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SEO in 2017: It’s The Same (But
It’s Not)
How Do Search Engines Work?
Search engines generally have 3 main jobs:
How Do People Work?
Image: Moz
• They become inspired
• They revisit their past
• They research their options
• They identify brands with the solutions
• They second-guess themselves
• They make the deal, or abandon it altogether
The Ugly Truth About
Organic Search in 2017
PR & Social Media Backlash Done Right
Using Data & SEO to Control the Narrative
SEO in 2017: It's The Same (But It's Not)
PR & Social Media Backlash
When Done Poorly…
SEO in 2017: It's The Same (But It's Not)
LOL
Google SERP,
2006
“Would You Like to Rank #1 Here in
Organic Search?”
“Kidding. It’s down here below the Local Map Pack.”
These Paid Ads Answer The Question
Position #0 (#7 below fold)
Moz, Local Search Ranking Factors
2017
On-Page Signals
• Content: Unique, Useful, Never Duplicated, Never
Lazy
• Location: Prove That You’re a Local Brand!
• Proximity: Multiple Offices? Are They On The Map?
• Do They Have Their Own Pages?
• Do They Have Their Own NAPU & Citations?
• Does it Answer The Question?
• Does it Keep People On Your Site?
• Does it Speak to Your People?
Image: DealerOn
Moz, Local Search Ranking Factors
2017
Traditional Off-Page Signals
• Links: Who Do You Partner With?
• Link Location: Prove That You’re a Local Brand
(Again)!
• Citations: Send People (and Google) The CORRECT
Info!
• Can You Prove You’ve Been There?
• Can You Get Reviews From Your People?
• Does it Speak to Your Work?
• Is it a Testament to Your Brand and PR?
• Does it Speak to Your People?
Image: DealerOn, Greg Gifford
The #1 Local Ranking Factor in 2017
Proximity
Automating SEO with Big Data
Sales Forecasting Using R + Marketing
WHAT WE’RE LEARNING:
1. Rankings Do Not Guarantee Success
2. Search > Industries > Single Query
3. Results Driven By Relevance + Intent
4. Technical Factors Remain Necessary
5. Cultivate Your Career Daily. Demand It!
6. User Signals CONTINUE to be Marginalized by Us All
WHAT WE KNOW:
1. It’s Still All About People – Our People
2. It’s Still All About Reputation
3. It’s Still All About The World Around Us
4. It’s Still All About Conversions, Leads, Revenue
5. SEO Boundaries Are Blurred in 2017
6. Tech and Marketing Need Each Other More Than Ever
What Do We Believe?
Be Local, Be
Global• Treat Locations Like
Locals
• Uniform NAPU
• Know Your Partners
• Know Your People
Be Fast, Be First, Be
Secure• HTTPS and HTTP/2
• Produce Content ASAP
• Be Like Water
Be Disruption-
Proof• Funnels over Channels
• Integration across Digital &
Traditional
• Continued Education and
Growth is no longer optional
for us.
• Find Your Niche and Dream
Big
Rankings !=
Revenue• Leads, Conversions,
Revenue pay the bills
• Rankings are not rankings
anymore
SEO in 2017: It's The Same (But It's Not)

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SEO in 2017: It's The Same (But It's Not)

  • 1. SEO in 2017: It’s The Same (But It’s Not)
  • 2. How Do Search Engines Work? Search engines generally have 3 main jobs:
  • 3. How Do People Work? Image: Moz • They become inspired • They revisit their past • They research their options • They identify brands with the solutions • They second-guess themselves • They make the deal, or abandon it altogether
  • 4. The Ugly Truth About Organic Search in 2017
  • 5. PR & Social Media Backlash Done Right Using Data & SEO to Control the Narrative
  • 7. PR & Social Media Backlash When Done Poorly…
  • 10. “Would You Like to Rank #1 Here in Organic Search?” “Kidding. It’s down here below the Local Map Pack.”
  • 11. These Paid Ads Answer The Question Position #0 (#7 below fold)
  • 12. Moz, Local Search Ranking Factors 2017 On-Page Signals • Content: Unique, Useful, Never Duplicated, Never Lazy • Location: Prove That You’re a Local Brand! • Proximity: Multiple Offices? Are They On The Map? • Do They Have Their Own Pages? • Do They Have Their Own NAPU & Citations? • Does it Answer The Question? • Does it Keep People On Your Site? • Does it Speak to Your People? Image: DealerOn
  • 13. Moz, Local Search Ranking Factors 2017 Traditional Off-Page Signals • Links: Who Do You Partner With? • Link Location: Prove That You’re a Local Brand (Again)! • Citations: Send People (and Google) The CORRECT Info! • Can You Prove You’ve Been There? • Can You Get Reviews From Your People? • Does it Speak to Your Work? • Is it a Testament to Your Brand and PR? • Does it Speak to Your People? Image: DealerOn, Greg Gifford
  • 14. The #1 Local Ranking Factor in 2017 Proximity
  • 16. Sales Forecasting Using R + Marketing
  • 17. WHAT WE’RE LEARNING: 1. Rankings Do Not Guarantee Success 2. Search > Industries > Single Query 3. Results Driven By Relevance + Intent 4. Technical Factors Remain Necessary 5. Cultivate Your Career Daily. Demand It! 6. User Signals CONTINUE to be Marginalized by Us All
  • 18. WHAT WE KNOW: 1. It’s Still All About People – Our People 2. It’s Still All About Reputation 3. It’s Still All About The World Around Us 4. It’s Still All About Conversions, Leads, Revenue 5. SEO Boundaries Are Blurred in 2017 6. Tech and Marketing Need Each Other More Than Ever
  • 19. What Do We Believe? Be Local, Be Global• Treat Locations Like Locals • Uniform NAPU • Know Your Partners • Know Your People Be Fast, Be First, Be Secure• HTTPS and HTTP/2 • Produce Content ASAP • Be Like Water Be Disruption- Proof• Funnels over Channels • Integration across Digital & Traditional • Continued Education and Growth is no longer optional for us. • Find Your Niche and Dream Big Rankings != Revenue• Leads, Conversions, Revenue pay the bills • Rankings are not rankings anymore

Editor's Notes

  • #4: The funnels do not care about your channels.  PEOPLE do not care about whether or not they find inspiration organically or on Instagram. But when you think about how SEO and Social (among the others) both complement the consumer journey, you begin to cater to all facets of the voyage.
  • #5: SEO alone is weak. It requires collaboration with every marketing channel, and the more access, the better. Rankings mean little compared to previous years. Treat it like a bellwether, a canary. Disruption is real. If you’re not keeping up with your personal development, you’re in for serious pain.
  • #6: When SEO + social media/PR/content marketing/analytics strategy, we can identify issues quickly and strike. Left: clicks vs impressions during the legal storm, during the actual event, and long after the event had passed. Right: data provided by Majestic - monitor linked mentions. By reaching out to the news providers across the US and in Houston, we were able to turn the bad press into wins for all.
  • #7: On September 24th, local pizza truck-turned-brick and mortar shop Pi Pizza made news. Patron voiced their displeasure with the restaurant’s policy against open carry of firearms on the grounds of alcohol being served. While the initial review was deleted, it kept on. News sites both state-wide and nationally linked to their Facebook and social media assets extensively. Bloggers have taken to writing op-eds both in support and denouncing their business practices, and across social media, pleas from friends and patrons for positive reviews have largely been relegated towards the Facebook and Yelp platforms. What about their website, which along with Google Reviews drives in desktop and mobile searchers looking for localized pizza options?
  • #8: Their battle was waged on social media with zero link acquisition going towards their business. Great for social, but no benefit to the site.
  • #10: SERPs have changed. I still recall the cringe-worthy things I once said about how “Nobody ever clicks paid ads”.
  • #11: Now it’s a blurred line between paid and organic search listings.
  • #12: And with Rich Snippets/Position #0, it’s even more unclear. Behold this horrendous snippet.
  • #16: By automating reporting using basic data science tools such as R and Rstudio, we can not only operate independently of designated Analytics specialists, we can store Google Search Console data indefinitely and keep a repository for our clients.
  • #17: This is my next big want – to be able to set content marketing and social/PR/SEO timelines better. Question: How can we develop prediction model on GA dataset and what are the summary statistics of the model? We should be able to see how data analysts can get transaction related dataset from source (Google Analytics) for predictive analysis of product revenue. http://www.tatvic.com/blog/product-revenue-prediction-with-r/