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    ZACK NOTES - SEO TOOLS - SMX EAST - NYC - 2013 - ZACK NOTES - SEO TOOLS - SMX EAST - NYC - 2013 - Presentation Transcript

    • Zack Notes Senior Analyst at UncommonGoods @zacknotes
    • UncommonGoods Independent B Corp out of Sunset Park in Brooklyn NY
    • UncommonGoods
    • SEO Tools (and more importantly, application)
    • If Google made a big algorithm change tomorrow, what would you do?
    • What if you saw some of your keywords dropping?
    • How would you see the big picture?
    • I use the Moz full ranking report to get the big picture on keyword movement
    • • You have to finesse this data a bit
    • Delete all columns except these
    • Select all 3 columns and run a pivot table
    • Drag and drop fields per chart above. Change Google from count to sum via value field settings
    • Highlight everything, copy and paste values only to a new sheet
    • What happened to my dates ?
    • Reformat the dates as short date
    • Ctrl-H to Find & Replace all zeros with 50 * zeros indicate this kw is not in top 50 * blank spaces indicate you were not tracking that kw yet
    • • Delete the grand total at the bottom row and far right column • Create a bottom row with the average of rankings for all keywords above
    • Chart date row vs average row
    • NS Traffic is a vanity metric. It tells us next to nothing.
    • How do you keep track of links you’ve acquired?
    • BuzzStream is a CMS for link builders
    • You can filter by tags, linking status, date added etc.. Contact Lists
    • Contact Details Dig deeper to get • Link details – acquisition method, anchor text, date found, etc.. • Contact details – name, email address, social accounts, etc.. • SEO stats – page Rank, moz domain authority, inbound link counts • Communication log – stores emails
    • You give Buzzstream Google search terms and they import domain, stats, contact info into a temp contact list Prospecting Automation
    • Are you missing keywords you should be ranking for?
    • We have over 2,500 products…
    • Our Navigation attempts to list all categories, but there is limited space.
    • We realized that we had collections of products that our Navigation was missing.
    • We realized that we had collections of products that our Navigation was missing
    • Without a landing page, we were missing out on search traffic
    • So we automated a system for creating landing pages
    • Our tech dept automated creation of these through an admin interface. They are indexed via the XML sitemap
    • We turned this search results page…
    • Into a static landing page
    • And now we have a ranking page
    • Isn’t this a presentation about SEO tools?
    • Here is the tool we used to discover more opportunities like this..
    • Note the phrase controls
    • I used SQL to export a list of all of our title tags, and then fed them into ToCloud
    • ToCloud allowed us to mine our title tags for search terms.
    • • We have created 250 of these pages. • 70 have converted • Revenue lift = 6% Results
    • How do you know when to schedule your link building (and other marketing) efforts ?
    • Sometimes it’s obvious…
    • Sometimes it’s not.
    • Some terms have fairly clear peaks
    • Others have more distributed curves
    • And others are just plain confusing
    • To analyze this, export the data
    • You get weekly, normalized data (unlike keyword tool)
    • Create a column to count off weeks and a column for each year you wish to include
    • Pasted yearly data from column 2 into the year columns
    • Create a column to average the yearly data
    • Apply conditional formatting
    • You can see that there is a traffic peak in August
    • Create a new column and re-normalize to 5
    • Copy and transpose the values with paste special
    • Now you have a calendar showing traffic peaks for “Home Décor”
    • Add all of your keywords and you get a great calendar tool to visualize your Keyword traffic • Since it’s normalized, you can’t compare rows (5 in one row is not necessarily representative of more traffic than 4 in a another row). • It’s basically aggregates and stores a crapload of Google Trends data in one chart and makes planning easier. • These values are different (1-5) because this is from a slightly more advanced calendar I built using Python ( Moz blog post below)
    • Zack Notes Senior Analyst at UncommonGoods @zacknotes