AI 英語口說學習 App 之消費者看法與行銷策略研究——以 Speak 為例

Abstract

隨著人工智慧（AI）技術在語言教育領域的廣泛應用，結合語音辨識與自然語言處理的英語學習應用程式（App）已成為提升口說能力的重要工具。Speak 為 2024 年進入臺灣市場的新興 AI 英語口說學習 App，主打沉浸式對話與即時語音回饋功能，惟關於臺灣消費者對其認知、使用行為與轉換意願的實證研究仍付闕如。 本研究以 Speak 為分析對象，採用問卷調查法，回收臺灣地區 413 份有效樣本，依使用歷程將消費者分群，並透過描述性統計、獨立樣本 t 檢定與卡方分析，比較其在學習困難因素、功能評價、學習體驗、廣告代言人與價格感知等構面之差異。研究結果顯示，Speak 雖具初步品牌認知，但試用轉換率顯著低於競品 Duolingo；其訂閱價格與消費者可接受度亦存在落差，部分功能評價於試用前後出現反差，反映行銷訊息與實際體驗間的預期落差。 有鑑於此，本研究建議 Speak 可導入 Freemium 模式以降低試用門檻，並針對消費痛點調整行銷溝通策略，提升代言人風格與訊息內容之契合度；功能設計則可著重於課程豐富性與學習成效，以強化整體價值感知與實際使用者之留存意願。研究結果不僅為 Speak 在臺灣市場的行銷策略提供實證依據，亦有助於學術界理解 AI 英語口說學習 App 推廣歷程中之消費者轉換挑戰與行為特徵。

The growing application of artificial intelligence (AI) in language education has led to the rise of AI English-speaking learning apps that incorporate speech recognition and natural language processing to improve speaking proficiency. Speak, an AI English-speaking learning app launched in Taiwan in 2024, offers immersive conversation and real-time feedback. However, empirical research on Taiwanese users’ awareness, behavior, and conversion intent toward Speak remains limited. This study uses a questionnaire survey and analyzes 413 valid responses from Taiwan. Based on user experience stages, participants were segmented into groups, and descriptive statistics, t-tests, and chi-square analyses were conducted to examine differences across five dimensions: learning difficulties, functionality, learning experience, spokesperson effectiveness, and price perception. Results show that while Speak has achieved basic brand awareness, its trial conversion rate is significantly lower than that of Duolingo. Price concerns and post-trial drops in functional evaluation reveal a gap between marketing claims and user experience. The study recommends implementing a Freemium model to lower trial barriers, refining communication strategies to address user concerns, and improving spokesperson-message alignment. Product design should emphasize course variety and learning effectiveness to strengthen value perception and user retention. These findings offer practical insights for Speak’s marketing in Taiwan and contribute to understanding consumer conversion challenges in AI English-speaking learning apps.