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Keyword Discovery: Search Engine Optimization

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Information about Keyword Discovery: Search Engine Optimization
Business & Mgmt

Published on December 1, 2008

Author: searchengineoptimization

Source: slideshare.net

Description

Advanced Keyword Discovery (Organic Search Engine Optimization) for Online Marketings
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Introduction Keyword Discovery Matters More Than Ever As search matures, Keyword Discovery becomes more important Increased competition Pickier users Good Keyword Discovery = Happier Clients Quicker return on investment Easily managed expectations Better budgeting Good Keyword Discovery = Higher Profits Meet client needs with minimal effort Choose better investments and better clients Keyword Discovery Matters More than Ever

As search matures, Keyword Discovery becomes more important

Increased competition

Pickier users

Good Keyword Discovery = Happier Clients

Quicker return on investment

Easily managed expectations

Better budgeting

Good Keyword Discovery = Higher Profits

Meet client needs with minimal effort

Choose better investments and better clients

Theory Traffic-on-Investment, the ROI of SEO Search Popularity is Meaningless without Competitive Data Keyword Competitiveness is Meaningless without Popularity Data Popularity/Competitiveness = Traffic-on-Investment Judging competitiveness measurements: The right competitiveness measurements allow an SEO to determine the ToI of any given keyword. To what degree does this measurement indicate a webmaster’s intent to compete for the targeted keyword? To what degree does this measurement indicate an obstacle to ranking for the targeted keyword? Traffic-on-Investment, the ROI of SEO

Search Popularity is Meaningless without Competitive Data

Keyword Competitiveness is Meaningless without Popularity Data

Popularity/Competitiveness = Traffic-on-Investment

Judging competitiveness measurements: The right competitiveness measurements allow an SEO to determine the ToI of any given keyword.

To what degree does this measurement indicate a webmaster’s intent to compete for the targeted keyword?

To what degree does this measurement indicate an obstacle to ranking for the targeted keyword?

Keyword Sources Data integrity and relativity. Data Integrity Does the data include automated searches? Is there an incentive to game the data collection? eg: Yahoo Relativity and Consistency Seasonal Data Private keyword sources with API: Trellian’s Keyword Discovery WordTracker Wordze Keyword Sources

Data Integrity

Does the data include automated searches?

Is there an incentive to game the data collection? eg: Yahoo

Relativity and Consistency

Seasonal Data

Private keyword sources with API:

Trellian’s Keyword Discovery

WordTracker

Wordze

Formula Construction The Aggregate Variables Total matches ( t ) total number of results returned when the keyword is searched without quotes shortcomings: large volume of incidental occurrences of keywords. Exact matches ( e ) total number of results returned when the keyword is searched within quotes shortcomings: some incidental occurrences of keywords. InURL matches ( u ) total number of results returned when the keyword is searched within quotes after inurl: shortcomings: overstates competitiveness of single keyword phrases InAnchor matches ( a ) total number of results returned when the keyword is searched within quotes after inanchor: InTitle matches ( l ) total number of results returned when the keyword is searched within quotes after intitle: shortcomings: some incidental occurrences, especially of single keyword phrases InText matches ( x ) total number of results returned when the keyword is se arched within quotes after intext: shortcomings: some incidental occurrences of keywords The Aggregate Variables

Total matches ( t ) total number of results returned when the keyword is searched without quotes shortcomings: large volume of incidental occurrences of keywords.

Exact matches ( e ) total number of results returned when the keyword is searched within quotes shortcomings: some incidental occurrences of keywords.

InURL matches ( u ) total number of results returned when the keyword is searched within quotes after inurl: shortcomings: overstates competitiveness of single keyword phrases

InAnchor matches ( a ) total number of results returned when the keyword is searched within quotes after inanchor:

InTitle matches ( l ) total number of results returned when the keyword is searched within quotes after intitle: shortcomings: some incidental occurrences, especially of single keyword phrases

InText matches ( x ) total number of results returned when the keyword is se arched within quotes after intext: shortcomings: some incidental occurrences of keywords

Formula Construction The Ranking Page Variables Ranking Page Links ( p l ) total number of inbound links to the page ranking for a particular keyword shortcomings: many of these links may not include targeted keyword. Ranking Page PageRank ( p p ) Google PageRank of page ranking for a particular keyword shortcomings: slow updates. Ranking Page InTitle ( p t ) occurrence of keyword in title of ranking page Ranking Page InText, H1s, etc. ( p x ) occurrence of keyword in various HTML tags of ranking page The Ranking Page Variables

Ranking Page Links ( p l ) total number of inbound links to the page ranking for a particular keyword shortcomings: many of these links may not include targeted keyword.

Ranking Page PageRank ( p p ) Google PageRank of page ranking for a particular keyword shortcomings: slow updates.

Ranking Page InTitle ( p t ) occurrence of keyword in title of ranking page

Ranking Page InText, H1s, etc. ( p x ) occurrence of keyword in various HTML tags of ranking page

Formula Construction The Domain Variables (thanks, Google)‏ Ranking Domain Links ( r l ) total number of inbound links to the domain ranking for a particular keyword shortcomings: many of these links may not include targeted keyword. Ranking Domain PageRank ( r p ) Google PageRank of domain ranking for a particular keyword shortcomings: slow updates. Ranking Domain Age ( r a ) age of domain ranking for a particular keyword The Domain Variables

Ranking Domain Links ( r l ) total number of inbound links to the domain ranking for a particular keyword shortcomings: many of these links may not include targeted keyword.

Ranking Domain PageRank ( r p ) Google PageRank of domain ranking for a particular keyword shortcomings: slow updates.

Ranking Domain Age ( r a ) age of domain ranking for a particular keyword

Formula Construction Misleading variables Bid Values average bids for a particular keyword in a paid-search listing shortcomings: does not indicate interest in competing via organic listings, does not indicate an obstacle for ranking organically, data is greatly skewed by paid-search policies (makes pharma look very uncompetitive), data is greatly skewed by price of item for sale. Traffic Estimates estimated traffic for a particular domain or page shortcomings: does not indicate interest in competing via organic listings, does not indicate an obstacle for ranking organically, data is skewed by type-in-traffic, paid-search campaigns, viral nature of site, etc. Common Misleading Variables

Bid Values average bids for a particular keyword in a paid-search listing shortcomings: does not indicate interest in competing via organic listings, does not indicate an obstacle for ranking organically, data is greatly skewed by paid-search policies (makes pharma look very uncompetitive), data is greatly skewed by price of item for sale.

Traffic Estimates estimated traffic for a particular domain or page shortcomings: does not indicate interest in competing via organic listings, does not indicate an obstacle for ranking organically, data is skewed by type-in-traffic, paid-search campaigns, viral nature of site, etc.

Formula Construction Multipliers and Mathematic Fixes What Matters the Most here is where, as an experienced SEO, you get to work your magic. You get to make your own algorithm. Annotated with the m # notation where # is the variable to which the multiplier applies Can be a positive constant, integer or fraction Can be an equation itself You can create an incidental occurrence rate by comparing two values, such as the intext and intitle measurements. Create an index of this to determine the incidental->intentional ratio of a word’s occurrence and then use that to tweak values with weaknesses due to incidental occurrence. Mathematical Fixes use math to devalue less important, less meaningful variables and to emphasize those variables that mean the most. For example, I always show great emphasis towards the allinanchor: aggregate data, and the inbound link numbers to both the domain and the ranking page. Links represent are a legitimate barrier to ranking. Multipliers and Mathematical Fixes

What Matters the Most here is where, as an experienced SEO, you get to work your magic. You get to make your own algorithm.

Annotated with the m # notation where # is the variable to which the multiplier applies

Can be a positive constant, integer or fraction

Can be an equation itself

You can create an incidental occurrence rate by comparing two values, such as the intext and intitle measurements. Create an index of this to determine the incidental->intentional ratio of a word’s occurrence and then use that to tweak values with weaknesses due to incidental occurrence.

Mathematical Fixes use math to devalue less important, less meaningful variables and to emphasize those variables that mean the most. For example, I always show great emphasis towards the allinanchor: aggregate data, and the inbound link numbers to both the domain and the ranking page. Links represent are a legitimate barrier to ranking.

Formula Creation Putting it all together. Using API and Scrapers to Gather All Data Look at Results in Context Comparing a keyword to other keywords is essential. It can also be valuable to look at keywords that are searched a similar number of times. The higher the V 0 score, the better the keyword. Understand and Attack Start by targeting keywords that have very few backlinks to the ranking pages. Rankings can often be secured for these keywords by simply creating well-optimized content. Putting it all together.

Using API and Scrapers to Gather All Data

Look at Results in Context Comparing a keyword to other keywords is essential. It can also be valuable to look at keywords that are searched a similar number of times. The higher the V 0 score, the better the keyword.

Understand and Attack Start by targeting keywords that have very few backlinks to the ranking pages. Rankings can often be secured for these keywords by simply creating well-optimized content.

Virante, Inc http://www.virante.com Commercial Implementation http://www.keyata.com

Virante, Inc http://www.virante.com

Commercial Implementation http://www.keyata.com

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