Using location data for local content creation

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Quick tips on using the Location reporting in Google Analytics for prioritizing areas for local content creation.

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Using location data for local content creation

  1. 1. Using Location Datato Inform Local Content Creation Ian Howells @ianhowells
  2. 2. Why Create Local Content?Local – not just for maps anymore. halo18.com
  3. 3. Perfect For…Doctors Car DealersDentists Lawn ServicesLawyers Snow RemovalLasik Surgeons PlumbersChiropractors Roof RepairRestaurants Etc… halo18.com
  4. 4. Venice and the continuedpush to local brings hugeopportunity for local leadgen, as well as offeringlocal SEO services.However…
  5. 5. There are over 10,000 cities in the US
  6. 6. We Need Priorities halo18.com
  7. 7. But First… Advanced Segments halo18.com
  8. 8. And a Quick Filter…Now we have just Google organictraffic with >50 visits in one week. halo18.com
  9. 9. And We’ve Got Cities halo18.com
  10. 10. Option 1Defensive play to maintain our top converter Great, localized content (specific to the niche) Photos from the city (stock or original) Include “San Jose” in the main call to action halo18.com
  11. 11. Option 2Go on offense - Improve the low converter Great, localized content (specific to the niche) Photos from the city (stock or original) Include “Sunnyvale” in the main call to action Consider a local value prop/selling point halo18.com
  12. 12. OpportunityIn this case… Converting at site average means 12 more leads week That’s an incremental 624 leads per year Or, $6,240 in revenue on traffic that already exists Just from Sunnyvale, CA halo18.com
  13. 13. Extra OpportunityYou can also use this info for…Geo-targeted Paid Search campaignsEgo-bait aimed at Google+ sharing Add keyword – exactly matching – (not provided) Sort cities with the most signed in visitors Create content pieces around those cities Strong CTA to share on Google+ halo18.com
  14. 14. If you’ve already gottraffic, odds are you’resitting on local gold mines.You just need to find them.
  15. 15. Happy Data Mining
  16. 16. Ian Howells@ianhowellshalo18.com

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