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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM39419

Leveraging AI to Extend the Lifecycle of Wearables: A Product Manager’s Strategy for Post-Launch Success

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM39419

Volume:

8 |

12 |

Dec 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM39419

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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DS

Darshak Sanghavi

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Abstract

In the fast-evolving wearable technology market, product managers face the challenge of maximizing product longevity while maintaining user satisfaction post-launch. AI offers powerful tools to continuously improve wearables through predictive maintenance, over-the-air (OTA) updates, and dynamic user feedback loops. This whitepaper explores how AI can be leveraged to extend the lifecycle of wearables by enabling predictive insights into device performance, automating software updates, and fostering deeper engagement with users. We also examine strategies for retaining customers, managing the lifecycle of wearables, and ensuring that wearables remain relevant long after their initial launch. By effectively utilizing AI, product managers can ensure that wearables provide value over time, improving both customer loyalty and business profitability.

KEYWORDS

AI-driven software updates predictive maintenance user retention strategies lifecycle management wearable longevity post-launch success over-the-air updates product lifecycle extension customer feedback loops AI in wearables.

Cite This Article

Darshak Sanghavi, "Leveraging AI to Extend the Lifecycle of Wearables: A Product Manager’s Strategy for Post-Launch Success," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 12, Dec 2024. https://doi.org/10.55041/IJSREM39419

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Publication Date

4/30/2025

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Double-Blind Peer Review

Review Rounds: 2

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