DOCSLIB.ORG

To Start the Social Selling Transformation Table of Contents

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
To Start the Social Selling Transformation Table of Contents 17 TIPS TO START THE SOCIAL SELLING TRANSFORMATION TABLE OF CONTENTS STARTING THE SOCIAL SELLING TRANSFORMATION JOURNEY ..........................................3 STEP 1: CREATE A PROFESSIONAL BRAND ........................................................................4 STEP 2: FIND THE RIGHT PEOPLE ......................................................................................6 STEP 3: BUILD YOUR PIPELINE ............................................................................................... 8 STEP 4: STRATEGICALLY EXPAND YOUR NETWORK ...........................................................10 STEP 5: ENGAGE WITH INSIGHTS .....................................................................................11 STEP 6: BUILD STRONG RELATIONSHIPS .........................................................................13 STEP 7: MEASURE HOW WELL YOU’VE ADOPTED SOCIAL SELLING .................................15 PUTTING THE SOCIAL WHEELS IN MOTION ......................................................................17 ABOUT LINKEDIN AND DEMAND GEN REPORT ................................................................19 02 STARTING THE SOCIAL SELLING TRANSFORMATION JOURNEY In our earlier piece 7 Ways Sales Professionals Drive Revenue With Social Selling, we provided a high-level overview of the concept Social Selling Defined: and principles of Social Selling. Since the publication of that E-book, social media has become even more central to the way businesses of Social Selling leverages your professional brand to all kinds drive new prospects and clients. fill your pipeline with the right people, insights and relationships. One of the reasons for this development is that social media platforms have added features and functions that make them more flexible and With that in mind, let’s dig into the details. easier to use. Even more important, however, is that both customers This E-book will give you concrete tips drawn from the experience and salespeople have by-and-large become social media natives. In of some of the world’s foremost experts on Social Selling about the other words, instead of simply using social media as a high-tech way actions you can take to gain more opportunities, close more deals to connect and prospect, people are now more likely to view it as the and drive more revenue. most visible representation of a person or company’s professional brand. As such, Social Selling is the most effective way to Follow these seven steps to begin building a profitable Social Selling leverage that brand to fill your pipeline with the right people, campaign today. insights and relationships. 3 Janet Zen STEP 1: Passionate Client Advocate * Specialist in Providing Solutions to Complex Challenges CREATE A PROFESSIONAL BRAND Greater Chicago Area | Digital Media Current Awesome Media Company Previous All-Star Sales Group Many salespeople treat their social media profiles as an afterthought, Education Indiana University 500 including no more than the bare minimum of identifying information. Send a message Endorse connections This is the 21st century equivalent of showing up to a meeting with a Contact Info rumpled suit and muddy shoes. Relationship Connected 1 year ago Your profile — especially your LinkedIn profile — is your professional Posts online brand. Instead of viewing your profile as your resume, look Published by Janet 6,075 See more followers at it as the place to demonstrate your value to clients, partners and prospects. THE RPM READINESS GUIDE Insights To Determine Whether Your Organization Is Prepared For Revenue Performance Management And Best Practices In addition to contact information, include robust calls-to-action To Start You On The Right Path To A Successful Journey ➡ DOES AN ORGANIZATION NEED TO BE BIG TO BE READY FOR RPM? ➡ THE PEOPLE POWER BEHIND RPM SUCCESS that guide prospects on how to move further down the relationship ➡ THE POTENTIAL PAYOFFS OF AN RPM JOURNEY Presented by Sponsored by funnel with you. Use the Headline, Summary and Interests sections to REPORT 7 Ways Sales Professionals Drive The RPM Readiness Guide Benchmarking Marketing Revenue with Social Selling April 2, 2014 Automation convey various elements of your experience, personality and skill set May 20, 2014 March 26, 2014 that highlight your ability to solve problems and make things happen. Background Summary Social Selling Transformation Tip #1 Success consists of going from failure to failure without loss of enthusiasm. - Winston Churchill “The work you do on your profile is going to Thanks for visiting my profile. I have included many items you may find informative. set the stage with the biggest impact. You Sales Professionals: Learn how to use LinkedIn http://linkd.in/1odaWW6 I’m an open networker. My connection philosophy is easy “Can I add value to you or can you add want to go from an aesthetic profile to creating value to me” if any of those are met, we can connect. If you would like to connect, please customize something that is more interactive by adding your message. I rarely accept generic connection requests. *********** Rich Media, links, and valuable content.” I am honored to be one of the most recognized social experts in the technology industry. With 10+ years of sales experience and a passion for social media, I have become an evangelist for social – Koka Sexton, selling, a topic that I promote through global speaking engagements and customer trainings. My expertise extends beyond my knowledge of social networks like LinkedIn, Twitter and social Sr. Social Marketing Manager, LinkedIn applications into my skill at employing them to drive lead generation, create new opportunities, and engage customers. 4 Click to share! Background Summary Success consists of going from failure to failure without loss of enthusiasm. - Winston Churchill Thanks for visiting my profile. I have included many items you may find informative. Sales Professionals: Learn how to use LinkedIn http://linkd.in/1odaWW6 I’m an open networker. My connection philosophy is easy “Can I add value to you or can you add Leaders in the sales engagement space are now stressing that it is value to me” if any of those are met, we can connect. If you would like to connect please customize your message. I rarely accept generic connection requests. critical for today’s sales professionals to connect with their customers *********** and prospects on a personal level. I am honored to be one of the most recognized social experts in the technology industry. With ten+ years of sales experience and a passion for social media, I have become an evangelist for social selling, a topic that I promote through global speaking engagements and customer trainings. It is also important that you optimize your profile for the LinkedIn My expertise extends beyond my knowledge of social networks like LinkedIn, Twitter and Social applications into my skill at employing them to drive lead generation, create new opportunities, and search engines by including keywords that prospects are most likely engage customers. to use when searching for services your company provides. Take Specialties: advantage of video and other interactive features to highlight the best *********** features of your brand — both organizational and personal. » Social Media Strategy » Social Media Channels » Content Marketing » Marketing » Sales 2.0 » Social Selling Training Social Selling Transformation Tip #2 » Social Selling Best Practices » Community Manager “Unless you are looking for a job, your profile » Social Media Tools isn’t about you, it’s about them. What value » LinkedIn for Marketing do you bring? Start with your headline — just » LinkedIn for Sales having your company name and title is not » Social Media Marketing engaging. What does your prospect or client » Customer Engagement care about? The whole point is to get them to continue looking through your profile, eventually Skills & Endorsements to reach out.” – Brynne Tillman, Top Skills Click to share! President & CEO, Social Sales Link 5 STEP 2: FIND THE RIGHT PEOPLE LinkedIn has one of the most powerful search engines in existence, and it’s specifically designed for professional networking and Social Selling Transformation Tip #3 business development. If you aren’t proactively searching for new “Most influential people use at least one social people to interact with, you are missing out on a big part of social monitoring tool to be notified when something media’s potential to be a growth driver for your business. is written about them on the web. I know of sales teams that engage with prospects by With Social Selling, you have access to a web of connections that commenting on their blog posts (or comments includes not only the people you know directly, but all the people they make on other people’s blog posts), re- they know, and so on. LinkedIn gives you the ability to tap into a vast tweeting something they say, or mentioning something about ecosystem of these potential prospects, all of whom can be traced them in a LinkedIn status update. This allows the sales person to directly back to your core professional circle. be known by the prospect so when that sales person calls they Salespeople who do a high quantity of LinkedIn searches substantially are not a complete unknown and they have a reference point to outperform those who neglect this feature. And those who use the full engage the prospect in a conversation.” suite of tools designed to maximize social search perform best of all. – Craig Elias, Chief Catalyst, Shift Selling
Load more

Recommended publications
  • Metadata for Semantic and Social Applications
    etadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008M will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web — the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Metadata for Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their Semantic and information in interoperable ways (”participatory metadata”) is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. Social Applications DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice. Edited by Jane Greenberg and Wolfgang Klas DC-2008
    [Show full text]
  • A Comparison of Information Seeking Using Search Engines and Social Networks
    A Comparison of Information Seeking Using Search Engines and Social Networks Meredith Ringel Morris1, Jaime Teevan1, Katrina Panovich2 1Microsoft Research, Redmond, WA, USA, 2Massachusetts Institute of Technology, Cambridge, MA, USA {merrie, teevan}@microsoft.com, [email protected] Abstract et al. 2009 or Groupization by Morris et al. 2008). Social The Web has become an important information repository; search engines can also be devised using the output of so- often it is the first source a person turns to with an informa- cial tagging systems such as delicious (delicious.com). tion need. One common way to search the Web is with a Social search also encompasses active requests for help search engine. However, it is not always easy for people to from the searcher to other people. Evans and Chi (2008) find what they are looking for with keyword search, and at describe the stages of the search process when people tend times the desired information may not be readily available to interact with others. Morris et al. (2010) surveyed Face- online. An alternative, facilitated by the rise of social media, is to pose a question to one‟s online social network. In this book and Twitter users about situations in which they used paper, we explore the pros and cons of using a social net- a status message to ask questions of their social networks. working tool to fill an information need, as compared with a A well-studied type of social searching behavior is the search engine. We describe a study in which 12 participants posting of a question to a Q&A site (e.g., Harper et al.
    [Show full text]
  • A Federated Search and Social Recommendation Widget
    A Federated Search and Social Recommendation Widget Sten Govaerts1 Sandy El Helou2 Erik Duval3 Denis Gillet4 Dept. Computer Science1,3 REACT group2,4 Katholieke Universiteit Leuven Ecole Polytechnique Fed´ erale´ de Lausanne Celestijnenlaan 200A, Heverlee, Belgium 1015 Lausanne, Switzerland fsten.govaerts1, [email protected] fsandy.elhelou2, denis.gillet4g@epfl.ch ABSTRACT are very useful, but their generality can sometimes be an ob- This paper presents a federated search and social recommen- stacle and this can make it difficult to know where to search dation widget. It describes the widget’s interface and the un- for the needed information [2]. Federated searching over derlying social recommendation engine. A preliminary eval- collections of topic-specific repositories can assist with this uation of the widget’s usability and usefulness involving 15 and save time. When the user sends a search request, the subjects is also discussed. The evaluation helped identify us- federated search widget collects relevant resources from dif- ability problems that will be addressed prior to the widget’s ferent social media sites [3], repositories and search engines. usage in a real learning context. Before rendering aggregated results, the widget calls a per- sonalized social recommendation service deemed as crucial Author Keywords in helping users select relevant resources especially in our federated search, social recommendations, widget, Web, per- information overload age [4,5]. The recommendation ser- sonal learning environment (PLE), Pagerank, social media, vice ranks these resources according to their global popu- Web 2.0 larity and most importantly their popularity within the social network of the target user. Ranks are computed by exploiting attention metadata and social networks in the widget.
    [Show full text]
  • Unicorn: a System for Searching the Social Graph
    Unicorn: A System for Searching the Social Graph Michael Curtiss, Iain Becker, Tudor Bosman, Sergey Doroshenko, Lucian Grijincu, Tom Jackson, Sandhya Kunnatur, Soren Lassen, Philip Pronin, Sriram Sankar, Guanghao Shen, Gintaras Woss, Chao Yang, Ning Zhang Facebook, Inc. ABSTRACT rative of the evolution of Unicorn's architecture, as well as Unicorn is an online, in-memory social graph-aware index- documentation for the major features and components of ing system designed to search trillions of edges between tens the system. of billions of users and entities on thousands of commodity To the best of our knowledge, no other online graph re- servers. Unicorn is based on standard concepts in informa- trieval system has ever been built with the scale of Unicorn tion retrieval, but it includes features to promote results in terms of both data volume and query volume. The sys- with good social proximity. It also supports queries that re- tem serves tens of billions of nodes and trillions of edges quire multiple round-trips to leaves in order to retrieve ob- at scale while accounting for per-edge privacy, and it must jects that are more than one edge away from source nodes. also support realtime updates for all edges and nodes while Unicorn is designed to answer billions of queries per day at serving billions of daily queries at low latencies. latencies in the hundreds of milliseconds, and it serves as an This paper includes three main contributions: infrastructural building block for Facebook's Graph Search • We describe how we applied common information re- product. In this paper, we describe the data model and trieval architectural concepts to the domain of the so- query language supported by Unicorn.
    [Show full text]
  • The Top 10 Alternative Search Engines (ASE) - Within Selected Categories Ranked by Webometric Indicators
    The Top 10 Alternative search Engines (ASE) - within Selected Categories Ranked by Webometric Indicators Bernd Markscheff el Bastian Eine Within the scientifi c fi eld of webometrics many research objects had been analyzed and compared with the help of webometric indicators (e.g., the performance of a whole country, a research group or an indi- vidual). This paper presents a ranking of ASEs which is based on webo- metric indicators. As search engines have become an essential tool for searching for information on the web many alternative search services have specialized in fi nding topic- or format-specifi c search results. By creating a ranking of these ASEs within selected categories we present an overview of the ASEs which are currently available. Through webo- metric indicators the ASEs were compared and the most popular ASEs of the respective categories determined. Keywords: Search engines, Webometric indicators Bernd Markscheff el Chair of Information and 1. Introduction Knowledge Management Technische Universität While searching for information on the web, search en- Ilmenau gines can assist the user to fi nd satisfying results. Although, P.O. Box 100565 just a few dominate the search engine market a large num- 98684 Ilmenau ber of diff erent web search services and tools exist (Maaβ Germany et al., [1]). Beside the well known universal search engines bernd.markscheff el@ like Google, Yahoo and Bing several ASEs are specialized tuilmenau.de in providing options to search for special document types, specifi c topics or time-sensitive information (Gelernter [2]; Bastian Eine Consultant for Search Engine Originally presented at the 7th International Conference on Webometrics, Optimization and Online Informetrics and Scientometrics (WIS) and 12th COLLNET Meeting, Marketing September 20–23, 2011, Istanbul Bilgi University, Istanbul, Turkey.
    [Show full text]
  • Searching the Enterprise
    R Foundations and Trends• in Information Retrieval Vol. 11, No. 1 (2017) 1–142 c 2017 U. Kruschwitz and C. Hull • DOI: 10.1561/1500000053 Searching the Enterprise Udo Kruschwitz Charlie Hull University of Essex, UK Flax, UK [email protected] charlie@flax.co.uk Contents 1 Introduction 2 1.1 Overview........................... 3 1.2 Examples........................... 5 1.3 PerceptionandReality . 9 1.4 RecentDevelopments . 10 1.5 Outline............................ 11 2 Plotting the Landscape 13 2.1 The Changing Face of Search . 13 2.2 DefiningEnterpriseSearch . 14 2.3 Related Search Areas and Applications . 17 2.4 SearchTechniques. 34 2.5 Contextualisation ...................... 37 2.6 ConcludingRemarks. 49 3 Enterprise Search Basics 52 3.1 StructureofData ...................... 53 3.2 CollectionGathering. 59 3.3 SearchArchitectures. 63 3.4 Information Needs and Applications . 68 3.5 SearchContext ....................... 76 ii iii 3.6 UserModelling........................ 78 3.7 Tools, Frameworks and Resources . 81 4 Evaluation 82 4.1 RelevanceandMetrics. 83 4.2 Evaluation Paradigms and Campaigns . 85 4.3 TestCollections ....................... 89 4.4 LessonsLearned ....................... 94 5 Making Enterprise Search Work 95 5.1 PuttingtheUserinControl . 96 5.2 Relevance Tuning and Support . 103 6 The Future 110 6.1 GeneralTrends........................ 110 6.2 TechnicalDevelopments. 111 6.3 Moving towards Cooperative Search . 113 6.4 SomeResearchChallenges . 114 6.5 FinalWords ......................... 117 7 Conclusion 118 Acknowledgements 120 References 121 Abstract Search has become ubiquitous but that does not mean that search has been solved. Enterprise search, which is broadly speaking the use of information retrieval technology to find information within organisa- tions, is a good example to illustrate this.
    [Show full text]
  • Collaborative Information Access: a Conversational Search Approach
    ICCBR Workshop on Reasoning from Experiences on the Web (WebCBR-09), Seattle Collaborative Information Access: A Conversational Search Approach Saurav Sahay, Anushree Venkatesh, and Ashwin Ram College of Computing Georgia Institute of Technology Atlanta, GA Abstract. Knowledge and user generated content is proliferating on the web in scientific publications, information portals and online social me- dia. This knowledge explosion has continued to outpace technological innovation in efficient information access technologies. In this paper, we describe the methods and technologies for ‘Conversational Search’ as an innovative solution to facilitate easier information access and reduce the information overload for users. Conversational Search is an interactive and collaborative information finding interaction. The participants in this interaction engage in social conversations aided with an intelligent information agent (Cobot) that provides contextually relevant search recommendations. The collaborative and conversational search activity helps users make faster and more informed search and discovery. It also helps the agent learn about conversations with interactions and social feedback to make better recommendations. Conversational search lever- agesthe social discovery process by integrating web information retrieval along with the social interactions. 1 Introduction Socially enabled online information search (social search) is a new phenomenon facilitated by recent Web technologies. This collaborative social search involves finding specific people in your network who have the knowledge you’re look- ing for or finding relevant information based on one’s social network. Social psychologists have experimentally validated that the act of social discussions have facilitated cognitive performance[1]. People in social groups can provide solutions (answers to questions)[2], pointers to databases or other people (meta- knowledge)[2][3] , validation and legitimation of ideas[2][4], can serve as mem- ory aids[5] and help with problem reformulation[2].
    [Show full text]
  • Natural Search User Interfaces
    Natural Search User Interfaces Prof. Marti Hearst UC Berkeley March/April , 2012 Book full text freely available at: http://searchuserinterfaces.com What works well in search now? Faceted Navigation 3 Real-Time Suggestions http://netflix.com http://www.imamuseum.org/ 4 Forecasting the Future First: What are the larger trends? In technology? In society? Next: Project out from these. Preferences for Preferences for Preferences for Audio / Video / Touch Social Interaction Natural Language “Natural” Interfaces Statistical Analysis of Wide adoption of social Enormous Collections Advances in media & user-generated UI Design Of Behavioral and Other Data content 6 Trend: More Natural Queries Trend: Longer, more natural queries § The research suggests people prefer to state their information need rather than use keywords. § But after first using a search engine they quickly learned that full questions resulted in failure. 8 Trend: Longer, more natural queries § The research suggests people prefer to state their information need rather than use keywords. § But after first using a search engine they quickly learned that full questions resulted in failure. § Average query length continues to increase § In 2010 vs 2009, searches of 5-8 words were up 10%, while 1-2 word searches were down. 9 Trend: Longer, more natural queries § Social Question Answering Sites: § Information worded as questions increasing available § with the questions that the audience really wants the answers to, and § written in the language the audience wants to use. § AND with
    [Show full text]
  • 1 Public Records Resources Online
    Public Records Resources Online How to Find Everything There Is to Know About "Mr./Ms. X" *Please see disclaimer at end of document* Summary of public records on Mr. / Ms. X . Starting with one or more Background Reports from the sources below can help provide an overview of where the person has lived and worked, as well as other pertinent information for searching, such as middle name or initial. They might also contain adverse filings and licensing information that you can later verify in other sources. Examples of vendors that provide background reports (for a fee): Westlaw/CLEAR (Thomson Reuters) $ Lexis/Accurint $ TLO $ His/her social security number is . These tools can help verify if an SSN is valid and related to a living person. SSN Validator Selective Service Online Verification He/she was born / died / naturalized . In addition to the Summary Reports in the first section of this guide, official death records may be found in resources on the federal, state, and local levels. The Genealogy Resources section of this guide might have other helpful resources for death records. Social Security Death Records The official federal record is the Social Security Death Index (SSDI). Only the subscription databases, such as Lexis, Westlaw, and TLO (all $) will have the most recent SSDI records, due to privacy restrictions. Try variations of spellings, or using only the last name and birth or death year and location if you're not finding an SSDI record. Ancestry Library $ Genealogy Bank SSDI Research Guide SSDI Databases Online State and Local Death, Burial, and Cemetery Records State and local death records will often provide more detailed information than an SSDI record, but they are not as easy to find.
    [Show full text]
  • On the Collaboration Support in Information Retrieval
    Open Archive TOULOUSE Archive Ouverte ( OATAO ) OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 19042 To link to this article : DOI : 10.1145/3092696 URL : http://doi.org/10.1145/3092696 To cite this version : Soulier, Laure and Tamine-Lechani, Lynda On the collaboration support in Information Retrieval. (2017) ACM Computing Surveys, vol. 50 (n° 4). pp. 1. ISSN 0360-0300 Any correspondence concerning this service should be sent to the repository administrator: [email protected] On the Collaboration Support in Information Retrieval LAURE SOULIER, Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6 LYNDA TAMINE, IRIT, Université de Toulouse, UPS Collaborative Information Retrieval (CIR) is a well-known setting in which explicit collaboration occurs among a group of users working together to solve a shared information need. This type of collaboration has been deemed as bene!cial for complex or exploratory search tasks. With the multiplicity of factors im- pacting on the search e#ectiveness (e.g., collaborators’ interactions or the individual perception of the shared information need), CIR gives rise to several challenges in terms of collaboration support through algorithmic approaches. More particularly, CIR should allow us to satisfy the shared information need by optimizing the collaboration within the search session over all collaborators, while ensuring that both mutually bene!cial goals are reached and that the cognitive cost of the collaboration does not impact the search e#ectiveness.
    [Show full text]
  • Search Engine Optimization and the Connection with Knowledge Graphs
    FACULTY OF EDUCATION AND BUSINESS STUDIES Department of Business and Economics Studies Search Engine Optimization and the connection with Knowledge Graphs Milla Marianna Hietala Oliver Marshall 2021 Student thesis, Master degree (one year), Credits Business Administration Master Programme in Business Administration (MBA): Business Management Master Thesis in Business Administration 15 Credits Supervisor: Ehsanul Huda Chowdhury Examiner: Maria Fregidou-Malama Abstract Title: Search Engine Optimization and the connection with Knowledge Graphs Level: Thesis for Master’s Degree in Business Administration Authors: Milla Marianna Hietala and Oliver Marshall Supervisor: Ehsanul Huda Chowdhury Examiner: Maria Fregidou-Malama Date: 28-01-2021 Aim: The aim of this study is to analyze the usage of Search Engine Optimization and Knowledge Graphs and the connection between them to achieve profitable business visibility and reach. Methods: Following a qualitative method together with an inductive approach, ten marketing professionals were interviewed via an online questionnaire. To conduct this study both primary and secondary data was utilized. Scientific theory together with empirical findings were linked and discussed in the analysis chapter. Findings: This study establishes current Search Engine Optimization utilization by businesses regarding common techniques and methods. We demonstrate their effectiveness on the Google Knowledge Graph, Google My Business and resulting positive business impact for increased visibility and reach. Difficulties remain in accurate tracking procedures to analyze quantifiable results. Contribution of the thesis: This study contributes to the literature of both Search Engine Optimization and Knowledge Graphs by providing a new perspective on how these subjects have been utilized in modern marketing. In addition, this study provides an understanding of the benefits of SEO utilization on Knowledge Graphs.
    [Show full text]
  • An Innovative Approach for Online Meta Search Engine Optimization
    The 6th Conference on Software, Knowledge, Information Management and Applications, Chengdu, China, September 9-11 2012, #57. 1 An Innovative Approach for online Meta Search Engine Optimization Jai Manral and Mohammed Alamgir Hossain Computational Intelligence Research Group School of Computing Engineering and Information Sciences Northumbria University, Newcastle Upon Tyne, NE1 8ST, UK {jai.manral; alamgir.hossain}@northumbria.ac.uk This paper presents an approach to identify efficient techniques used in Web Search Engine Optimization (SEO). Understanding SEO factors which can influence page’s ranking in search engine is significant for webmasters who wish to attract large number of users to their website. Different from previous relevant research, in this study we developed an intelligent Meta search engine which aggregates results from various search engines and ranks them based on several important SEO parameters. The research tries to establish that using more SEO parameters in ranking algorithms helps in retrieving better search results thus increasing user satisfaction. Initial results generated from Meta search engine outperformed existing search engines in terms of better retrieved search results with high precision. Index Terms— Search Engine Optimization, Meta Search Engine, Page Ranking, WWW. selects its preferred web-pages. Ranking is based on various I. INTRODUCTION parameters, some are known others not. Search engine optimizers work hard to use these parameters and rank their The information on the web is prodigious; searching web-pages higher in the result. Every researcher has its own relevant information is difficult for users. The accuracy of opinion of using SEO techniques. In order to learn how to search results is measured by relevancy of query term to web- optimize webpages and their relevancy to search engines page pages ranked and displayed by search engines.
    [Show full text]