AI-Powered Value Proposition: Revolutionizing Customer Engagement

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F25%3A101870" target="_blank" >RIV/60460709:41110/25:101870 - isvavai.cz</a>

Výsledek na webu

<a href="https://uni.uhk.cz/hed/site/assets/files/1093/proceedings_2025_1-1.pdf" target="_blank" >https://uni.uhk.cz/hed/site/assets/files/1093/proceedings_2025_1-1.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.36689/uhk/hed/2025-01-019" target="_blank" >10.36689/uhk/hed/2025-01-019</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AI-Powered Value Proposition: Revolutionizing Customer Engagement

Popis výsledku v původním jazyce

This study explores the integration of artificial intelligence (AI) into the Value Proposition Canvas (VPC) model, emphasizing its impact on business processes, customer need identification, and company performance. It examines AI applications across different VPC stages, focusing on technologies such as natural language processing (NLP), machine learning (ML), and generative AI. These technologies enhance customer insights, allowing businesses to develop highly personalized value propositions (VPs) and improve market responsiveness. A case study of a luxury resort illustrates how AI-driven analytics refine decision-making, optimize customer engagement, and increase the accuracy of VPs. The findings suggest that AI integration leads to improved personalization, greater strategic adaptability, and higher operational efficiency. Furthermore, AI adoption strengthens automation, streamlines data-driven optimization, and enhances customer-centric approaches, ultimately driving competitive advantage. By leveraging AI, businesses can improve targeting, enhance strategic planning, and create more efficient and responsive VPs. The study provides practical recommendations for companies seeking to integrate AI into their VP strategies, ensuring long-term success in an increasingly digital and competitive marketplace.

Název v anglickém jazyce

AI-Powered Value Proposition: Revolutionizing Customer Engagement

Popis výsledku anglicky

This study explores the integration of artificial intelligence (AI) into the Value Proposition Canvas (VPC) model, emphasizing its impact on business processes, customer need identification, and company performance. It examines AI applications across different VPC stages, focusing on technologies such as natural language processing (NLP), machine learning (ML), and generative AI. These technologies enhance customer insights, allowing businesses to develop highly personalized value propositions (VPs) and improve market responsiveness. A case study of a luxury resort illustrates how AI-driven analytics refine decision-making, optimize customer engagement, and increase the accuracy of VPs. The findings suggest that AI integration leads to improved personalization, greater strategic adaptability, and higher operational efficiency. Furthermore, AI adoption strengthens automation, streamlines data-driven optimization, and enhances customer-centric approaches, ultimately driving competitive advantage. By leveraging AI, businesses can improve targeting, enhance strategic planning, and create more efficient and responsive VPs. The study provides practical recommendations for companies seeking to integrate AI into their VP strategies, ensuring long-term success in an increasingly digital and competitive marketplace.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Hradec Economic Days

ISBN

978-80-7435-855-5

ISSN

2464-6059

e-ISSN

2464-6067

Počet stran výsledku

333

Strana od-do

213-224

Název nakladatele

University of Hradec Králové

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

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