Chapter 6. Attracting Buyers with Search, Semantic, and Recommendation Technology

Transcription

1 Attracting Buyers with Search, Semantic, and Recommendation Technology

2 Learning Objectives Using Search Technology for Business Success Organic Search and Search Engine Optimization Recommendation Engines Pay-Per- Click and Paid Search Strategies A Search for Meaning Semantic Technology

3 Using Search Technology for Business Success How Search Engines Work Search Engine: an application for locating webpages or other content on a computer network using spiders. Spiders: web bots (or bots); small computer programs designed to perform automated, repetitive tasks over the Internet. Bots scan webpages and return information to be stored in a page repository.

4 Using Search Technology for Business Success

5 Using Search Technology for Business Success Web Directories Typically organized by categories. Webpage content is usually reviewed by directory editors prior to listing. Page Repository: data structure that stores and manages information from a large number of webpages, providing a fast and efficient means for accessing and analyzing the information at a later time.

6 Using Search Technology for Business Success Figure 6.5 Components of crawler search engines (Grehan, 2002).

7 Using Search Technology for Business Success Figure 6.6 Search engines use invested indexes to efficiently locate Web content based on search query terms.

8 Using Search Technology for Business Success Why Search is Important for Business Enterprise search tools allow organizations to share information internally. An organizations ability to share knowledge among employees is vital to its ability to compete. Information is not always in the same format.

9 Using Search Technology for Business Success Why Search is Important for Business Structured data: information with a high degree of organization, such that inclusion in a relational database is seamless and readily searchable by simple, straightforward search engine algorithms or other search operations. Unstructured data: messy data not organized in a systematic or predefined way.

10 Using Search Technology for Business Success Security Issues Limited access to certain data via job function or clearance. Request log audits should be conducted regularly for patterns or inconsistencies. Enterprise Vendors Used to treat data in large companies like Internet data but include information management tools.

11 Using Search Technology for Business Success Recommendation Engines Attempt to anticipate information users might be interested in to recommend new products, articles, videos, etc. Search Engine Marketing A collection of online marketing strategies and tactics that promote brands by increasing their visibility in search engine results pages (SERPs) through optimization and advertising.

12 Using Search Technology for Business Success Search Engine Marketing Basic search types: Informational search Navigational search Transactional search Strategies and tactics produce two outcomes: Organic search listings Paid search listings Pay-per-click (produce click-through rates) Social media optimization

13 Using Search Technology for Business Success Mobile Search Technically configured mobile sites Content designed for mobile devices Business search Focused search Filetype Advanced search Search tools button Search history

14 Using Search Technology for Business Success Real-time Search Google Trends Google Alerts Twitter Search Social Bookmarking Search Page links tagged with keywords Specialty Search: Vertical Search Programmed to focus on webpages related to a particular topic and to drill down by crawling pages that other search engines are likely to ignore.

15 Using Search Technology for Business Success 1. What is the primary difference between a web directory and a crawler based search engine? 2. What is the purpose of an index in a search engine? 3. Describe the page-ranking method most commonly associated with Google s success. 4. What is the difference between search engine optimization and PPC advertising? 5. Describe three different real-time search tools.

16 Learning Objectives Using Search Technology for Business Success Organic Search and Search Engine Optimization Recommendation Engines Pay-Per- Click and Paid Search Strategies A Search for Meaning Semantic Technology

17 Organic Search and Search Engine Optimization Search Engine Optimization Keyword conversion rates: the likelihood that using a particular keyword to optimize a page will result in conversions*. Ranking factors Reputation or popularity PageRank: Google s algorithm based on the assumption that people are more likely to link a high-quality website than poor-quality site. Backlinks: external links that point back to a site. Relevancy User Satisfaction Conversions: when a website visitor converts to a buyer

18 Organic Search and Search Engine Optimization Inbound marketing An approach to marketing that emphasizes SEO, content Marketing, and social media strategies to attract customers. Outbound marketing Traditional approach using mass media advertising.

19 Organic Search and Search Engine Optimization Black Hat SEO Gaming the system or tricking search engines into ranking a site higher than its content deserves. 1. Link spamming: generating backlinks toward SEO, not adding user value. 2. Keyword tricks: embedded high-value keywords to drive up traffic statistics. 3. Ghost text: text hidden in the background that will affect page ranking 4. Shadow (ghost or cloaked) pages: created pages optimized to attract lots of people through redirect.

20 Organic Search and Search Engine Optimization 1. Search engines use many different clues about the quality of a website s content to determine how a page should be ranked in search results. These clues fall into three primary categories: Reputation or Popularity, Relevancy, and User Satisfaction. Explain the rationale for using each of these three categories as an indicator of a website s content quality. 2. Backlinks were a key factor in Google s original PageRank algorithm. Explain what a backlink is and why Google has reduced its emphasis on backlinks and instead uses many other additional factors in its ranking algorithm? 3. Explain why so-called black hat SEO tactics are ultimately short-sighted and can lead to significant consequences for businesses that use them. 4. How do organizations evaluate the effectiveness of their search engine optimization (SEO) strategies and tactics? 5. Explain why providing high quality, regularly updated content is the most important aspect of any SEO strategy.

21 Learning Objectives Using Search Technology for Business Success Organic Search and Search Engine Optimization Recommendation Engines Pay-Per- Click and Paid Search Strategies A Search for Meaning Semantic Technology

22 Pay-Per-Click and Paid Search Strategies Pay-Per-Click PPC advertising campaigns: 1. Set an overall budget 2. Create ads 3. Select associated keywords 4. Set up billing account information

23 Pay-Per-Click and Paid Search Strategies Paid Search Advertising Metrics Click through rates (CTR): used to evaluate keyword selection and ad copy campaign decisions. Keyword conversion: should lead to sales, not just visits. Cost of customer acquisition (CoCA): amount of money spent to attract a paying customer. Return on advertising spend (ROAS): overall financial effectiveness.

24 Pay-Per-Click and Paid Search Strategies Quality Score Determined by factors related to the user s experience. Expected keyword click-through-rate (CTR) The past CTR of your URL (web address) Past effectiveness Landing page quality Relevance of keywords to ads Relevance of keywords to customer search Ad performance on difference devices

25 Pay-Per-Click and Paid Search Strategies 1. What would most people say is the fundamental difference between organic listings and PPC listings on a search engine? 2. What are the four primary steps to creating a PPC advertising campaign on search engines? 3. In addition to the bid price for a particular keyword, what other factor(s) influence the likelihood that an advertisement will appear on a search results page? Why don t search engines just rely on the advertisers bid when deciding what ads will appear on the search results page? 4. How do webpage factors influence the effectiveness of PPC advertisements? 5. Describe four metrics that can be used to evaluate the effectiveness of a PPC advertising campaign.

26 Learning Objectives Using Search Technology for Business Success Organic Search and Search Engine Optimization Recommendation Engines Pay-Per- Click and Paid Search Strategies A Search for Meaning Semantic Technology

27 A Search for Meaning Semantic Technology Semantic Web Meaningful computing using metadata: application of natural language processing (NLP) to support information retrieval, analytics, and data-integration that compass both numerical and unstructured information. Semantic Search Process of typing something into a search engine and getting more results than just those that feature the exact keyword typed into the search box. Metadata Data that describes and provides information about other data.

28 A Search for Meaning Semantic Technology

29 A Search for Meaning Semantic Technology Web 3.0 Developed by W3C. Resource description framework (RDF) Used to represent information about resources Web ontology language (OWL) Language used to categorize and accurately identify the nature of Internet things SPARCQL protocol Used to write programs that can retrieve and manipulate data scored in RDF RDF query language (SPARCQL)

30 A Search for Meaning Semantic Technology Semantic Search Features and Benefits Related searches/queries Reference results Semantically annotated results Full-text similarity search Search on semantic/syntactic annotations

31 A Search for Meaning Semantic Technology Semantic Search Features and Benefits Concept search Ontology-based search Semantic Web search Faceted search Clustered search Natural language search

32 A Search for Meaning Semantic Technology 1. List five different practical ways that semantic technology is enhancing the search experience of users. 2. How do metadata tags facilitate more accurate search results? 3. Briefly describe the three evolutionary stages of the Internet? 4. Define the words context, personalization, and vertical search and explain how they make for more powerful and accurate search results. 5. What are the three languages developed by the W3C and associated with the semantic Web?

33 Learning Objectives Using Search Technology for Business Success Organic Search and Search Engine Optimization Recommendation Engines Pay-Per- Click and Paid Search Strategies A Search for Meaning Semantic Technology

34 Recommendation Engines Recommendation Filters Content-based filtering: products based on product features in past interactions. Collaborative filtering: based on user s similarity to other people.

35 Recommendation Engines Limitations of Recommendation Engines Cold start or new user: challenging since no starting point or preexisting information exists. Sparsity: unable to create critical mass due to few ratings or similar groups are unidentifiable. Limited feature content: manual information entry is prohibitive where there are many products. Overspecialization: narrowly configured results may only recommend the same item, but in different sizes or colors.

36 Chapter 5 Recommendation Engines Hybrid Recommendation Engines Weighted hybrid: results from different recommenders are assigned weight and combined numerically to determined final recommendations. Mixed hybrid: results from different recommenders presented along-side of each other. Cascade hybrid: results from different recommenders assigned a rank or priority. Mixed hybrid: results from different recommenders combines results from two recommender systems from the same technique category.

37 Recommendation Engines 1. How is a recommendation engine different from a search engine? 2. Besides e-commerce websites that sell products, what are some other ways that recommendation engines are being used on the Web today? 3. What are some examples of user information required by recommendation engines that use collaborative filtering? 4. Before implementing a content-based recommendation engine, what kind of information would website operators need to collect about their products? 5. What are the four distinct methodologies used by recommender systems to create recommendations? 6. What is a recommendation engine called that combines different methodologies to create recommendations? What are three ways these systems combine methodologies?