Dan Taylor's #SEO lightning talk about incorporating entity analysis into your SEO strategy, and three methods of scaling it.

1. Incorporating Entity
Analysis Into Site & Topic
Optimization
Optimizing for things, not strings.
Dan Taylor, SALT

2. Why does this matter?
We’ve known for a long time now that Google has advanced (and continues) to advance it’s
understanding of topics and entities, and the relationship (and strength) of relationship
between them.
In more (very) recent times, this is also important in how Google is now changing title tags
using elements from the URL, HTML, Image ALT text, headers…
@taylordanrw

3. Strings Became Things
With Hummingbird 2013, Google took search phrases, such as [whitby town] and advanced it
from being 2 words, 10 characters, to meaning an entity: m/09t9_k.
This then allowed RankBrain 2015 to go from seeing [whitby town play football] to [m/09t9_k
play m/02vx4].
Understanding this, and then the related topics and entities around specific topics/entities
allows us create better user experiences and map more points within Google’s own perception
of the world.
@taylordanrw

4. Entities
The majority of what we know about entities
has been taken from some patents, analysis,
asking the Google advocates, and from what
makes sense.
RankBrain is not a ranking factor in the
traditional sense. Its job is not to act as a
signal but rather to adjust which signals carry
what weight.
This doesn’t mean keywords are redundant.
Keywords are really vague and
unhelpful when you think about it. A
"pitcher" for example, can refer to
glassware or baseball. But as an
entity, each one is completely
separate. There is no ambiguity
because they are different entities
that simply share a keyword.
EMILY BRADY
Google is no longer a
"one-trick-wiki-
poney" for
#knowledgepanels -
FAR FAR from it, in
fact.
& Schema is not the
solution on its own.
JASON BARNARD
Entities are based on
word identification
and understanding.
Topic clusters are
critical to SEO on
scale. "Keywords" are
integral to both.
ALAN BLEIWEISS
This goes way beyond the traditional
thinking in SEO: one keyword > one
intent > one type of content > one
type of SERP. We now have to think
of entities first and ask ourselves
what kind of content we can build
around these entities.
ROSHAN S. AMBLER

5. Ranking Search Results Based On Entity Metrics
2015 Patent.
According to the patent, the ranking of entities for search involves considering four factors.
● Relatedness
● Notability
● Contribution
● Prize
Relatedness
Relatedness is determined based on the co-occurrence entities. Basically, if two entities are
referenced frequently on the web.
@taylordanrw

6. Ranking Search Results Based On Entity Metrics
Notability
Google uses a fairly simple formula (in the patent) to determine how notable an entity is.
Avoiding the formula, it basically breaks down that the more valuable an entity is (determined
by things including links, reviews, mentions, and relevance), the lower the value of the category
or topic it’s competing in, the higher its notability.
Contribution
Contribution is determined by external signals (e.g., links, reviews) and is basically a measure
of an entity’s contribution to a topic. A review from a well-established and respected food
critic would add to this metric than my opinions on how well the restaurant cooked their
steak.
Prize
The prize metric. A measure of the various relevant prizes an entity has received. These could
be a Nobel Prize, an Oscar, or a TechSEO Boost Innovation award.
@taylordanrw

7. Making this useful, means making this scalable
So we have justification for why this is a powerful way of looking at content, and user value
proposition - but the only way to make this useful is to make it scalable.
This means scalable data collection + common sense and analysis.
We can understand Google’s relations using various data sources. These include:
● Images + Image Search
● Google’s Knowledge Graph API
● Google Trends
@taylordanrw

8. Google Trends

9. Google Images
We know from other patents that
Google annotates images as part
of the mechanisms to grow and
increase connections within the
Knowledge Graph between
entities (object and attribute).

10. Google Images

11. Google Images

12. Google KG API
{
"@context": {
"EntitySearchResult": "goog:EntitySearchResult",
"detailedDescription": "goog:detailedDescription",
"kg": "http://g.co/kg",
"goog": "http://schema.googleapis.com/",
"@vocab": "http://schema.org/",
"resultScore": "goog:resultScore"
},
"@type": "ItemList",
"itemListElement": [
{
"resultScore": 1504.721435546875,
"result": {
"name": "Whitby Town F.C.",
"@type": [
"Organization",
"Thing",
"SportsTeam"
],
"description": "Football club",
"@id": "kg:/m/09t9_k",
"detailedDescription": {
"license": "https://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-
ShareAlike_3.0_Unported_License",
"articleBody": "Whitby Town Football Club is an English football club based in Whitby, North
Yorkshire. The club participates in the Northern Premier League, the seventh tier of English football. ",
"url": "https://en.wikipedia.org/wiki/Whitby_Town_F.C."
}
},

13. Google KG API
entityexplorer.com

14. Google KG API
carlhendy.com/knowledge-graph-search/

15. THANKS!
<email>dan@salt.agency</email>
<twitter>@taylordanrw</twitter>
<slides>https://dantaylor.online/slides</slides>
@SALT_agency // https://salt.agency
Let’s connect!