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I work at Portent where I am lucky to work with smart people (and not just because they help me with Excel).

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Funniest part: seeing IAs using the Toni Braxton store as an orientation point to find the conference venue

Not-best-part: Getting locked out of my room in a 5000+ room hotel and having to wait, wait, wait for someone to come and let me back in.

Best Part: getting called out by Rashmi Sinha in closing plenary for the call to action of broadening scope to include search optimization

Some time after: Peter Morville comes up with “findability” and Lou Rosenfeld starts his Search Metrics workshops.

This isn’t what I meant.

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Click Distance: the further from an authority page, the less important it must be

URL Depth: the further from the homepage, the less important it must be

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More images

More linked text

Sidebar navigation accompanies Global navigation

Yahoo becomes busier, more categories, international sites

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Apple capitalizes on new search technology with more heavily “designed” look

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Navigation dominance

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Apple introduces site navigation for the first time

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A true “home” page, start here and navigate to where you want to be

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Apple…not so much

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Broad band comes into its own and BIG pictures make a splash

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Why Google started moving away from link-based relevance

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I have presented at 2 UXPA DC UserFocus conferences Bird Bears Bs of Discoverability (well attended sessions)

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Using the Internet: Skill Related Problems in User Online Behavior; van Deursen & van Dijk; 2009

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We’re constructing worse queries but feel that we’re getting better results.

Which canary in what coal mine just died?

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Pew Internet Trust Study of Search engine behavior

http://www.pewinternet.org/Reports/2012/Search-Engine-Use-2012/Summary-of-findings.aspx

In January 2002, 52% of all Americans used search engines. In February 2012 that figure grew to 73% of all Americans. On any given day in early 2012, more than half of adults using the internet use a search engine (59%). That is double the 30% of internet users who were using search engines on a typical day in 2004. And people’s frequency of using search engines has jumped dramatically.

Moreover, users report generally good outcomes and relatively high confidence in the capabilities of search engines:

91% of search engine users say they always or most of the time find the information they are seeking when they use search engines

73% of search engine users say that most or all the information they find as they use search engines is accurate and trustworthy

66% of search engine users say search engines are a fair and unbiased source of information

55% of search engine users say that, in their experience, the quality of search results is getting better over time, while just 4% say it has gotten worse

52% of search engine users say search engine results have gotten more relevant and useful over time, while just 7% report that results have gotten less relevant

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Pew Internet Trust Study of Search engine behavior

http://www.pewinternet.org/Reports/2012/Search-Engine-Use-2012/Summary-of-findings.aspx

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And Google’s response…

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Personalization of results They Tracks: What is selected, Level of interaction, What is not-done (bounce rate) and use Signals: Location. Search history

Dynamic query suggestions - displayed as searcher enters query Calculation of information from 3 sources

User: previous search patterns Domain: countries, cultures, personalities GeoPersonalization: location-based results

Metrics used for probability modeling on future searches

Active: user actions in time

Passive: user toolbar information (bookmarks), desktop information (files), IP location, cookies

In 2002, Google acquired personalization technology Kaltix and founder Sep Kamver who has been head of Google personalization since

Defines personalization: “product that can use information given by the user to provide tailored, more individualized experience”

Personalization enables shorter, less specific queries set to change user behavior (easier, more natural queries) = search shorthand

Tied direct user interaction with results (ability to promote/demote in results set, add comment) discontinued because too noisy & interest did not always equal searching for topic and used by SEO community for other purposes

Only enable if signed in

Only impacted future searches (if signed in)

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User profile phases

1. Gather raw information

2. Construct profile from user data

3. Allow application to exploit profile to construct personal results

Keywords profiles represent areas of interest

Extracted from documents or directly provided by user, weights are numerical representation of user interest

Polysemy is a big problem for KW profiles

Semantic networks

Filtering system

Network of concepts – unlinked nodes with each node representing a discrete concept

Used by alta vista (used header that represented user personal data, set of stereotypes (prototypical user comprised of a set of interests represented by a frame of slots

Each “slot” (made up of domain, topic & weight (domain =area of interest, topic = specific term used to identify area of interest, weight = degree of interest) that makes up frame weighted for relevance

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Jaime Teevan MS Research (http://courses.ischool.berkeley.edu/i141/f07/lectures/teevan_personalization.pdf)

Tools used

Software agents: most reliable as more control over install and application

Cookies: least invasive

Login: more pervasive across machines and time

Proxy Servers: limited to user register of machine with server

Session IDs: limited to a single session

Advantages: more data, better data (easier for system to consume and rationalize)

Disadvantage: user has no control over what is collected

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Advantage: User has more control over personal and private information

Disadvantage: compliance, users have a hard time expressing interests, burdensome on user to fill out forms, false info from user

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Vince update 2009

http://searchenginewatch.com/article/2288128/Vince-The-Google-Update-We-Should-Be-Talking-About

Big brands can afford better sites

Big brands spend more $$ in adwords

“The internet is fast becoming a "cesspool" where false information thrives, Google CEO Eric Schmidt said yesterday. Speaking with an audience of magazine executives visiting the Google campus here as part of their annual industry conference, he said their brands were increasingly important signals that content can be trusted. …Brands are the solution, not the problem," Mr. Schmidt said. "Brands are how you sort out the cesspool….Brand affinity is clearly hard wired," he said. "It is so fundamental to human existence that it's not going away. It must have a genetic component.” Eric Schmidt, Google, October 2008

http://www.seobook.com/google-branding

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Google does not care about UX (just look at android)

Like it or not, part of Google’s evil strategy in selecting the UX community is because they think that we have our heads in the clouds.

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And sort of blames SEO for it (not outright but in a passive/aggressive) kind of way

2007 Google Patent: Methods and Systems for Identifying Manipulated Articles (November 2007)

Manipulation:

• Keyword stuffing (article text or metadata)

• Unrelated links

• Unrelated redirects

• Auto-generated in-links

• Guestbook pages (blog post comments)

Followed up: Google Patent: Content Entity Management (May 2012)

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Entity=anything that can be tagged as being associated with certain documents, e.g. Store, news source, product models, authors, artists, people, places thing

The entity processing unit looks at “candidate strings and compares to query log to extract: most clicked entity, most time spent by user)

Query logs (this is why they took away KW data – do not want us to reverse engineer as we have in past)

User Behavior information: user profile, access to documents seen as related to original document, amount of time on domain associated with one or more entities, whole or partial conversions that took place

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Receives the query

Applies user profile

Extracts query terms

Assigns entities

Identifies candidate synonyms (synonym database

Synonym engine assigns confidence score

phrase term order

placement on page (?)

using phrase engine (?) compound terms often found together

Compare to threshold

Satisfied – use revised query as well

Not satisfied – discard

Submit to index for SERP

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Screen capture of the software architecture from the patent filing

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http://stopdesign.com/archive/2009/03/20/goodbye-google.html

Douglas Bowman

on leaving as head of Google Visual Design (2009)

Tested 41 shades of blue

Debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case.

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Answered for us and the client

Would this become the first deliverable after signing?

Precipitate the client questionnaire?

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If machines are methodical, as we’ve seen, and people are emotional, as we experience, where is the middle ground? Are we working harder to really find what we need or just taking what we get and calling it what we wanted in the first place? Google Patents

•Improving Search using Population Information (November 2008)

•Rendering Context Sensitive Ads for Multi-topic searchers (April 2008)

•Presentation of Local Results (July 2008)

•Detecting Novel Content (November 2008)

•Document Scoring based on Document Content Update (May 2007)

•Document Scoring based on Link-based Criteria (April 2007)

Microsoft: Patents

Launches “decision engine” with focus on multiple meaning (contexts) as well as term indexing and topic association and tracking

-Lead researcher Susan Dumais at the forefront of user behavior for prediction on search relevance

-Look to recent acquisition of Powerset (semantic indexing) and FAST ESP (semantic processing)

Calculating Valence of Expressions within Docum0ents for Searching a Document Index (March 2009): System for natural language search and sentiment analysis through a breakdown of the valence manipulation in document

Efficiently Representing Word Sense Probabilities (April 2009): Word sense probabilities stored in a semantic index and mapped to “buckets.”

Tracking Storylines Around a Query (May 2008): Employ probabilistic or spectral techniques to discover themes within documents delivered over a stream of time

Compares the query with the contents of each document to discover whether query exists implicitly or explicitly in received document

Builds topic models

Consolidate the plurality of info around certain subjects (track stories that continue over time)

Collect results over time and sort (keeps track of the current themes and alerts to new)

Track

Rank (relevance)

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Present abstracts

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Users look to search engines for guidance. We can provide similar guidance with user controls

Tools Suggestions as query is entered

At page search box

On search page

Spell check/correction

Best Bets

Augmented Search results

Awards

Display PageRank score

Sharing

User Ratings

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Jared Spool did a site search study some time ago that found users successful 37% of the time when using site search and 50+% of the time when navigating

Users don’t like navigation at the outset but will use it if contextual and in a form that they can influence

Buzzallions: Top Ranked, Bottom Ranked, Most Reviewed, Price: Low to High, Price: High to Low

Tools

Facets

Filters

More Like This…

Always have opportunity to clear selections, return to original state

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Remember that most of the site visitors do not come through the home page.

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Search Metrics SEO Correlation factors 2013 Spearman Correlation – study of google result

Keywords in title should be placed as close to front as possible

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A descriptive, keyword-rich page title brings strong relevance weight to the page. Page title is the most important metadata field. It should always include the company name. It must map to the page content; you can’t just stuff irrelevant keywords in there. It does not appear ON the page [that is and <h1> tagged element within the <body> tags.

And, NO copy and paste please!

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Description may not have the favored status of <title>. Its importance comes in another form, helping the user to decide if they want to click through to the destination page.

One of the not-content elements that search engines note is how many people click through to your site and how long they stay there before coming back. The more “sticky” your site is, the better your chances of getting in front of people who need to know.

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Image search accounts for nearly 6% of Google searches

That adds up to approximately 600 million searches in May 2009

Read by screen reader technology so cannot sound too weird

3/13/2014

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This client invests a lot of time and effort in their News & Events directory

Customers are viewing the utility pages (Contact, etc) and the product justification/ROI section.

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Content Dashboard for Google Analytics

https://www.google.com/analytics/web/template?uid=YNIE7uQ4Ri-xjSid7V-q6Q

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Mom and creampuffs

The search engines think that we’re superfluous because we don’t “get search” That’s what I’m here to end. I want you to “get search.” We are information professionals, not mice! We’re going to use every neuron, synapsis and gray cell to fight back.

We will shift from trying to optimize search engine behavior to optimizing what the search engines consume, move from search engine optimization to information optimization

We will Focus

We will be Collaborative

We will get Connected

We will stay Current

Because we are user experience professionals, not Matt Cutts, Sergey Brin or Larry Page.

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