دانلود رایگان مقاله اثربخشی بلند مدت بخش مصرف کننده اینترنتی بر بازارایابی

عنوان فارسی
چگونه بخش مصرف کننده اینترنتی در بلند مدت بر بازارایابی تاثیر میگذارد؟
عنوان انگلیسی
How Online Consumer Segments Differ in Long-term Marketing Effectiveness
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
14
سال انتشار
2014
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E2417
رشته های مرتبط با این مقاله
مدیریت و علوم اقتصادی
گرایش های مرتبط با این مقاله
مدیریت کسب و کار و بازاریابی
مجله
مجله بازاریابی تعاملی - Journal of Interactive Marketing
دانشگاه
آلمان
کلمات کلیدی
تأثیر طولانی مدت، بخش، موسیقی دیجیتال، آنلاین، همکاری، تبلیغات، تقسیم بندی-کلاس پنهان، اتورگرسیو برداری
چکیده

Abstract


Online commerce gives companies not only a growing global sales platform, but also powerful consumers enjoying 24/7 availability, choice proliferation and the power to opt in and out permission-based communication. Unfortunately, our knowledge is limited on long-term marketing effectiveness in this space and on how it differs across customer segments. Managers appear overwhelmed by the combination of rich online data on hundreds of thousands of customers and the typical aggregate-level data on offline marketing spending. This paper is the first to investigate the long-term impact of coupon promotions, TV, radio, print, and Internet advertising across customer segments for a major digital music provider with over 500,000 customers. We first segment customers and subsequently analyze how these segments respond in the long run to different marketing activities when purchasing music downloads. Our findings reveal that the effectiveness of marketing differs across segments, while standard segmentation approaches fail to identify the most valuable catches in a sea of consumers. In contrast to empirical generalizations on consumer packaged goods, heavy users of digital music products are least sensitive to price and most sensitive to TV advertising and to multiple touch points. Light users, the majority of consumers, are price sensitive and tend to opt out of targeted communication. Our research enables managers in the digital media space to target high-value customer segments with the most effective actions.

نتیجه گیری

Conclusion


The rise of the Internet and broadband access such as DSL has revolutionized the way digital media are marketed and sold. While forgoing the actual physical product (and consequently certain features of the physical product, such as liner notes), consumers are now able to purchase media at any given time and consume it immediately. With music, consumers have gained the additional benefit of “unbundled” songs, as it is now possible to buy individual songs without the need to buy the rest of the album. These dramatic changes in the actual product as well as in the way the products are marketed and sold, combined with the sheer size of the online entertainment industry, raise many questions that have not been addressed in marketing research as of yet. In this paper we investigate the short- and long-run effectiveness of the marketing mix across segments that substantially differ in size, profile and marketing response. Based on our analysis of hundreds of thousands of consumers of a major European music download provider, we find that standard segmentation approaches fail to identify the most valuable catches in a sea of consumers. In contrast to empirical generalizations on consumer packaged goods, heavy users of digital music products are least sensitive to price and most sensitive to TV advertising and to multiple touch points. Light users, the vast majority of digital music consumers, are price sensitive and tend to opt out of targeted communication. Our methodology accounts for data at different levels: the market and the individual consumer. Firms still use traditional marketing instruments such as offline advertising and the data on these marketing actions are available in the typical aggregated form well known from many other industries. However, data on purchases and some other marketing instruments, e.g., coupons, is available on a customer-level. We propose a two-stage model to accommodate these different levels of aggregation and show how simply aggregating over customers leads to aggregation bias in estimating response to marketing actions.


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