Hey, hey, kids. I hope you enjoyed your lunch because now its back to the sessions. Two more and we’re out of here. For now, it’s time to talk advanced keyword research.
First up is Bryson.
Keyword Research 1.0: Search volume was the only consideration. High volume keywords not necessarily qualified. Content that doesn’t connect to audience less likely to convert.
Beyond Search Volume: Query Intent
- Navigational Queries: Someone who knows what they’re looking for. People are looking for a specific site. It’s about branding, awareness. Someone looking for shoes.com or Zappos.
- Transaction Queries: Interactive. Suited for direct response or engagement. [buy shoes] or [nike commercial]
- Informational Queries: Educational queries. Awareness.
Beyond Search Volume: Demographic Qualification
You need to think about who your users actually are. Match demographics of site with keywords and you’ll increase conversions.
Beyond the Web: Mobile
Desktop search is different from mobile search. Not only are the queries different, but different modes of mobile queries are different. SMS search is different from mobile Web search or voice search. It’s based on the input. Optimize your mobile site based on the type of query.
Beyond the Web: Video
YouTube is the second largest search engine. In YouTube, people are looking for certain types of material [stuff that would make their mother’s blush]. You can look at the YouTube Suggest keyword tool to find out what the popular search queries are. You can also use YouTube Promote. It allows you to cut and paste keywords to put into an Excel sheet.
Yesterday, Google released a YouTube Keyword Suggestion Tool. [I tried to grab a link to that but couldn’t find it. Can anyone help me?]
Christine is next.
Keyword research is an iterative process.
Keyword lists from within company
- Review company Web site and print collateral
- Press releases
- Often too much insider jargon
- May or may be a customer’s lingo
Site Search Box
- Reveals keywords and expressions that visitors are actually using
- Gives insight into number of words searchers are using
- Can follow visitors path and see if site converts
- Useful source for long tail KW
- Make sure you collect site search data
Intel from Offline Conversions
- Phone and in-store conversions are an often overlooked resource
- Offline purchases often driven by online search.
Use keyword research tools to expand your options and refine your selections. HitWise’s Search Terms Gap Analysis is good for comparisons and brainstorming. Put a keyword in and find out who’s getting traffic from it.
Use tools to identify word trends. They give you insights you can’t get just looking at your analytics. Keyword use reflects what is on users mind.
The Long Tail Concept and Finding New Opportunities
It’s based on a frequency graph. The idea is that non-hits can make money based on sheer volume. As users get more sophisticated, they’re using more words in their queries. Most one word queries are navigational queries.
Long tail identification techniques: use keyword concatenation, SEOBook permutation tool, etc.
If you’re perusing the long tail, be realistic. You can’t go after them all. Find the long tail words that perform. Balance the effort with the return you’re going to get. Look for ways that allow you to scale. Use Broad or Phrase match in PPC with care. Market smarter.
Use tools to find your marketing. Define and conquer! Customize your landing pages as much as you can. Different visitors have different goals.
Evaluating KW Performance: Make sure the words you’re optimizing for are giving you the performance that you can tell if they’re actually working.
Next up is Marty.
You want to combine predictive output with site-specific datasets at the keyword level.
- Statistics culled from organic analytics (KW traffic, conversion, behavior criteria)
- PPC history (CPC, CTR, conversion, etc…)
- SEOmoz’s Linkscape (SEO competitiveness-predict)
Aggregated Datasets Theoretically Useful to “Advise” Keyword Selection Process
- Very few SEMs actually pull it off.
- Share process using spreadsheets to pilot advanced techniques, for API automation
What Is Keyword Research For Anyway?
Classic keyword research = Selecting Words for SEO, PPC and Offline clarity.
- Other Compelling Objectives Attainable by Analytic Mashups.
- Wire-Frame Attainable SEO Based on Page strength, Taking SERPs Competitiveness Into Account
- Mine SEO Clues for More efficient PPC
- Multitude of Seriously Useful applications.
- All About Increasing ROI in All Channels.
Not Your Mother’s Keyword Basket
- Leverage Mashed Datasets & Stacked Sorting Routines.
- Even within themselves, most Web based tools only provide a single dimension of data sorting.
- AdWords Keyword Tool Sorts By Single Attribute.
Creative Demographic Research Artists Rock Tools By .CSV Export
- Add additional Keyword-Level Metrics
- Execute Multiple Sort Routines
Example: Intersection of Low PPC Cost & Search Frequency
- Each Data Set Has “Attributes” (Columns)
- AdWords Keyword Basket Dataset Attributes
Export keyword Basket to an Excel .CSV
Sort Data to identify the intersection of low PPC cost & search frequency.
- Not Possible possible in the AdWords Web UI,
- 2 Step-Sort is Super Easy in Excel.
The Sort Reveals 269, 400 Annual SEO Keywords, estimated @ $.05 CPC.
Sorting Analytic Mashups! Combine Available Datasets to Same Spreadsheet
- Aggregate Keyword Basket Predict
- Organic Keyword Analytics History
- PPC datasets
- Competitiveness Metric
Cross Channel Data Sorting is Very Simple.
- Create New Columns Spreadsheet Colums
- Enter Each Keyword’s Data in Next To Keyword Basket’s Output.
Import/Collate Each Keyword’s Organic History
(Remember, this data is from your site’s Web analytics like Google Analytics, ClickTracks, Enquisite, etc…)
- Traffic Frequency
- Conversion Frequency
- Conversion Ratio
- Engagement (Time & Page Views)
Import/Collate Each Keyword’s PPC History (This data comes from your PPC Accounts)
- Click Through Count
- Click Through Ratio (CTR)
- Actual Cost Per Click (CPC)
- Conversion Count
- Conversion Ratio
- Cost Per Conversion
Import Average mR of Each Keyword’s Top 3 Organic SERPs
- mR = “MozRank,” LinkScape’s PageRank Metric.
- Contribution to Measure Page Value & Organic Competitiveness
- Turn Off Personalized Search As Best Able
- Query Each Keyword, Average Top 3 Results mR
- Type In Spreadsheet By each keyword,
- Viable Estimate of SERPs Competitiveness Keyword.
Ready to fly?
- Now that you have the the predictive, organic & PPC historical data for each keyword on one spreadsheet, there’s awesome collating power at your data-sorting fingertips. Here is a partial list of “sorts” to cross-advise organic and PPC marketing efforts
High Organic Traffic / Low Organic Conversion
Identify Where Organic Traffic Intersects w/ Low Conversion.
Higher Predict Frequency / Lower Organic Competitiveness
Intersection of AdWords Search Volume Predict, Attainable SERPs for the Keyword.
Lower Predicted PPC Cost Per Click / High Organic Conversion Ratio
Find cost keywords, Proven to Convert Organically. Classic Mashup Report.
High PPC Conversion Frequency / High Organic Traffic / Low Organic Conversion
- Triple sort Identifies Organic Conversion Deficiencies
- Proven PPC Converston, Week Organic Conversions
- Good Organic Volume
- Targeted For Improvement Where There’s Already Good Organic Traffic
Other Fun Keyword Attributes For Research Mashups
- Any number Of Other (provocative) Attributes Which Comprise Organic & PPC Historical
- Mash into our aggregated-sort approach for spectacular clarity.
- Behavioral Triggers & Funnels
- Users’ Proclivity To Socialize Content
- Geographic Data
- Page Strength (Page on Which The SEO Is Placed)
How to Actually Use This Information
- Pioneering Algorithms Using Spreadsheets is Easy
- Enterprise Execution is Another Story
- Sort With Hand-Blended Exports
- Bring the processes to Dev Tewam Automation
- Various APIs Comprise Keyword Predict Baskets, Organic & PPC
Not Every Dataset Available For Every Website.
- Use what’s available
- Make Keyword Research Even More Valuable.
- Predictive Keyword Basket Tools Only Part of the show.
- Mash in keyword-level metrics + Multi-Level sorting
- Using Both What is Predictable & Known.