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Business Intelligence for Search Marketing: Challenges and Opportunities

Explore the challenges and opportunities in utilizing business intelligence for search marketing, including SEO and SEM factors, data-driven applications, and data processing. Discover the potential impact and value of data-driven insights and uncover relevant data mining techniques. Gain insights into automation opportunities and potential research topics in the field of knowledge discovery in search marketing.

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Business Intelligence for Search Marketing: Challenges and Opportunities

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  1. Business Intelligence for Search Marketing:Challenges and Opportunities Panelists: Bassel Ojjeh (Group VP, Strategic Data Solutions) Alex Tuzhilin (NYU) Yunhong Zhou (HP Labs)

  2. Yahoo’s SDS Mission Statement “ Create value for consumers and marketers by delivering a consumer-centric data platform and insight services that maximize user engagement and enable innovative marketing solutions “

  3. Ebusiness Customer Lifecycle visible impression click thru revisit search Reach Acquisition Internet visitors churn Retention Conversion revisit purchase/ download signup/purchase revisit

  4. Search Marketing • Search Engine Optimization (SEO) • Increase ranking in organic search engine results • Search Engine Marketing (SEM) • Increase ranking in paid search listings

  5. SEO Factors • Inlinks & page ranks • Keyword density • Indexation • Errors: broken links • Outlinks

  6. SEM Factors • Bid amt • Clickthru rate • Creative • Landing page

  7. What Advertisers Need • Keyword selection/categorization • Bid optimization • Click fraud prevention/detection • Landing page optimization • Competitor intelligence

  8. Pains • Large-scale/dynamic • Keywords • Pages/links • Competitors • Data availability • Lack automation • Lack scalability

  9. BI for SEO/SEM Value/Impact Data Driven Applications Insights Data Processing Data Mining Data

  10. Questions • Value/Impact • How do we measure? • What are the potentials? • What are the challenges? • Data/Data Processing/Data Mining • What is the relevant data? • What are some applicable data mining techniques? • What are the challenges? • Data Driven Applications/Insights • What are the automation opportunities? • What are the challenges? • What are the potential KDD research topics?

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