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=== Marketing optimization === Marketing organizations use analytics to determine the outcomes of campaigns or efforts, and to guide decisions for investment and consumer targeting. Demographic studies, customer segmentation, conjoint analysis and other techniques allow marketers to use large amounts of consumer purchase, survey and [[panel data]] to understand and communicate marketing strategy.<ref name=":1">{{Cite journal|last1=Wedel|first1=Michel|last2=Kannan|first2=P.K.|date=November 1, 2016|title=Marketing Analytics for Data-Rich Environments|url=https://journals.sagepub.com/doi/10.1509/jm.15.0413|journal=Journal of Marketing|volume=80|issue=6|pages=97β121|doi=10.1509/jm.15.0413|s2cid=168410284|issn=0022-2429|access-date=January 10, 2022|archive-date=March 31, 2022|archive-url=https://web.archive.org/web/20220331114129/https://journals.sagepub.com/doi/10.1509/jm.15.0413|url-status=live|url-access=subscription}}</ref> Marketing analytics consists of both qualitative and quantitative, structured and unstructured data used to drive strategic decisions about brand and revenue outcomes. The process involves predictive modelling, marketing experimentation, automation and real-time sales communications. The data enables companies to make predictions and alter strategic execution to maximize performance results.<ref name=":1" /> [[Web analytics]] allows marketers to collect session-level information about interactions on a website using an operation called [[sessionization]]. [[Google Analytics]] is an example of a popular free analytics tool that marketers use for this purpose.<ref>{{Cite web|title=Session - Analytics Help|url=https://support.google.com/analytics/answer/6086069|access-date=2022-01-09|website=support.google.com|archive-date=January 10, 2022|archive-url=https://web.archive.org/web/20220110161138/https://support.google.com/analytics/answer/6086069|url-status=live}}</ref> Those interactions provide [[web analytics]] information systems with the information necessary to track the referrer, search keywords, identify the IP address,<ref>{{Cite web|title=IP address - Analytics Help|url=https://support.google.com/analytics/answer/6322282|access-date=2022-01-09|website=support.google.com|archive-date=January 10, 2022|archive-url=https://web.archive.org/web/20220110152845/https://support.google.com/analytics/answer/6322282|url-status=live}}</ref> and track the activities of the visitor. With this information, a marketer can improve marketing campaigns, website creative content, and information architecture.<ref>{{Cite web|title=Analytics Tools & Solutions for Your Business - Google Analytics|url=https://marketingplatform.google.com/about/analytics/|access-date=2022-01-09|website=Google Marketing Platform|language=en|archive-date=October 2, 2022|archive-url=https://web.archive.org/web/20221002000102/https://marketingplatform.google.com/about/analytics/|url-status=live}}</ref> Analysis techniques frequently used in marketing include marketing mix modeling, pricing and promotion analyses, sales force optimization and customer analytics, e.g., segmentation. Web analytics and optimization of websites and online campaigns now frequently work hand in hand with the more traditional marketing analysis techniques. A focus on digital media has slightly changed the vocabulary so that ''marketing mix modeling'' is commonly referred to as ''attribution modeling'' in the digital or [[marketing mix modeling]] context.{{Citation needed|date=January 2022}} These tools and techniques support both strategic marketing decisions (such as how much overall to spend on marketing, how to allocate budgets across a portfolio of brands and the marketing mix) and more tactical campaign support, in terms of targeting the best potential customer with the optimal message in the most cost-effective medium at the ideal time.
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