Keywords Hiding in Plain Sight


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Learn how to get the most from your historical keyword data. We’ll answer questions like: “Which long tail keywords have the best conversion potential?” and “Which keywords need their own landing page?”

Experience level: Intermediate
Target audience: Affiliates/Publishers
Niche/vertical: Keywords

Jeremy Bencken, Founder, Wordloop (Twitter @Bencken)

Published in: Business, Technology, Design
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  • This is how a lot of people do keyword research today…
  • This is what we need to be doing…
  • His question to me was, “which keywords should I emphasize for SEO?” I’m going to show you two ways to summarize ultra long tail keyword data. #1 ngram analysis. #2 Bayesian filtering
  • Just because “what is” had 3% conversion, does it mean /any/ keyword search with “what is” will convert as well? There’s an infinite set of “what is” queries, and we’re only looking at a small chunk of them.
  • Should really target keywords with “what are” over “what is” given that “what are” has 2x higher conversion but 1/3 of the traffic?An observation could be the result of random noise. Eg. Kw1 has 1000 entrances and conversion of 10%, kw2 has 10 entrances and conversion of 50%. Which is better?Chicken & egg: You have sparse data about keywords you don’t rank well for… so how are you supposed to know you SHOULD target them???
  • Training file will include 1 line for every unique keyword. For this site, in six months, that was 131k keywords.
  • Now you can run lots of keywords against the model. Google provides an API, you’ll need to write program– PHP, Ruby, Python, whatever you want. Now, go get keyword suggestions from Adwords/Wordstream/Wordtracker and screen them for conversion potential.Use these keywords as seeds to generate related keyword ideas.Find keywords you are not #1 for, and focus your on-page SEO efforts on them.Identify content that convertsProduct names vs. product categoriesTopic areas
  • Keywords Hiding in Plain Sight

    1. 1. Keywords Hiding in Plain Sight Using Ngram Analysis and Bayesian Filtering to Find High Conversion Keywords
    2. 2. Would you rather be this guy… @bencken
    3. 3. …or this guy? @bencken
    4. 4. My BackgroundPerformance-Based Content Marketing for B2B Link Building Tools to Help You Scale @bencken
    5. 5. A Friend’s Video Content Site… • 26,700 distinct kws per month • 90% 1-entrance kws • 3% of kws converted • 61% of conversions from kws under 10 entrances @bencken
    6. 6. Organic Entrances vs. Keywords @bencken
    7. 7. Which keywords drive conversion? @bencken
    8. 8. Approach #1N-GRAM ANALYSIS
    9. 9. Ngram Analysis B D dvd ripping software for mac A C ID 2-word ngram (bigram) A dvd ripping B ripping software C software for D for mac @bencken
    10. 10. @bencken
    11. 11. n-gram Analysis Pros/Cons• Pros – Find major phrases that drove traffic and conversions – Indicator of what phrases Google is ranking you for• Cons – Hard to compare keyword conversion with varying volumes – Ignores long tail data – Chick and egg problem @bencken
    12. 12. Approach #2BAYESIAN FILTERING
    13. 13. Bayesian Filtering• Same technology that detects spam• Based on probability that words are associated with conversions• Finds the phrases and sub- parts associated with conversions @bencken
    14. 14. Google Bestows Upon Us “Prediction”…• You need… – Conversion data at kw level – Excellent Analytics – Google Cloud Storage – Google Prediction• Steps – Download your keyword data from GA • Beware of sampling, English only, Same medium, More is better – Organize keyword data into 2 columns: number,”keyword” • Number: 1 = converted, 0 = no conversion – Upload to Google Cloud Storage – Train a new Predict model prediction/docs/hello_world @bencken
    15. 15. Example Training Data0,"best dvd ripping software"0,"dvd ripping software"0,"book"0,"sell videos online"0,"best free dvd ripper"0,"turkey"0,"master cleanse blog"0,"a book"0,"dvd ripping software for mac"0,"learn economics market structure online"0,"sell videos"0,"tropic thunder"1,"chemistry: videos of fission and fusion"0,"dvd ripping software mac"0,"selling videos"0,"prono videos"0,"special days in december"0,"selling videos online"0,"list of december holidays"0,"grim reaper" @bencken
    16. 16. @bencken
    17. 17. Let’s Ask a Question… Question: Would calculus or algebra search traffic perform better? algebracalculus Answer: calculus searches convert better! @bencken
    18. 18. Prediction At Scale… So what? Prediction Value * Google AW Search Volume = Potential 1) Screen all your top keywords and ngrams via the model. 2) Screen all those single-visit keywords for opportunities. 3) Screen suggestions from 3rd party tools. Filter performance: 97.6% accurate, 2.2% false positive, .2% false negative @bencken
    19. 19. @bencken
    20. 20. Keyword Tools • Adchemy • MergeWords • Adgooroo • Market Samauri • Adwords Keyword • NicheBot Tool • Searchmetrics • ConcentrateMe • SEMRush • Ispionage • SEOBook • KeyCompete • Spyfu • Keyword Discovery • Ubersuggest (Trellian) • Wordstream • Keyword Elite 2.0 • Wordtracker • Keyword Spy • Wordze @bencken
    21. 21. Thanks!Jeremy BenckenFounder, @bencken