Seeing Double: Content Replication in Pitch Decks and Oral Pitch Presentations

The pitch deck is a common component of pitch presentations, yet there is little we know regarding its integration in a pitch presentation. This research seeks to identify the extent of the repetition of verbal content present both the oral presentation and the slides of pitches from an accelerator program. 13 accelerator pitch presentations were analyzed. Results suggest the use of replications is common in pitch presentations, although it varies across presentations, visual elements, and topic of the slides. The paraphrasing of textual elements seems to be the most recurrent replication type in a majority of the topics. The number of replications seem to be higher for certain topics, such as ‘Achievements‘, and lower for others, such as ‘Company’.

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Published
2025-07-20
DOI
https://doi.org/10.1109/procomm64814.2025.00011
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

Seeing Double: Content Replication in Pitch Decks and Oral Pitch Presentations

Paula Cabezas
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Natural Language Processing Techniques
article

Seeing Double: Content Replication in Pitch Decks and Oral Pitch Presentations

Paula Cabezas
article en

Abstract

The pitch deck is a common component of pitch presentations, yet there is little we know regarding its integration in a pitch presentation. This research seeks to identify the extent of the repetition of verbal content present both the oral presentation and the slides of pitches from an accelerator program. 13 accelerator pitch presentations were analyzed. Results suggest the use of replications is common in pitch presentations, although it varies across presentations, visual elements, and topic of the slides. The paraphrasing of textual elements seems to be the most recurrent replication type in a majority of the topics. The number of replications seem to be higher for certain topics, such as ‘Achievements‘, and lower for others, such as ‘Company’.

University of Bremen (DE)
Openalex Percentile: Top 89%
Natural Language Processing Techniques
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