Signal to Noise Ratio

How much signal can you get out of a message when there is too much noise. Did I lose you? While signal to noise ratio is typically a electronic communications issue, signal to noise can also be a problem with communications. How many companies do you know that when they communicate something to its employees, that they all heard it. Too often that message is sent using only one channel, the intranet, or an email. But to do communications really well, communication must occur over multiple channels over a period of time. And of course, too often it not good either (too much noise).

Why? I believe a section in David Amerland's book, Semantic Search, can help shed some light. No matter the channel used, every message sent and received has three basic pieces, the emitter, the signal and the receiver. Let me use a simple internet example. The person that tweets, is the emitter, the tweet is the signal and the receiver is anyone that is following the "emitter".

Depending on the channel, the noise to signal changes. An email signal to noise ratio is different than using a intranet content. To be successful, the emitter needs to take the amount of noise on the channel into account to ensure the message is received clearly and concisely.

In addition, the channel that is chosen needs to be chosen carefully. As with internet marketing, there is many ways of getting a message out (commercials, twitter, facebook, print, etc.). As with the internet marketing, the enterprise communications team needs to choose the correct channel(s). Choosing the correct channel(s) over a specific time period is critical to ensure that the message is received by as many employees as possible. And remember, sometimes noise can obscure the message, especially if the emitter is someone that sends too many messages out to its audience.

This note was inspired +David Amerland book, Google Semantic Search - Amazon location 2129.

Knowledge graphs built from Enterprise Social Networks

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More and more companies are building social networks in the enterprise. For those keeping track, the common term used today is Enterprise Social Networks (ESN).In almost all cases, the reasoning for implementing an ESN is to improve collaboration, break down silos, ease the flow information, etc. One that is often missing is how it could influence search results in the enterprise.

In the internet, social networks play a huge role in helping with search results. This help does not come in the straight up indexing of the content and adding to the overwhelming amount of content already being indexed, but rather from the building a a social or knowledge graph from the social networks.

Google, Microsoft, Facebook, etc. have built algorithms to mine the content in social networks and to try to understand the relationships between the interactions happening in the social networks. While this information is used for many purposes, the mining of the data is used build out what is called a social graph and to extend knowledge graphs (think really big taxonomies or ontologies).

There is a big opportunity for companies to leverage their ESN implementations to improve their search results. This concept goes beyond the idea of ESN and could even be applied to any location people interact with each other (online meetings, Chat sessions, even corporate email).

By mining the information from these interactions, a social graph of related to topics and concepts can be built, that will improve how people search and eventually find the information they are most interested in.

This note was inspired  +David Amerland book,  Google Semantic Search - Amazon location 2111.

Marketing Enterprise Procedures/Processes/reference material

As I read David's book, I quickly realize that the internet content creation preparation checklist tips he provides at location 2075 (Kindle edition of the Google Semantic Search book) are similar items for how to create content in an enterprise. Basically, if you want your content (a policy, procedure, reference material) to be found, you need to use some simple marketing techniques (yes, marketing techniques, build and they will come does not work) and a great place to start is to adapt the checklist that David has in his book.

• Identify the types of content you are producing (policy/procedure/etc.)
• Decide what message you want to send to the different target audiences
• Explain how your policy/procedure/content reflects what you want to get across to the target audience
• Explain how the policy/procedure is consistent with the values of your department/division believes in
• Explain your content creation strategy, including frequency of updates, interactions with employees about the content, etc.
• Identify your main content /communication channel
• What other channels do you plan on using to get your message out about the policy/procedure?
• How do you plan on measuring success? (e.g. how do you know the policy/procedure/etc. reached the correct people?)
• Explain how you will identify the main traffic drivers in terms of the content produced for your policies/procedures

The ideas that David refers to in his book are often easy enough to translate from being specific to internet marketing and search strategies to enterprise marketing and search strategies. And in this scenario, this still holds true. Do you have a policy or procedure you need to communicate (market) to your employees? You are going to need to follow some of these basic tenants to be fully successful.

This note was inspired by +David Amerland  book, Google Semantic Search - Amazon location 2075

Corporate Publisher - you are more than just someone on a project

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So, its been several weeks since I last posted. No good reason except for life was moving faster than I could write. Picking up where I left off, David writes about the need for entrepreneur to realize that while they might have set their company up to sell something, they still need to be a publisher. Why? My perspective is that it is simple, as an entrepreneur, you need to do marketing.

I have been in many position in the enterprise where this same concept applies. If you worked on an project implementation that crosses a large part of the organization, you are very much like the entrepreneur. You need to become a publisher, a marketer, a cheerleader. Unfortunately, teams that provide services to other parts of the corporation often forget that they need to do marketing.

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1955.

I wonder ... Enterprise profile photos in search results

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I know that google has gone away from authorship and providing image previews, but I still wonder if there is some value in providing an image of the authori/authors next to search results. I believe that there is some serious value in the enterprise of showing all authors of a document or a piece of content, so people know who all contributed to the content.

I wonder if there could be some sort of UI design that would provide images of the authors in certain instances (they are authorities on a subject in the enterprise?) and not show the author images in the search results for when they are not the recognized authority on a topic.  Similar to my last post, this technique would most likely drive people to the "higher authority" content.

The only thing that puts some level of doubt into my mind is the changes that Google recently did to their search results. I wonder if they found that the pictures did not add that much to how people found the content they were looking for. I wonder if they determined that having those images did not improve the "trust" that people had for the content.  If that is the case, I wonder if providing profile photos next to the search results would increase or decrease the trust people had related to the content.  

I wonder...

This note was inspired by +David Amerland 's book, Google Semantic Search.

Images, previews and search results - how to attract bees to honey

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Much of the content in an enterprise intranet is documents. Documents of procedures, project plans, division and department policies, design document to, legal documents, etc. In fact this type of content completely overwhelms the content found related to corporate news, corporate communications and corporate policies. So how do you attract people to the content that is more important?

When people search for content, all content in the search results are not made equal and different techniques should be used to attract people to the content. One method is to provide an image or snippet of the actual content in the search results. Through semantic search, search should be able to determine which results should have an image, based on the quality of the snippet and the relative importance of the content. This technique means that not all search results would have an image snippet but rather a subset of the search results.

The two reasons why I came up with restricting images in the search results include:

1. By only providing images for some content, the search engine can help drive people to specific content. For example, content that is growing in authority but does not have the highest authority score might have an image snippet provided.
2. If all results had images, the search results would get over cluttered and the power of providing an image is actually a net negative, not a net positive.

To try to help the end user, I suggest that some images are provided and in other instances, the search results provides a way for people to click to get to a "preview" of the content. The image snippet would be a lower quality, less informative version of the preview. The images would attract employees to click the preview or go directly to the content, while the preview would allow people unsure if the content was what they were looking for a way to determine if the content is really what they were looking for.

And if you had not thought of it, the behavior of the image snippet and the viewing of the preview  can all feed into determining the best search results through authority and semantic methods.

This note was inspired by +David Amerland 's book, Google Semantic Search.

Click through rates (#CTR) and search basics 101

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I recently completed reading and taking rough notes from David Amerland's Google Semantic Search. The books is well worth the exercise of reading. I recommend that you read through the book while expanding your thinking by trying to determine how it might apply beyond what David discusses. While I indicated that I am done reading the book, I still have 30+ rough notes to convert to intelligent blog posts. So sit back and relax over the next several weeks as I review and share my thoughts generated by David's book.

Today's thoughts are pretty simple and to the point. As I read David's book, I realize that I am relearning many concepts that I once knew while learning many new concepts. This post is about click through rates (#CTR) and the impacts that they have on search results. I am relearning CTR and also learned some new thoughts and concepts. What I knew was that CTRs include the number of people that clicks a link to go to a site. What I learned beyond what I knew was that CTR also how long the person stays on the page or site.

And the great thing about this is that semantic search finds value in analyzing the length of time someone visits a site or a piece of content. Semantic search infers that the quality of content is higher when a person reads the sites pages and content for longer periods of time. Basically, the longer people stay, the higher the likelihood the content is quality and the more trustworthy the content should be treated.

And the beauty of this is, that this basic principal applies to semantic search in the enterprise. And such a simple concept can have a very large impact on search results in the enterprise allowing people to find the content that is most valuable and most trust worthy.

Love it - search basics 101.

This note was inspired by +David Amerland 's book, Google Semantic Search.

Reputation --> Trust --> Semantic Search in the Enterprise

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Based on what I have been reading I believe that I understand that semantic search is built on the trusting the content that has been written. This trust can be gained via trusting the individual and can the trustworthiness can be increased by people indicating that they trust the content.  

Based on this assumption and assuming that reputation is built based on both digital and analog interactions (especially in a closed environment like the enterprise), how can a complete picture of reputation (and hence trust) be built within the enterprise? And how can a great enterprise search experience be built without the full enterprise reputation picture being created? I would venture to guess that the interactions in digital will approximate the reputation in the analog world, but then again, that is assuming that there is 100% adoption and interaction in the enterprise digital systems. 

Anyone else have any thoughts?

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1853.

Building Widespread Trust because of Digital Reputation

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In the enterprise, reputation is traditionally built by analog interactions. Even when there are digital interactions,(email, esn, documents, papers, white papers, etc.) a large part of reputation still comes from 1:1, meetings, presentations, , etc. That means that reputation in the enterprise is not just based on a digital interaction. It also means that trust, which is based on reputation, is something that is built on both digital and analog interactions.

What I find interesting is that digital interactions can be so much more dramatically important than the analog interactions in building widespread trust. Why? The power of digital interactions in the enterprise is the reach it provides, allowing employees to build a reputation with employees they never work with and hence gain a level of trust with another employee that would have never been able to occur before that (series of ) digital interaction(s).

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1842

The Enterprise Knowledge Graph Grows from the Employee Profile

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This blog post has a little more conceptual thought that will probably require time to read David Amerland's book, Google Semantic Search (see the reference below to get an idea of what I was reading to understand the thoughts in this blog post)

The knowledge graph is a semantic search concept that is all about interpreting what is seen in the internet. The same concepts can be applied to the enterprise, and to be honest is probably a lot easier to do. If I understand how the knowledge graph works, the knowledge graph is built by manually and automatically. The automatic part is completed by the level of trust sites are given and the level of trust of information the search engines find. The knowledge graph is grown over time as it determine what is most trustworthy.

One of the many thoughts I had on the concept of the knowledge graph in the enterprise is that it can be grown systematically based on employee profiles. The links to project sites, links to primary contacts, links to topics that are related are often found in employee profiles. So Building out an enterprise profile is key to creating a social network of connections. The profile is a key piece of information that can help the knowledge graph grow - growing through the connections of topics to employees and employees to employees and then back from employees to topics.

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1727

Measuring the Flow of Information in the Enterprise

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In my previous post I talked about the idea of trust enabling the flow of information in a closed system like the enterprise. Continuing these thoughts, I conjecture that if there is trust which enables the flow of information, that these two items will make the workforce of an organization more effective. Assuming each of these things are true, how can you tell that an organization is becoming more effective? One way of determining this is to poll or survey the organization to see what people are saying related to trust. Gallup has a survey that is related engagement. a similar poll/survey could be used to determine the level of trust within the organization.

There are most likely other ways to measure effectiveness of an organization. For example, if you know that the flow of information is also correlated to trust and effectiveness, you might be able to measure the flow of information to gain insights into the effectiveness of the employees in an organization. And the great thing is, that by measuring it through this measure, you can obtain a second and different perspective on the level of trust and effectiveness in the organization.

So by measuring the participation between employees, where participation is not just the one way push of information, but the interactions between employees and the amount of collaboration between employees, you can start to get a picture of how much trust there is between employees in a company and you can measure the effectiveness of the organization. Going back to the big picture, if employees trust each other, they will start listening to each other, and the work force of an organization will become more effective. And going back to Ramanathan's statements, a closed system like the enterprise needs trust to occur to enable the flow of information.

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1678.

Trust in the Enterprise Enables the Flow of Information

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In David Amerland's book, Google Semantic Search, he references a research paper, Propagation of Trust and Distrust, by Ramanathan Guha. In the research paper, Ramanathan notes in his summary of results that "Typical webs of trust tend to be relatively 'sparse': virtually every user has expressed trust values for only a handful of other users." In closed environments there is a real need for wholesale participation in the system because that provides the connective matrix that helps generate trust.

Am I mistaken when I say that the enterprise is a 100% closed environment. Using Ramanathan's thoughts from his research, it is pretty easy to see that if you want information to flow in the enterprise, you have to build a level of trust within the enterprise between employees. As trust levels increase, flow of information between employees occurs at higher and higher effectiveness levels.

This concept does not just apply to Enterprise Social Networks (ESN) but it applies to the analog world and other technology systems. Obtaining 100% participation is easy when employees are in close proximity to each other but when people are spread across multiple floors, buildings and countries, obtaining 100% participation and building trust is much harder.

So if your employees need to trust people that are one floor above them or across the world, companies need to approximate close proximity. One of the best tools to use to enable improved communication through a trust network is an ESN built around virtual communities. Communities are places where people can go to share information about a topic of interest. These virtual communities can be for a topic like Java development or it could be about a project.

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1680.

Trusting intranet sites to improve search results

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Authority of a site or page is crucial for determining how a page or a site will show up in search results. That is the case for the internet and that is the case for enterprise intranets.  So, how do you measure the authority of a page or site in an intranet? Can the interactions of employees on sites help determine the authority of a site? How much does trust play in the role of authority? If the employees trust the page, should that have an impact on the authority rank of the site? Can you measure how much employees trust a site?

My opinion? Yep.  

And in many cases there are ways to systematically determine the authority of the site because of the actions of the employees on the site. One way of determining if a site is trust worthy is to measure the frequency of employees viewing a site. As enterprises embrace social though, there is the huge potential on how improving intranet search results.

David Amerland's book, Google Semantic Search, talks specifically about the internet and the influence of social on search results. Specifically, he states that based on individual interactions (social included) the search results are influenced. The ideas discussed in David's book easily translate to an enterprise intranet that has an Enterprise Social Network (ESN). David's list of influencers include:

• Commenting in a blog post on the website
• Responding to comments on a blog post on the website
• Commenting about a website in social network
• Responding to comments about a website in social networks 
• Resharing the content of websites and adding a comment to the reshare
• Resharing the content of websites without adding any comment
• Following websites that have a presence on a social network
• “Liking” or “+ 1-ing” the content of websites
• Interacting with the social network posts of websites

Why is this list so important? Because the list provides a way for people to show that they trust the content. And if they show they trust the content, than the there is a higher chance that the page or site should have an increased authority.  And if the content has a higher authority rank, then it should show up higher on the search results.  Without this type of interaction, enterprise search will continue to fall short.  

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1560.

Trust and Authority of Intranet Sites to Improve Search

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My trek reading through Google Semantic Search book continues with some insights into trust and authority of pages and sites. I continue to see search engine optimization similarities between what happens in the internet and what should be happening in the enterprise. For instance, in this note, the idea of a page or site being authoritative can be applied directly to helping employees find content in sites that are created in a company intranet.  

Inside the enterprise, often there are many different types  of "sites". These sites range from sites or pages for policies, sites where projects occur, reference material sites, self help sites, business procedures sites and community sites. And for each of these sites, the level of authority of trust associated with each site varies. In addition, these trust scores vary based on the subject or topic of the site.

For example the policy pages/sites should have a high trust/authority score, since they are basically the rules the company and employees need to follow.  A site for a project should have a much lower trust or authority score. Project sites typically are working on future state ideas, and do not represent the current state.  Just imagine what could happen if an employee were to read and use content on a project site to answer an customers question.

Similarly, sites that are for communities of practice should have a higher trust / authority score for the subjects they are centered around. The Java community site should have a high trust / authority score on the Java topic. The customer support community should have a high trust / authority score on customer support. etc.

By improving the authority of specific sites, especially around subjects, the findability and discoverability of sites increases, making every employee's life in the enterprise that much better and makes each of them more effective.

This note was inspired by +David Amerland 's book, Google Semantic Search.

Multiple Authors, Authority and SEO

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As I read through different books, each books gets me thinking and the note I create might not make perfect sense.  And sometimes when I review my notes, a note causes multiple thoughts to occur that are really not related.Today's and tomorrow's posts are both the outcome of the same note from the same location in David's book.

One of the issues with authorship occurs when more than one person is responsible for the blog post, document, wiki page. This is especially exposed when the last person that modified the document appears as the author of the document or content. Thankfully in the enterprise, there is a solution already in place to help resolve this issue (at least in most instances). Most internal collaboration and intranet systems include a mechanism identify each of the authors via history and versioning. Based on this history, the content can be attributed to each of the authors.

Enterprise search systems can use this extra meta data to increase authorship rank, trust and authority of that person on the subject while also influencing the page rank of other content from the same author on the same subject.

This comment was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1457

Page Rank, Authority and Enterprise Search

As explained in David's book, authority is used to help determine the rank of a piece of content.  And page rank is most likely influenced by using the items that David highlights in his book. Specifically:

• Who created the content
• What else that person has created in the past 
• The content creator’s social media connections
• The content creator’s online activity with further content
• The content creator’s interaction with other people
• How the content this person created was received in a social media setting
• The content’s quality, authority, and originality.
• The content’s stylistics (language level, reading difficulty, paragraph length, use of headings and subheadings, overall length, embedded links, supportive links in footnotes, citations, images, and any multimedia embedded in it.

I am not willing to completely read between the lines on this, but I sense that there could be a hint of not only knowing what content was created in the past by the person, but actually what content has the person created on the same subject in the past. If I do or do not read between the lines, I am thinking that authority can be taken to an extra layer of granularity within the enterprise.  What I mean is, authority can actually be assigned to employees for a specific subject area.  

Even in the enterprise, a page rank on a subject can still be applied using the bullets above with a couple of small adjustments.  Page rank would be influenced based on the person's previous content created on the subject, including both writing and social interactions on the subject.  

So, by building on the original thoughts in David's book, the ideas on determining the rank of a piece of content depends on not just the general authority of the person that created the content, but can be strengthened based on the authority the employee has on the subject the content is about.  (btw, I could have completely gone down the path that page rank should be based on the subject of the page, so it becomes more granular and is a subject page rank - this concept is much more difficult to do).

This comment was inspired by +David Amerland 's book, Google Semantic Search - Amazon Location 1351

Enterprise Identity is not a Differentiator in Enterprise Search

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As I read David Amerland's book, and I learn more and more about how semantic search works, I start to get a better understanding of how semantic web and semantic search might work within the enterprise.  

In the David's book, he refers to identity as being very important for building trust, authority and reputation.  As I think about the enterprise, all content has an author associated with it, especially when the enterprise has a collaboration system like Jive or SharePoint. In addition all content on the intranet portal like the news and policies have an author.  So in the enterprise, identity is almost always associated with content.

As David explains, identity enables authority which enables trust and builds a persons reputation.  So the question that I asked myself is, if identity is critical for authority, trust and reputation.  And if all content in the enterprise has an identity associated with it, what is the differentiator that builds authority and trust?

The differentiator that I came up with is ... identity is not a differentiator but rather the differentiator happens downstream where reputation is built based on the person's ability to become an authority on a subject.

This comment was inspired by +David Amerland 's book, Google Semantic Search - Amazon Location 1261

Enhancing the Enterprise Community via Search and Social

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This comment was inspired by +David Amerland 's book, Google Semantic Search.

David mentions that communities back in the day numbered in the 100's and that in those communities it was easy to reach out and contact another person since most people knew each other.  In many companies (not all) the same thing happens, employees are numbered in the 100's. While companies can and are in many cases similar to the the small communities mentioned in David Amerland's book, it doesn't mean that employees can just go over and talk to another person to get the answer. Employees do not know everyone in the enterprise as they would in a community.  The dynamics in the enterprise is different than a community. So, some of the best ways of getting answers to question employees don't know is to use search and to use social.

And if that is the case, what are you doing to ensure that search is built in a way that finds useful information and how are you preparing your organization to embrace social?

Reducing the Gap through Semantic and Social

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This comment was inspired by +David Amerland 's book, Google Semantic Search

As I think about semantic search and the value it can provide to an enterprise, I realize very quickly that enterprise semantic search is all about reducing the gaps and the distance between employees, groups, teams, departments, divisions. And combining the power of enterprise social with semantic search is even more powerful that either on their own.  These thoughts lead me to believe that it is all about getting people to realize and recognize that interacting, finding, discovering and interacting again is all about reducing the gap.

SEO won't fix a site that sucks

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As I stated in my last post, my plan is to regularly post short little notes I created as I read books. My expectation is that the posts will come in spurts, based on my ability to find time to read the book I am reading. As you will find, my notes are typically caused by the book and are not notes directly of or from the book. 

A couple of ground rules. I will always reference which book I was reading which caused the thought. If I can, I will reference where in the book I was when I wrote my comment, but there are times where it just does not make sense and the only reference you will see is to the book.  The notes I am posting could be as short as sentence or they could be longer. I will not be posting more than one note a day, but there could be many days between posts.

This comment was inspired by  +David Amerland 's book, Google Semantic Search

Remember, if people find the site through search or other means and the site sucks, you are going to do more harm than good.