Boost Your Marketing ROI With Experimental Design  

Oleh:

Almquist, Eric ; Wyner, Gordon

Jenis: Article from Bulletin/Magazine - ilmiah internasional
Dalam koleksi: Harvard Business Review bisa di lihat di link (http://web.b.ebscohost.com/ehost/command/detail?sid=f227f0b4-7315-44a4-a7f7-a7cd8cbad80b%40sessionmgr114&vid=12&hid=105&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bth&jid=HBR) vol. 79 no. 10 (2001), page 135.
Topik: DESIGN; consumer marketing; internet marketing; marketing implementation; marketing planning; marketing strategy; statistical analysis; statistical methods; test markets

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Perpustakaan Pusat (Semanggi) Nomor Panggil: HH10.17 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Consumers are regularly blitzed with thousands of marketing messages - television commercials, telephone solicitations, supermarket circulars, and Internet banner ads. Still, a lot of these messages fail to hit their targets or elicit the desired response : the purchase of a product or service. It has been very difficult for companies to isolate what drives consumer behavior, largely because there are so many possible combinations of stimuli. In this article, consultants Eric Almquist and Gordon Wyner explain that although marketing has always been a creative endeavor, adopting a scientific approach to it may actually make it easier - and more cost effective - for companies to target the right customers. "Experimental design" techniques, which have long been applied in other fields, let people project the impact of many stimuli by testing just a few of them. By using mathematical formulas to select and test a subset of combinations of variables, marketers can model hundreds or even thousands of marketing messages accurately and efficiently - and they can adjust their messages accordingly. The authors use a fictional company, Biz Ware, to describe how companies can map out on a grid a combination of the attributes (or variables) of a marketing message and the levels (or variations) of those attributes. Marketers can test a few combinations of those attributes and levels and can apply logistic regression analysis to extrapolate the probable customer responses to all of the possible combinations. The company can then analyze the experiment's implications for its resources, revenues, and profitability. The authors also present the results of their work with Crayola, in which they used experimental design techniques to test that company's e - mail marketing campaign.

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