Keyword Research

I created these Keyword Research steps to help my team best address and strategist online marketing goals for our clients:

Initial steps include gathering notes from sales touches and initial marketing meeting notes. These are extremely important research tools! Always be on the lookout for keyword targets in these materials. These notes, combined with any existing website info, form the initial ingredients of any project.

Initial data sources for keyword research:

• online marketing services/package type
• sales notes
• marketing meeting notes
• client questionnaire answers
• existing website info/analytics
• competitor info / link analysis
• keyword clusters documents

I’ve ranked keyword phrases/themes into three SEO tiers, (basically High, Mid, Low) and we offer clients packages/services created to address these competition levels. In these ways, package levels and package framework can relate directly to our recommended keywords lists.

With this research information in-hand, the online marketer will compose the initial keywords draft. These terms should logically support the general layout of the project and the targeted tiers, with the requirement to create an initial bucket list with extra recommendations to be whittled down. In this way, we have a good list of variables to include in our research, and also present to the client as future, or undesirable terms.

Now to compare/contrast and pick our list, it’s time to run this keywords list through the Algorithm Spreadsheet I’ve created.

Once the data entry is complete, sort by keyword score and remove the least-desirable of the list. As a general rule, removing highest and lowest scores first, and then picking the best from the remaining options is effective.

The SEO Quake plug-in for Firefox/Chrome proved valuable in scraping Page Rank and Domain Age information from Page One search results.




Here is the Algorithmic formula:

factor: Keyword SEO and ALLINANCHOR and ALLINTITLE: equal 10% weight and 20% of Algorithm
ALLINANCHOR and ALLINTITLE will be scored as:
over 1000 = high = 10
under 1000 = low = 2
factor: Ave Domain Age of top ten sites: equals 20% of Algorithm
6+ years = 100% = 20
2-6 years = 60% = 15
0-2 years = 40% = 5
factor: Page saturation of kw phrase: equals 30% of Algorithm
500,000+ = 100% = 30
100,000-500,000 = 60% = 15
under 100,000 = 40% = 5
factor: Ave PR of top ten sites: equals 30% of Algorithm
pagerank of 3+ is top of the foodchain, ex: NY RE = 30
pagerank of 1-3 is competitive – El Segundo RE = 15
pagerank of 0-1 is not heavily competitive – Silver Mountain Real Estate = 5

Regarding Tiers, In General:

Tier 1 terms – Top Level Metro markets,”general” industry terms – ALGORITHM SCORE RANGE: 100-70
Tier 2 terms – Local neighborhood “general” industry terms – ALGORITHM SCORE RANGE: Generally 40-70 range
Tier 3 terms – specific industry niche areas or categories – ALGORITHM SCORE RANGE: 40-0

Tier 3 terms are usually the most longtail terms in the keyword list
Tier 2 terms should be supported by the longtail terms in the keyword list, creating “pods” of similar content
Tier 1 terms are supported by mid and longtail terms, possibly with doubled-up content pages anchoring the top phrases