI-ITE 2025)
Series
Advances in Intelligent Systems Research
Publication Date
31 December 2025
ISBN
978-94-6463-940-7
ISSN
1951-6851
DOI
10.2991/978-94-6463-940-7_10How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Preetish Panda
PY  - 2025
DA  - 2025/12/31
TI  - Analyzing Customer Conversion Patterns: A Survival Analysis Approach to Multi-Channel Attribution
BT  - Proceedings of the Conference on Social and Sustainable Innovation in Technology & Engineering (SASI-ITE 2025)
PB  - Atlantis Press
SP  - 94
EP  - 146
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-940-7_10
DO  - 10.2991/978-94-6463-940-7_10
ID  - Panda2025
ER  -