5. • We have accepted this Blue
Link reality
• With 10 Possibilities, Errors
are Expected
• But, honestly, this is sad…
• We have tortured the
unstructured data to game
the Algo and produce blue
links
How We Got Here
6. • Structured Data leads the
way to answers
• Machine Learning and
Artificial Intelligence leverage
this
• The Interface finally begins to
return Answers, not blue
links, breaking the whole
interface paradigm
Where Are We Going?
25. Data Ecosystem & Signal to Noise Processing
Data flows as input and output between most location services
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48. • Bad data is a killer to AI and
machine learning
• The systems begin to “learn
wrong” and can’t easily “un-
learn” data
• The once “allowable” bad
result out of ten now
completely cripples the new
Interface
Now What if The Data Is Wrong
49. Single Sources of Truth
“Alexa, What’s the first rule of
Fight Club?”
Only a Single Source Can be Used for This, with Verification.
Classic Algos Struggle with This.
50. Am I Exaggerating?
Anyone Remember Long Term Capital Management?
• “using quantitative models to exploit deviations from
fair value…”
• “finance veterans, PhDs, professors, and two Nobel Prize
winners…”
• “LTCM triggered more than $1 Trillion in default risks
and lost $4.4B in one year
• One of the single biggest causes of the global, financial
meltdown
51. 76%
visit a business within one day
Total Location Search users
28%
of these searches
result in a purchase
T h i n k W i t h G o o g l e , 2 0 1 6
60. Headlines: Mobile First Indexing
“To make our results more useful, we’ve begun experiments to
make our index mobile-first. Although our search index will
continue to be a single index of websites and apps, our
algorithms will eventually primarily use the mobile version of a
site’s content to rank pages from that site, to understand
structured data, and to show snippets from those pages in our
results…”
61. What Are We Searching For?
• Every year, we debate the death of SEO
• AI, Machine Learning, Personalization – are all feeding
into the move to Voice & SEO’s demise
63. Three Data Levels
• Grossly Simplified: RAW, STRUCTURED, INSIGHTS
RAW DATA
POINT IN TIME
BUILDING
BLOCKS
FREE TEXT
SPOKEN
STRUCTURED
IN TIME
DIRECTIONAL
GROWTH &
DECLINE
SCHEMA
INSIGHTS
TRIGGERS
RELATIONSHIPS
PATTERNS
PREDICTION
ANSWERS
64. Three Data Levels
• Grossly Simplified: RAW, STRUCTURED, INSIGHTS
Stock Price
$58.00 /
share
News Stock
Overlay
News
Triggers High
Stock Chart
$58.00 is
a 52wk
High
NEWS
Alert
65. Search Engines Are Evolving
1. Searcher
(Human)
2. Search Engine
(Machine, mostly)
3. Source
(Human, mostly)
Potential
answers
Link to the Selected Answer
68. Why is This Getting More Important?
1. Searcher
(Human)
2. Search Engine
(Machine, mostly)
3. Source
(Human, mostly)
Potential
answers
Link to the Selected Answer
One Great Answer
69. Pichai recently noted that Google has been
“laying the foundation for this for
many, many years.”
This has led Google to develop an end-to-end
solution that means customers
NEVER HAVE TO OPEN AN APP OR
VISIT A WEBSITE.
73. Schema
“Over 10 million sites use Schema.org
to markup their pages and email
messages.”
Which basically means no one is doing this well.
74. Really? 10 Million?
We passed One Billion Websites in September of
2014, and its closer to 1.08B today
10,000,000 / 1,080,000,000 = .926%
Nice work, everyone!
< 1%
76. Schema Example: Restaurant
GreatFood
4 stars - based on 250 reviews
1 Madison Ave New York, NY 10010
Latitude: 40 deg 44 min 54.36 sec N
Longitude: 73 deg 59 min 8.5 sec W
(408) 714-1489
www.greatfood.com
Hours: Mon-Thu 5pm - 9:30pm
Fri-Sat 5pm - 10:00pm
Categories: Middle
Eastern, Mediterranean
Price Range: $$
Takes Reservations: Yes
77. Back to Tombstone
Q: “Alexa, What is a Tombstone?”
A: “A headstone or gravestone placed over a grave.”
Q: “Alexa, Is Tombstone a movie?”
A: “No, a gravestone is not a film.”
Q: “Alexa, is there a movie called Tombstone?”
A: “Yes, there is a film called Tombstone.”
Q: “Alexa, can you order me a Tombstone pizza?”
A: “I didn’t see that in your past orders, so I added a
Tombstone pizza to your shopping list.”
78. 100+
Location Data
Fields
Name
Address 1 & 2
Sublocality
Display Address
Address Visible
City
State
Postal Code
Country
Main Phone
Categories
Latitude
Longitude
Closed Flag
Special Offer
Special Offer URL
Business Hours
Holiday Hours
Description
Website
Website Display URL
Emails
Payment Methods
Logo
Photos
YouTube Video URLs
Menu
Products
Events
Bios
Additional Hours Text
Additional URLs
Alternate Phone
Mobile Phone
Fax
Toll-Free Number
Twitter Handle
Facebook Page
Year Established
Associations
Specialties
Brands
Languages
Keywords
Attribution Logo/URL
This Isn’t Easy, But It’s Critical