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Brand Storytelling : Integrated Marketing Communications for the Digital Media Landscape.
・ISBN 978-1-5381-7637-5 hard GB£ 65.00
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・ISBN 978-1-5381-7638-2 paper GB£ 25.99
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電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 979-88-8183-539-2
| 著者・編者 | Quesenberry, Keith A. / Coolsen, Michael K., |
|---|---|
| 出版社 | (Rowman & Littlefield, US) |
| 出版年月 | 2023.02 |
| ページ数 | 320 pp. |
| 言語 | ENG |
| ニュース番号 | <700-790> |
解説
This innovative new text introduces students to the power of storytelling and outlines a process for creating effective brand stories in a digital-first integrated marketing communications plan.
From the earliest works on storytelling to the latest research, this text explains why and how storytelling works, the forms storytelling takes, and how to develop an integrated advertising, PR, and strategic marketing communications campaign that leverages the power of story within the reality of today's digital-first media landscape.
Keith A. Quesenberry and Michael K. Coolsen present a balance of research and theory with practical application and case studies within a classroom-friendly framework for undergraduate or graduate courses or for the marketing communications professional looking for a guide to integrate storytelling into their brand communications. Emphasizing digital and social media perspectives in the strategic planning and campaign process, Brand Storytelling also surveys TV, radio, outdoor, print opportunities as well as earned, shared, owned, and paid media.
Features:
Chapters introduce discipline foundations through key figures, main content sections explaining concepts with examples, templates and stats, a main case study, questions for consideration, and list of key concepts for review.Coverage of new technologies in Web3, such as NFTs, cryptocurrency, media streaming, CTV, and the metaverse, ChatGPT, and DALL-E 2.Key terms are bolded and defined throughout and featured in a glossary along with an index of key concepts, figures, companies, and cases for easy reference.Plan/campaign research addresses evaluation and optimization of IMC execution including descriptive, predictive, and prescriptive analytics. Instructor resources include chapter outlines, learning objectives, test banks, slides, forms, template worksheets, example assignments, and syllabi.