Your SlideShare is downloading. ×
TANM Research and Marketing Conference 2013, Albuquerque, NM
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

TANM Research and Marketing Conference 2013, Albuquerque, NM

356
views

Published on

Using Big Data to understand the Tourism Consumer. Delivered conclusions from Research on Social Media, Search Volume, Brand and what the consumer is looking for in Content.

Using Big Data to understand the Tourism Consumer. Delivered conclusions from Research on Social Media, Search Volume, Brand and what the consumer is looking for in Content.

Published in: Travel, Technology, Business

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
356
On Slideshare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
9
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • not even close
  • not even close
  • not even close
  • knowing what they’re doing, not what they’re telling us
  • Dimensions: HHI, interests, demo, psycho
  • takes years, you’re already behind∂
  • happens to everyone
  • not even close
  • Demographics are used because they suggest Behavior. Until marketing changes Behavior, it’s wasted. We look for the closest thing to Behaviors
  • knowing what they’re doing, not what they’re telling us
  • it’s a behavior, signal
  • AZ better on coasts, NM in Texas and drive market
  • the STO and DMOs grouped, NM holds drive market to the east, not West
  • volume in drive markets
  • off season versus summer, timing very different
  • of the people who went to STO, then DMO, matches, they converted later on DMO Brand by Keyword. Unattributed branding at STO
  • the biggest impact isn’t from increasing budget, it’s increasing signal rate
  • brand, and higher per capita in drive market
  • farther is more planning, drive wants To Do and Attractions
  • most frequent is organic and direct. and most organic is brand
  • it’s a behavior, signal
  • Social Media is neither first nor last
  • it’s a behavior, signal
  • frenzy goes to conversion
  • lots of new, mostly locals
  • FL coming in off season, drive markets are Dec/Jan or Jun/Jul, Extended/West is May but more evenly distributed
  • How many days out are they planning by RFV, content planning
  • content to market, events are drive
  • not even close
  • takes years, you’re already behind∂
  • Transcript

    • 1. Using Big Data to Understand the Consumer TANM Research & Marketing Conference Insights For Success October, 2013 Albuquerque, NM R. A. Burrell Using Big Data, Analytics and other Data to understand your Chief Analyst at Internet Honey Audience; what they're doing, what they want and how to use it.
    • 2. Sources & Uses Real results are presented from several States, DMOs, Reservations and Attractions. Your results may vary significantly. The intention is for demonstrative purposes only. Conversions and Signals are a combination of Reservations, Visitor Guide Requests or other Signals of Intent To Travel.
    • 3. We Will: •Define Big Data •Learn How to harness it •Turn Big Data into knowledge
    • 4. Big Data is: •A bunch of data so massive and complex it’s entirely useless •It requires special technology and techniques because it breaks conventional stuff
    • 5. Who Cares?
    • 6. Who Cares? The most successful marketers: 1.Harness data & optimize 2.Have content marketing
    • 7. Data Structure Visualize >>> Measures Measures Aggregates Aggregates Summaries Summaries Facts Facts Big Data = massive Big Data = massive quantities quantities of small data of small data
    • 8. Data Sources
    • 9. Where are the Facts? Silos: Good for Grain, Not Data
    • 10. Data Map Sources Signals of Intent to Travel Reservations, Occupancy Rates, Lodging Tax Keywords Social Media Email Ad Impressions Web Traffic Call Center Welcome Center
    • 11. How Do We Harness It?
    • 12. Best Practice*
    • 13. Data Quality
    • 14. Turn Big Data into knowledge •Competitive Research •Optimize Engagement •Measure Social
    • 15. Competitive Research
    • 16. Competition Are We Winning? Where? Who? How?
    • 17. Search Volume by Market Share of Voice How many people are searching for us in a Target Market?
    • 18. US Population
    • 19. Search Volume: NM, AZ, CO Using Big Data, Analytics and other Data to understand your Audience
    • 20. Search Volume: NM, AZ, CO Indexed Using Big Data, Analytics and other Data to understand your Audience
    • 21. Search Volume: NM, AZ Using Big Data, Analytics and other Data to understand your Audience
    • 22. Search Volume: NM, AZ, CO DMOs Indexed Using Big Data, Analytics and other Data to understand your Audience
    • 23. Search Volume: NM, AZ DMO Using Big Data, Analytics and other Data to understand your Audience
    • 24. Top NM Keywords Using Big Data, Analytics and other Data to understand your Audience
    • 25. Competition Frienemies
    • 26. Other Value •What’s coming downstream •How effective are you at state level •Market Share/Share of Voice •How much goes from STO Brand to Industry Partners Unattributed
    • 27. Timing DMO A DMO B
    • 28. Brands DMO STO
    • 29. Other Value •What’s coming downstream •How effective are you at state level •Market Share/Share of Voice
    • 30. Optimize Engagement
    • 31. Keywords Are We Engaging?
    • 32. Keyword Category by Market Using Big Data, Analytics and other Data to understand your Audience
    • 33. Keyword Category by Market: Non-Brand Using Big Data, Analytics and other Data to understand your Audience
    • 34. Signal Rate by Keyword Category Attraction Brand Hotels Trip Planning To Do
    • 35. Signal Rate by Keyword Category Attraction Brand Hotels Trip Planning To Do Using Big Data, Analytics and other Data to understand your Audience
    • 36. Signal Rate by Keyword Category Attraction Brand Hotels Trip Planning To Do Using Big Data, Analytics and other Data to understand your Audience
    • 37. Keyword Category Tells us how well we engage them on what they were thinking Not Engaging on To Do
    • 38. Channels Using Big Data, Analytics and other Data to understand your Audience
    • 39. Channels Using Big Data, Analytics and other Data to understand your Audience
    • 40. Channels Using Big Data, Analytics and other Data to understand your Audience
    • 41. Channels Using Big Data, Analytics and other Data to understand your Audience
    • 42. Social Media’s Contribution What does Social Media contribute to Conversion?
    • 43. Path To Conversion/Signal Using Big Data, Analytics and other Data to understand your Audience
    • 44. Path To Conversion/Signal Using Big Data, Analytics and other Data to understand your Audience
    • 45. Search Volume by Market Share of Voice Correlation of Branded Search Volume and Social Media
    • 46. NM Volume, Top Markets Using Big Data, Analytics and other Data to understand your Audience
    • 47. AZ Volume, Top Markets Using Big Data, Analytics and other Data to understand your Audience
    • 48. Engagement Drive Market
    • 49. Timing Using Big Data, Analytics and other Data to understand your Audience
    • 50. Timing and RFV (Reason For Visit) Using Big Data, Analytics and other Data to understand your Audience
    • 51. RFV In December Using Big Data, Analytics and other Data to understand your Audience
    • 52. Engagement Drive Market coming to visit Friends and Relatives in Dec/Jan They need what to do
    • 53. Engagement Drive Market coming to visit Friends and Relatives in Dec/Jan Locals need what to do with them
    • 54. Social vs. Marketing Geography Leads Likes
    • 55. Social vs. Marketing Geography Leads Likes
    • 56. Engagement Perhaps Email/Web for Leads Social for Locals
    • 57. We Did: •Define Big Data •Learn How to harness it •Turn Big Data into knowledge
    • 58. Thank You www.slideshare.net/ richardaburrell

    ×