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Generative AI for growth hacking: how startups use generative AI in their growth strategies

dc.contributor.authorRezazadeh, Arash
dc.contributor.authorKohns, Marco
dc.contributor.authorBohnsack, René
dc.contributor.authorAntónio, Nuno
dc.contributor.authorRita, Paulo
dc.date.accessioned2025-07-16T13:41:50Z
dc.date.available2025-07-16T13:41:50Z
dc.date.issued2025-04
dc.description.abstractThis study explores how startups and scaleups in Europe and the US use generative AI in their go-to-market strategies across product-led, sales-led, and operational efficiency-driven growth. Through interviews with 20 cases spanning pre-seed to Series E funding stages, we 1) analyze generative AI's role in growth strategies, 2) identify large language model use cases for tackling growth challenges such as customer churn, and 3) develop a framework for AI capabilities that guides managers in building, refining, and reflecting on their knowledge of using generative AI for growth hacking. Key findings include the implications of generative AI for technical and non-technical content creation in product-led growth, promotional content creation and repurposing, and customer experience personalization in sales-led growth, and market research, market entry strategies, and customer engagement in operational efficiency-driven growth. Findings empower managers to develop effective generative AI-driven growth hacking strategies while proactively managing unintended organizational, competitive, and societal consequences.eng
dc.identifier.doi10.1016/j.jbusres.2025.115320
dc.identifier.eid105000491667
dc.identifier.issn0148-2963
dc.identifier.urihttp://hdl.handle.net/10400.14/53944
dc.identifier.wos001453385700001
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAI capabilities
dc.subjectGenerative AI
dc.subjectGrowth hacking
dc.subjectLarge language models
dc.subjectStartup
dc.titleGenerative AI for growth hacking: how startups use generative AI in their growth strategieseng
dc.typeresearch article
dspace.entity.typePublication
oaire.citation.titleJournal of Business Research
oaire.citation.volume192
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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