Enabling Product Platform Growth with AI-Assisted Insight

Jeffrey L. Jenkins (), Joseph S. Valacich () and David W. Wilson ()
Additional contact information
Jeffrey L. Jenkins: Brigham Young University
Joseph S. Valacich: University of Arizona
David W. Wilson: Brigham Young University

A chapter in The Design of Human-Centered Artificial Intelligence for the Workplace, 2025, pp 453-466 from Springer

Abstract: Abstract This chapter presents a discussion on the challenges associated with managing and gaining insights from the massive amount of behavioral data available to digital service providers. The case studies presented demonstrate the potential benefits of leveraging AI tools to automate the analysis process and gain valuable insights into user behavior at scale. The use of algorithmic analysis can identify malfunctioning features or common interaction pathways leading to negative outcomes, and exploratory analyses can uncover unexpected use cases that may unlock new markets or revenue streams. The chapter concludes that AI-enabled insight is becoming increasingly critical to successful PLG strategies as it enables businesses to better understand their users and make data-driven decisions that support growth and improve the user experience. The examples presented here suggest that there are still many possibilities for deriving insights from user behavior data that have not yet been explored.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-83512-4_26

Ordering information: This item can be ordered from
http://www.springer.com/9783031835124

DOI: 10.1007/978-3-031-83512-4_26

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().