Technology predictions 2010
Edit: Now includes predictions from: IDC, Gartner, Screen Digest, Elemental Links, Freeform Dynamics
Predicting what will be big is a fun game that all the analysts like to play each year. The technology industry, often so full of hype, frequently drinks its own Kool-Aid and genuinely believes that they have the next big thing. Obviously I am a cynic, but I often doff my cap to the analyst world who makes their living (as IDC say) analysing the future.
Consequently I have listed below some of the predictions that our analysts have come out with in the hope of looking back at this post in a years time to see how accurate their prophetic skills are.
IDC’s two big guesses are an “Apple iPad” and “Battles in the Cloud.” They have an excellent download detailing their full views here which i would recommend everyone to get. Their summary is as follows:
- Growth will return to the IT industry in 2010. We predict 3.2% growth for the year, returning the industry to 2008 spending levels of about $1.5 trillion.
- 2010 will also see improved growth and stability in the worldwide
telecommunications market, with worldwide spending predicted to increase 3%. - Emerging markets will lead the IT recovery, with BRIC countries growing 8–13%.
- Cloud computing will expand and mature as we see a strategic battle for cloud
platform leadership, new public cloud hot spots, private cloud offerings, cloud
appliances, and offerings that bridge public and private clouds. - It will be a watershed year in the ascension of mobile devices as strategic
platforms for commercial and enterprise developers as over 1 billion access the
Internet, iPhone apps triple, Android apps quintuple, and Apple’s "iPad" arrives. - Public networks — more important than ever — will continue their aggressive
evolution to fiber and 3G and 4G wireless. 4G will be overhyped, more wireless
networks will become "invisible," and the FCC will regulate over-the-top VoIP. - Business applications will undergo a fundamental transformation — fusing
business applications with social/collaboration software and analytics into a new generation of "socialytic" apps, challenging current market leaders. - Rising energy costs and pressure from the Copenhagen Climate Change
Conference will make sustainability a source of renewed opportunity for the IT
industry in 2010. - Other industries will come out of the recession with a transformation agenda and look to IT as an increasingly important lever for these initiatives. Smart meters and electronic medical records will hit important adoption levels.
- The IT industry’s transformations will drive a frenetic pace of M&A activity.
Gartner always one to beat the rush tend to name their strategic technologies in October for the next year. In fairness, they do have many bespoke reports on Predict 2010, they are behind their firewall so I cannot share the full content with you. However, below is their list of strategic technologies for 2010 which is in the public domain. I have fully copied below the below extract from the aforementioned release.
- Cloud Computing. Cloud computing is a style of computing that characterizes a model in which providers deliver a variety of IT-enabled capabilities to consumers. Cloud-based services can be exploited in a variety of ways to develop an application or a solution. Using cloud resources does not eliminate the costs of IT solutions, but does re-arrange some and reduce others. In addition, consuming cloud services enterprises will increasingly act as cloud providers and deliver application, information or business process services to customers and business partners.
- Advanced Analytics. Optimization and simulation is using analytical tools and models to maximize business process and decision effectiveness by examining alternative outcomes and scenarios, before, during and after process implementation and execution. This can be viewed as a third step in supporting operational business decisions. Fixed rules and prepared policies gave way to more informed decisions powered by the right information delivered at the right time, whether through customer relationship management (CRM) or enterprise resource planning (ERP) or other applications. The new step is to provide simulation, prediction, optimization and other analytics, not simply information, to empower even more decision flexibility at the time and place of every business process action. The new step looks into the future, predicting what can or will happen.
- Client Computing. Virtualization is bringing new ways of packaging client computing applications and capabilities. As a result, the choice of a particular PC hardware platform, and eventually the OS platform, becomes less critical. Enterprises should proactively build a five to eight year strategic client computing roadmap outlining an approach to device standards, ownership and support; operating system and application selection, deployment and update; and management and security plans to manage diversity.
- IT for Green. IT can enable many green initiatives. The use of IT, particularly among the white collar staff, can greatly enhance an enterprise’s green credentials. Common green initiatives include the use of e-documents, reducing travel and teleworking. IT can also provide the analytic tools that others in the enterprise may use to reduce energy consumption in the transportation of goods or other carbon management activities.
- Reshaping the Data Center. In the past, design principles for data centers were simple: Figure out what you have, estimate growth for 15 to 20 years, then build to suit. Newly-built data centers often opened with huge areas of white floor space, fully powered and backed by a uninterruptible power supply (UPS), water-and air-cooled and mostly empty. However, costs are actually lower if enterprises adopt a pod-based approach to data center construction and expansion. If 9,000 square feet is expected to be needed during the life of a data center, then design the site to support it, but only build what’s needed for five to seven years. Cutting operating expenses, which are a nontrivial part of the overall IT spend for most clients, frees up money to apply to other projects or investments either in IT or in the business itself.
- Social Computing. Workers do not want two distinct environments to support their work – one for their own work products (whether personal or group) and another for accessing “external” information. Enterprises must focus both on use of social software and social media in the enterprise and participation and integration with externally facing enterprise-sponsored and public communities. Do not ignore the role of the social profile to bring communities together.
- Security – Activity Monitoring. Traditionally, security has focused on putting up a perimeter fence to keep others out, but it has evolved to monitoring activities and identifying patterns that would have been missed before. Information security professionals face the challenge of detecting malicious activity in a constant stream of discrete events that are usually associated with an authorized user and are generated from multiple network, system and application sources. At the same time, security departments are facing increasing demands for ever-greater log analysis and reporting to support audit requirements. A variety of complimentary (and sometimes overlapping) monitoring and analysis tools help enterprises better detect and investigate suspicious activity – often with real-time alerting or transaction intervention. By understanding the strengths and weaknesses of these tools, enterprises can better understand how to use them to defend the enterprise and meet audit requirements.
- Flash Memory. Flash memory is not new, but it is moving up to a new tier in the storage echelon. Flash memory is a semiconductor memory device, familiar from its use in USB memory sticks and digital camera cards. It is much faster than rotating disk, but considerably more expensive, however this differential is shrinking. At the rate of price declines, the technology will enjoy more than a 100 percent compound annual growth rate during the new few years and become strategic in many IT areas including consumer devices, entertainment equipment and other embedded IT systems. In addition, it offers a new layer of the storage hierarchy in servers and client computers that has key advantages including space, heat, performance and ruggedness.
- Virtualization for Availability. Virtualization has been on the list of top strategic technologies in previous years. It is on the list this year because Gartner emphases new elements such as live migration for availability that have longer term implications. Live migration is the movement of a running virtual machine (VM), while its operating system and other software continue to execute as if they remained on the original physical server. This takes place by replicating the state of physical memory between the source and destination VMs, then, at some instant in time, one instruction finishes execution on the source machine and the next instruction begins on the destination machine.
However, if replication of memory continues indefinitely, but execution of instructions remains on the source VM, and then the source VM fails the next instruction would now place on the destination machine. If the destination VM were to fail, just pick a new destination to start the indefinite migration, thus making very high availability possible.
The key value proposition is to displace a variety of separate mechanisms with a single “dial” that can be set to any level of availability from baseline to fault tolerance, all using a common mechanism and permitting the settings to be changed rapidly as needed. Expensive high-reliability hardware, with fail-over cluster software and perhaps even fault-tolerant hardware could be dispensed with, but still meet availability needs. This is key to cutting costs, lowering complexity, as well as increasing agility as needs shift. - Mobile Applications. By year-end 2010, 1.2 billion people will carry handsets capable of rich, mobile commerce providing a rich environment for the convergence of mobility and the Web. There are already many thousands of applications for platforms such as the Apple iPhone, in spite of the limited market and need for unique coding. It may take a newer version that is designed to flexibly operate on both full PC and miniature systems, but if the operating system interface and processor architecture were identical, that enabling factor would create a huge turn upwards in mobile application availability.
Edit now with mobile predictions from Julien Theys at Screen Digest (his view not the companies)
- Facebook’s careful and progressive foray into Location-Based services will deal a deadly blow to many mobile LBS startups
- SonyEricsson and Motorola’s handset businesses will face very serious existential crisis and possibly split up.
- Sony is very likely to take another solo shot at mobile (especially if it wants to leverage the Playstation branding)
- Palm will be acquired by a bigger fish
- Sync services, Address Book/Social Network consolidation and cloud backups are going to be ubiquitous
- Apple’s app store will remain an outlier in terms of success. Developers of crappy apps will blame everyone but themselves for not making any money.
App rejection horror stories will keep tech pundits busy yet customers won’t care. - Open source mobile software will keep tech pundits busy yet customers won’t care
- A very bad year for Windows Mobile, Microsoft to (try to) unify all its scattered efforts in portable media (WinMo, Zune, Sidekick…)
- A surprisingly high number of people will keep buying simple phones and not care about mobile web
- Wholesale B2B mobile data deals (like Kindle content delivery) to bring in extra cash for operators (big for eBook readers, navigation and automotive industries)
- Don’t hold your breath: Google hardware, iPhone nano, Android-based Nokias, decent mobile broadband speed & coverage.
- Tempted to say no Apple Tablet in 2010 because, really, where’s the rush?
Edit: single predictions from analysts:
- The biggest thing in IT in 2010 will be datacentres. but thanks to virtualisation they will be a tad lighter.
Martin Atherton from Freeform Dynamics - 2010: Event Processing transcends niche status, to well-recognized & adopted business technique for real-time visibility & responsiveness.
Brenda Michelson from Elemental Links
I will update this post with additional content as it becomes available from other analyst houses in the hope of having a one-place summary.
Additional note: Edelman have had their own stab at gazing into the crystal ball looking at what 2010 and beyond may hold for the Economy, Business, Government and the Media. You can read the full content here.
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Gartner buys AMR
In breaking news today, Gartner has bought AMR Research for $64 million in cash. In total this acquisition brings Gartner an extra 40 analysts and 45 sales people.
What this means – our view…
This is a very smart move by Gartner and continues their approach to acquire firms and therefore individuals who have rich industry experience. What’s more this also enables Gartner to enrich their vertical portfolio which in recent years has fallen in lieu of their horizontal expertise.
Perhaps most significantly though they have purchased the key thought leadership in the supply chain (such as Nigel Montgomery). This is intrinsically linked to IT and therefore a natural complement to analyst advisory services.
Perhaps the other less obvious reason for this acquisition is the subsequent hiring of a very experienced sales force who will no doubt help Gartner sell its richer portfolio.
Looking at previous mergers (such as Meta), we can expect some natural churn but overall I think this is good for Gartner.
But is it good for AMR and their client base?
At first glance you would say ‘yes’. Previous AMR clients will now have access to Gartner’s rich resources as well as their analysts giving a far broader and richer experience – I expect that with time this will come at an extra cost but we will have to wait and see.
For the other industry players, it is a clear sign that they will have to up their game once again.
If you’re interesting in reading more on this, it’s worth checking out the IIAR blog post on the acquisition. There’s some interesting and valuable insights there.
More information: link to Yahoo news, Gartner press release
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Top analyst blogs
Within the analyst world the past year has been a dichotomy in the land of blogging. Whereas we have seen a surge in the number of analysts that have taken to this medium, it is contrasted with a decrease from the recognised ‘leaders’ in the frequency of which they post.
This new ranking system has fundamentally evolved since the last version to take into account the seismic shifts in the way people communicate online. The key changes relate to inbound links such as from Twitter as well as well as a combined Yahoo / Google (3-month date limited) approach.
Whenever these lists are published, there are several points that always get raised which I will address now…
- This blog is not from an analyst. The argument as to whom is an analyst or a consultant is becoming largely moot. In my opinion if someone is independent and directly influences technology procurement then they are an analyst. I know this will cause a huge amount of disagreement but as an outsider looking in this is the way I see the market. This is not to say that some analysts have different strengths over others, it is more a case that I think as an AR pro, I need to monitor the lot of you.
- The blog is written by multiple authors. Some blogs have several analysts writing them whereas others do not. The merits of a single blog author is something that I personally favour as this allows me to understand the tone of blog without having to understand the many personalities that are associated with it. Regardless, for this table, my view has not been to argue this but merely to present the data.
- It is irrelevant showing all the blogs as I am only interested in a specific topic – bingo, that is exactly right. My suggestion to all AR pros is to identify which of your analysts are on this and only look at those. This list compiled from the newly updated analyst blog directory on Tekrati does not see to micro-segment but merely to list all blogs regardless of their speciality.
- Hey – you have forgotten to include this blog. Please let me know the name and if I will include it as an edit.
- Isn’t this just like TweetLevel but for blogs? Yep, this algorithm is part of a larger project to fully understand influence and engagement on the web. This methodology is part of BlogLevel.
- Will you be producing a league table for those on Twitter? Yes, next week.
Without further ado, congrats to everyone who is included and especially those who have managed to make the top 50 – this is an outstanding achievement. Of course, a huge pat on the back to ex-Forrester and now Altimeter analyst, Jeremiah Owyang for showing everyone how to combine blogs and twitter to tremendous affect.
Edit: Since this blog was originally posted several blogs have now been added (including Denis Howlett – #2, Michael Krigsman – #6, Esteban Kolsky – #42 and Michael Gartenberg – #61). A special congrats to Denis for jumping in at second place.
Methodology
I have taken the feedback I have received from the previous research and modified the methodology.
Scores are now calculated as follows:
Google PageRank – Google PageRank is a link analysis algorithm that interprets web links and assigns a numerical weighting (0 to 10) to each page. High-quality pages receive a higher PageRank. The ranking uses the actual PageRank of the blogs homepage as part of its algorithm.
Yahoo Inbound Links [date unlimited] – Yahoo counts the total number of inbound links that go directly to a blog. Each number was assigned to a range which was then used as part of the algorithm.
Google Inbound Links [3 months date limited] – Google allows people to search the number of inbound links to a specific blog but limit this to a predefined date period. Similar to how Technorati only looks at six months of data, this method was used in combination with the Yahoo Inbound Link count to assess which blogs were considered to be important due to the number of links that came to them, but also currently relevant as measured by the limitations on the timescale. Each number was assigned to a range which was then used as part of the algorithm.
Google Reader Subscribers – Google reader lists the total number of subscribers to a blog. I believe this is a more realistic number to that which Bloglines provides. Mihai Parparita confirms that “these numbers include subscribers across all Google services”. To account for people using other readers (e.g. Newsgator) it has been suggested that this number is multiplied by 3. Subscriber ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number that was used as part of the algorithm.
Frequency of Posts – Updating relevant and interesting content frequently onto a blog will naturally cause more people to find this blog important. This score is established via Google Reader to understand the precise number of posts per week that the blogger makes. Frequency numbers were determined and assigned to a range that was used as part of the algorithm.
Date Last Blog Post Published – Working in combination with ‘Frequency of Posts’, this score mitigates against blogs that were once popular but haven’t been updated for a long time. The number of days since the last blog post was calculated and assigned to a range which was used as part of the algorithm.
Comments – A simple way to judge how valuable a blog is to other people is through the number of comments (where this is enabled) that visitors make. In a similar way to linking and subscribing this user requested service shows a significant value. The number of comments made over the last five posts were calculated and assigned to a range which was used as part of the algorithm.
Twitter Inbound Links – There are various online tools available to count the number of links inbound to a blog from Twitter. Backtype was used to count the number of these occurrences over the past five blog posts. The number of times this happened was calculated and assigned a range which was used as part of the algorithm.
Weighting – Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish a blogs total score.
Badges
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Gartner MQ for dummies
Found on Geek and Poke, hat tip: Robert De Souza
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My colleagues in the PA department have written a wonderful analysis of the Queens’s speech. This is available for download here.
This year’s Speech outlines the Government’s final programme of planned laws ahead of the General Election and has focused on a range of priority political issues. Included are measures to tackle the nation’s finances through putting into law a pledge to halve the budget deficit within four years, a Bill to prevent a repeat of the recession by stopping “reckless” bankers from getting bonuses and plans to improve welfare services, for instance by providing free social care for the most needy.
Headline points include:
- Financial Services Bill
- Fiscal Responsibility Bill
- Energy Bill
- Digital Economy Bill
The Conservative and Liberal Democrat parties outlined their respective opposition to the Speech this year before it was even made, with both stating that most of the Bills within the Speech will not become law, with a General Election due by June 2010,
and that consequently the Speech is little more than a Labour Party manifesto, considered by the Conservative leader David Cameron to be a “waste of time”.
The Government and Conservative Party continued their debate today about the practical reality of introducing so many Bills with so little time left before the General Election to bring them on to the Statute Book (there are 10 new bills and three Bills carried over from the last parliamentary year in this year’s Speech, with around only 70 days left when Parliament will sit before the General Election must be called). The Government continues to argue that “most” of the proposed Bills will be passed before the next election, whereas the Conservative Party has stated that its peers are prepared to obstruct many of the proposals in order to prevent this.
Nick Clegg, leader of the Liberal Democrats, went even further than the Conservative Party in his criticism, stating that it should not even have taken place this year as the Government instead should have focused on the more pressing priority of reforming parliamentary expenses and spending in order to win back the trust of the general public.
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TweetLevel is a new measurement tool that calculates someone’s importance on Twitter. In other words it is the Twitter equivalent to Google’s PageRank.
The explosive growth of Twitter has massively impacted the nature of communications. Initially the domain of the tech-minority, it has now reached a maturity level where it has branched out to multiple demographics.
Tables: Nielsen Twitter usage increase Feb 08 to Feb 09 and Nielsen Twitter usage age groups
My personal view is that as long as Twitter is the tool that key audiences use then I will use it too – if everyone changes next week to product X, then I will too. However, as a communications professional, it is my job to take part in the conversations that my key audiences are having no matter where they take place.
Jeremiah Owyang of Altimeter Group sums it up:
I’ll be very clear on this. If you want to influence me, be in a conversation and dialog with me, in person, online, and wherever I go.
One of the common questions Edelman is asked is ‘who should I spend my limited time with?’. It is this question that has forced companies to tier their audiences depending upon their impact within the wider community. One of the common problems associated with ranking twitter users is the misconception that popularity = influence. This couldn’t be further from the truth. Popularity has its place but it should not be the only metric that defines ‘importance’.
TwitterLevel aims to answer this question.
This unique tool compiles twitter data from over 30 sources and feeds the data through an algorithm to rank an individual according to four weightings:
- Popularity (i.e. How many people follow you)
- Influence (i.e. What you say is interesting, relevant and many people listen)
- Engaged (i.e. You actively participate within your community)
- Trusted (i.e. People believe what you say)
Of course, the explanation above is a simplified definition of a complex algorithm(the full methodology of this is shown at the bottom of this post).
To illustrate how this works, I have selected four individuals who each excel in different areas. What this shows is not a measure of an individuals ‘importance’ in the world or even social media but simply how they use Twitter.
Popular – CNN Breaking News
With close to 2.8 million followers this account is exceptionally popular. However, by contrast its engagement score is very low – this is because all the account does is broadcast its opinion (and links) without engaging in conversations with other people. However, without doubt it is exceptionally important as people believe what it says (as shown by its trust score) and its content is retweeted frequently.
Influential – Calvin Lee
Calvin Lee at Mayhem Studios has a high influence score, but a low number of followers as compared to other people in the top 20 TweetLevel names ranked by influence. With less than 40,000 followers Calvin understands that within Twitter it is micro-communities that count not necessarily who can win the popularity contest. Calvin also has a very high engagement score as a result of interactively discussing frequent, relevant and interesting content.
Engagement – T-Mobile USA
Congratulations to T-Mobile for understanding that the key to using Twitter as a tool is to have two-way conversations that are informative with their community. They have mastered this medium and have been ranked top over a list of millions when it comes to who has the most engaged Twitter account.
Just as PR has gone to public engagement, and AR has gone to analyst engagement, it is only natural that I believe that instead of mass-broadcast (shown by popularity) or mass-amplification (shown by influence), I believe that the purest form of interaction is via multiple targeted micro-conversations where people actively engage and interact with the niche community. This is why when scores are weighted for ‘engagement’ the ‘involvement index’ becomes the most important factor.
Robert Scoble in his recent post discussing the merits of Twitter’s Suggested Users touches on engagement. He explains that the number of followers someone has (i.e. their popularity on Twitter) should be turned off and the answer… engagement.
Turn off follower counts for everyone and come up with a new “engagement score” that is more focused on how you use Twitter and how people engage with you.
Couldn’t agree more which is why TweetLevel has such a high weighting on this metric.
Trust – Paulo Coelhlo
The extra measurement of trust has been included as this factor is the key to action. When people are reviewing how they should act, they may take into consideration someone who is popular, influential or engaged – however, this final metric is the decisive or tipping point. This view is backed-up by the Edelman trust barometer which stated that:
77% of people refused to buy products or services from a company they distrusted
It is this final measure of trust that has been the most discussed during beta testing. After all how do you measure trust on Twitter? Although not the only factor that decides this ranking, in my opinion if someone is prepared to associate what someone else has said with them (via retweeting for example), then this indicates a measure of trust. Whereas some Twitter users achieve this via posting news (such as CNN), others such as Paulo Coehlo have achieved a magnificent trust score by tweeting content that other people wish to spread throughout the twittersphere.
As a final point, I know that when discussing this people tend to be far more interested in ‘influence’ rather than engagement or trust. My view was nicely echoed by AdAge when commenting on Ashton Kutcher’s use of bill board advertising when trying to win the (in)formal ‘first to 1million followers’ against CNN competition. In this piece they quoted a New York commenter who goes by Stevewax:
Seems to me what’s useful with Twitter is creating a small, two-way community with people who aren’t busy running a Twitter team and who have time to SHARE ideas. Rather than broadcast them.
Find out what your TweetLevel is
Simply go to: www.tweetlevel.com now and find out your score. While you are at it, try a few other people and see how you compare to them. I welcome your feedback as to how this can be improved or your comments in general.
Algorithm and Methodology
Following – Twitter lists the number of people each user follows. The tendency for most celebrities is to only follow a few individuals. The more people that someone follows, there is an increased likelihood of them actively participating in conversations with the community instead of simply broadcasting to it. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.
Followers – Twitter lists the number of people that follow each user. Like subscribing to a feed, this is a clear indication of ‘popularity’ as it requires someone to actively request participation. Even though TweetLevel has a ranking of people based upon popularity, it is influence, engagement and trust that is more important. Due to the nature of logarithmic ranges, a change in the number of people that follow someone, such as from 500 – 1000, will give a far higher change in score than a move from 180K – 200K. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.</p>
Twitter Lists – without a doubt this feature addition to Twitter will significantly change the influence score. Even though Twitter has released their API to us, this particular metric is not yet included. When it is, a TweetLevel score will increase depending upon the number of times a user is included in a list, the number of people who follow that list and the authority of those people.
Updates – How often does someone update what they are doing. This number is purely objective as it scores someone highly no matter what the content of their post (i.e. how relevant is it). Nevertheless it is assumed that if someone posts frequently but has poor content then their ‘followers’ will decrease. Update ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm.
Name Pointing – e.g. @name – How many people engage in conversation with a celebrity or point to their name. The clearest way to establish this is to run a search on the number of people who reference @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 30) – again this was then used as part of the algorithm.
Retweets – Has a tweet caused sufficient interest that it is worth re-submitting by others? Despite a great deal of ‘noise’ (i.e. posts that are not relevant or interesting), when someone sees something that is of high interest, their post can be re-tweeted. The clearest way to establish this is to run a search on the number of people who reference RT @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 50) – again this was then used as part of the algorithm.
Twitalyzer – “This is a unique (and online) tool to evaluate the activity of any Twitter user and report on relative influence, signal-to-noise ratio, generosity, velocity, clout, and other useful measures of success in social media.” This 3rd party tool is a useful method to combine automated metrics dependent upon criteria within posts and publicly available numbers. Where tools such as this are available, we incorporate them into the algorithm to achieve a more confident score. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twitalyzer noise to signal ratio – Signal-to-noise ratio is a measure of the tendency for people to pass information, as opposed to anecdote. Signal can be references to other people (defined by the use of "@" followed by text), links to URLs you can visit (defined by the use of "http://" followed by text), hashtags you can explore and participate with (defined by the use of "#" followed by text), retweets of other people, passing along information (defined by the use of "rt", "r/t/", "retweet" or "via"). If you take the sum of these four elements and divide that by the number of updates published, you get the "signal to noise" ratio. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twinfluence Rank – Twinfluence is an automated 3rd party tool that uses APIs to measure influence. For example: “Imagine Twitterer1, who has 10,000 followers – most of which are bots and inactives with no followers of their own. Now imagine Twitterer2, who only has 10 followers – but each of them has 5,000 followers. Who has the most real "influence?" Twitterer2, of course.” As with Twitalyzer, this index uses 3rd party tools to add greater confidence in the overall Twitter score. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Twitter Grader – Twitter Grader is the final automated tool to add greater confidence to the final index. This site creates a score by evaluating a twitter profile. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Involvement Index – The Involvement Index is unique Edelman IP that calculates a score based upon how an individual engages with their community. It is calculated by analysing the content of an individual posts. People who score highest in this category have frequent, relevant, high-quality content that actively involved the twitter community (asking questions, posting links or commenting on discussions) and did not purely consist of broadcasting. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Velocity Index – As more people engage on Twitter, it may become harder to keep activity going. The velocity index measures changes on a regular basis and assigns a score based on increased or decreased participation. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.
Weighting - Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish an individual’s total score.
Weighted for Popularity – the key variable is the number of people someone has following them. There are many online tools that show this such as Twitterholic.
Weighted for Engagement – the key variables are an individual’s participation with the Twitter community (as measured by the Involvement Index), with additional emphasis on the frequency of people name pointing an individual (via @username), the numbers of followers and the signal to noise ratio. Other attributes were included in the final score but were given a lower weighting.
Weighted for Influence – the key variables in this instance is a combination of the number and authority of someone’s followers together with the frequency of people name pointing an individual (via @username) and the how many times and individuals posts are re-tweeted. Other attributes were included in the final score but were given a lower weighting.
Weighted for trust – the best measure of trust is whether an in individual is will to ‘trust’ what someone else has said sufficiently that they are also prepared to have what they tweeted associated with them. The key metric in this instance are a combination of retweets and number of followers. Other attributes were included in the final score but were given a lower weighting.
In the true spirit of ‘open sourcing’ this work, I welcome your comments, views and criticisms in how this approach can be as accurate as possible. Whereas I don’t believe for one moment that TweetLevel has found the holy grail of social media measurement, I think it is a good step forward and look forward to discussing this with you.
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Top analyst blogs
Within the analyst world the past year has been a dichotomy in the land of blogging. Whereas we have seen a surge in the number of analysts that have taken to this medium, it is contrasted with a decrease from the recognised ‘leaders’ in the frequency of which they post.
This new ranking system has fundamentally evolved since the last version to take into account the seismic shifts in the way people communicate online. The key changes relate to inbound links such as from Twitter as well as well as a combined Yahoo / Google (3-month date limited) approach.
Whenever these lists are published, there are several points that always get raised which I will address now…
- This blog is not from an analyst. The argument as to whom is an analyst or a consultant is becoming largely moot. In my opinion if someone is independent and directly influences technology procurement then they are an analyst. I know this will cause a huge amount of disagreement but as an outsider looking in this is the way I see the market. This is not to say that some analysts have different strengths over others, it is more a case that I think as an AR pro, I need to monitor the lot of you.
- The blog is written by multiple authors. Some blogs have several analysts writing them whereas others do not. The merits of a single blog author is something that I personally favour as this allows me to understand the tone of blog without having to understand the many personalities that are associated with it. Regardless, for this table, my view has not been to argue this but merely to present the data.
- It is irrelevant showing all the blogs as I am only interested in a specific topic – bingo, that is exactly right. My suggestion to all AR pros is to identify which of your analysts are on this and only look at those. This list compiled from the newly updated analyst blog directory on Tekrati does not see to micro-segment but merely to list all blogs regardless of their speciality.
- Hey – you have forgotten to include this blog. Please let me know the name and if I will include it as an edit.
- Isn’t this just like TweetLevel but for blogs? Yep, this algorthim is part of a larger project to fully understand infleunce and engagement on the web. This methodology is part of BlogLevel.
- Will you be producing a league table for those on Twitter? Yes, next week.
Without further ado, congrats to everyone who is included and especially those who have managed to make the top 50 – this is an outstanding achievement. Of course, a huge pat on the back to ex-Forrester and now Altimeter analyst, Jeremiah Owyang for showing everyone how to combine blogs and twitter to tremendous affect.
Edit: Since this blog was originally posted the following blogs have now been added. A special congreats to Denis for jumping in at #2.
| Rank |
Blog Name |
 |
 |
 |
 |
 |
 |
| 2 | Denis Howlett | 16.8 | 4.5 | 8.1 | 12.5 | 23.5 | 65.3 |
| 40 | Esteban Kolsky | 9.6 | 4.5 | 5.0 | 7.5 | 19.1 | 45.7 |
| 57 | GartenBlog | 12.0 | 4.2 | 6.2 | 14.1 | 5.8 | 42.3 |
| 215 | In Full Bloom | 2.4 | 3.4 | 0.0 | 8.7 | 11.4 | 25.9 |
| Rank |
Blog Name |
|
|
|
|
|
|
| 1 | Web Strategy by Jeremiah | 14.4 | 5.7 | 12.0 | 24.0 | 27.5 | 83.6 |
| 2 | Compete Blog | 14.4 | 4.8 | 9.3 | 19.4 | 14.7 | 62.7 |
| 3 | Workplace Learning Today | 12.0 | 4.1 | 7.5 | 14.0 | 24.9 | 62.4 |
| 4 | James Governor’s MonkChips | 14.4 | 5.1 | 7.7 | 17.5 | 13.8 | 58.4 |
| 5 | Virtually Speaking | 16.8 | 4.4 | 6.6 | 8.7 | 21.7 | 58.3 |
| 6 | Service-Oriented Architecture | 16.8 | 4.8 | 8.7 | 14.2 | 13.7 | 58.2 |
| 7 | StorageMojo | 12.0 | 5.2 | 8.7 | 14.0 | 17.2 | 57.1 |
| 8 | Storage Bits | 16.8 | 4.4 | 9.6 | 0.0 | 26.4 | 57.1 |
| 9 | Greenmonk Associates | 14.4 | 4.5 | 6.9 | 13.1 | 16.7 | 55.6 |
| 10 | Customer Experience Matters | 12.0 | 4.5 | 8.0 | 17.5 | 13.4 | 55.3 |
| 11 | People Over Process | 14.4 | 4.6 | 7.3 | 16.4 | 11.4 | 54.1 |
| 12 | Chilmark Research | 12.0 | 4.1 | 7.7 | 14.4 | 15.9 | 54.1 |
| 13 | Collaborative Thinking | 14.4 | 4.7 | 7.5 | 14.1 | 13.3 | 53.9 |
| 14 | Column 2 by Sandy Kemsley | 12.0 | 4.4 | 9.1 | 12.4 | 15.4 | 53.3 |
| 15 | DBMS2 – DataBase Management System Services | 12.0 | 4.3 | 7.2 | 15.3 | 14.5 | 53.2 |
| 16 | Dean Bubley’s Disruptive Wireless | 12.0 | 4.3 | 6.5 | 15.8 | 13.8 | 52.4 |
| 17 | A Software Insider’s Point of View | 12.0 | 4.3 | 8.0 | 15.1 | 13.0 | 52.3 |
| 18 | CMS Watch Trends and Features | 14.4 | 3.4 | 3.2 | 20.0 | 10.4 | 51.4 |
| 19 | James Bach’s Blog | 9.6 | 4.5 | 7.7 | 17.4 | 11.1 | 50.2 |
| 20 | Hitwise Intelligence | 14.4 | 4.9 | 0.0 | 16.4 | 14.5 | 50.1 |
| 21 | Deal Architect | 12.0 | 3.9 | 10.2 | 11.8 | 12.2 | 50.0 |
| 22 | GoMo News | 12.0 | 4.8 | 10.3 | 11.1 | 11.3 | 49.5 |
| 23 | IDC eXchange | 14.4 | 3.8 | 5.5 | 14.7 | 11.0 | 49.4 |
| 24 | Message | 12.0 | 4.4 | 9.6 | 16.3 | 6.4 | 48.7 |
| 25 | Identity and Privacy Strategies Blog | 12.0 | 3.9 | 7.7 | 12.4 | 12.5 | 48.5 |
| 26 | Outside Innovation | 12.0 | 4.4 | 1.6 | 19.5 | 11.0 | 48.5 |
| 27 | Forrester’s Interactive Marketing Blog | 12.0 | 4.8 | 10.4 | 16.4 | 4.7 | 48.2 |
| 28 | 451 CAOS Theory | 14.4 | 4.6 | 9.7 | 14.0 | 5.3 | 47.8 |
| 29 | Gartner – Jim Sinur | 12.0 | 3.2 | 5.0 | 11.8 | 15.8 | 47.8 |
| 30 | Music Industry Blog | 12.0 | 3.2 | 4.5 | 12.7 | 15.1 | 47.5 |
| 31 | Enterprise 2.0 Blog | 14.4 | 5.9 | 8.4 | 13.6 | 5.2 | 47.4 |
| 32 | Brandon Hall Analyst Blog – Janet Clarey | 12.0 | 4.7 | 5.0 | 14.2 | 11.3 | 47.2 |
| 33 | Local Onliner | 12.0 | 4.6 | 5.7 | 12.8 | 11.9 | 47.0 |
| 34 | Securosis Blog | 12.0 | 3.6 | 9.5 | 14.2 | 7.7 | 46.9 |
| 35 | Forrester Blog For Information andKM Professionals | 12.0 | 4.7 | 6.8 | 13.4 | 9.4 | 46.2 |
| 36 | Forrester Blog for Consumer Product Strategy Professionals | 12.0 | 3.6 | 9.5 | 10.8 | 10.3 | 46.2 |
| 37 | Gartner – John Pescatore | 12.0 | 3.4 | 6.6 | 11.8 | 12.3 | 46.1 |
| 38 | Business Process and Applications Commentary | 12.0 | 3.8 | 7.8 | 11.1 | 11.2 | 45.9 |
| 39 | Local Media Blog | 12.0 | 4.4 | 8.0 | 14.4 | 6.8 | 45.7 |
| 40 | Always On Real-Time Access | 9.6 | 4.4 | 6.4 | 14.7 | 10.5 | 45.5 |
| 41 | Enterprise Anti-Matter | 12.0 | 3.9 | 4.8 | 12.4 | 12.3 | 45.4 |
| 42 | George F. Colony’s Blog: Counterintuitive | 12.0 | 4.0 | 5.9 | 13.0 | 10.4 | 45.3 |
| 43 | Vendorprisey | 12.0 | 4.7 | 4.5 | 16.4 | 7.7 | 45.2 |
| 44 | VideoNuze | 12.0 | 4.3 | 8.2 | 13.2 | 7.4 | 45.0 |
| 45 | Forrester Product Management Blog | 12.0 | 4.1 | 6.1 | 13.4 | 9.5 | 45.0 |
| 46 | Collaboration and Content Strategies Blog | 12.0 | 2.7 | 7.4 | 12.0 | 10.6 | 44.7 |
| 47 | Gartner – Allen Weiner | 12.0 | 3.0 | 5.3 | 10.4 | 13.7 | 44.4 |
| 48 | ThreatChaos | 9.6 | 4.1 | 6.1 | 13.4 | 11.2 | 44.3 |
| 49 | isen.blog | 14.4 | 5.0 | 5.7 | 7.8 | 11.1 | 44.0 |
| 50 | Market Strategies for IT Suppliers | 9.6 | 3.9 | 4.8 | 9.1 | 16.5 | 43.8 |
| 51 | Application Platform Strategies Blog | 12.0 | 0.0 | 7.3 | 13.1 | 11.4 | 43.8 |
| 52 | Gartner – Andrea Di Maio | 12.0 | 3.0 | 9.3 | 11.4 | 7.4 | 43.2 |
| 53 | Bryan Chapman | 12.0 | 3.8 | 3.2 | 10.9 | 12.8 | 42.7 |
| 54 | Data Center Strategies Blog | 12.0 | 3.0 | 5.9 | 12.3 | 9.4 | 42.5 |
| 55 | Gartner – Nick Jones | 12.0 | 3.7 | 5.3 | 10.6 | 10.9 | 42.4 |
| 56 | Contentblogger | 14.4 | 4.0 | 4.8 | 12.7 | 6.5 | 42.3 |
| 57 | Contentblogger(TM) – News Commentary | 14.4 | 4.0 | 4.8 | 12.7 | 6.5 | 42.3 |
| 58 | ThinkBalm – Immersive Internet Insights and Expertise | 12.0 | 3.4 | 6.9 | 4.3 | 15.5 | 41.9 |
| 59 | Gartner – Jeffrey Mann | 12.0 | 2.3 | 0.0 | 9.9 | 17.4 | 41.5 |
| 60 | tecosystems | 14.4 | 4.2 | 0.0 | 17.0 | 5.8 | 41.4 |
| 61 | Text Technologies | 12.0 | 4.1 | 2.5 | 13.6 | 9.3 | 41.4 |
| 62 | Yankee Group Blog | 12.0 | 3.8 | 5.7 | 12.9 | 7.0 | 41.4 |
| 63 | Gartner – Kristin Moyer | 12.0 | 3.1 | 3.2 | 10.1 | 13.0 | 41.3 |
| 64 | IT Infrastructure and Operations | 12.0 | 4.0 | 4.8 | 11.3 | 9.1 | 41.2 |
| 65 | Web Globalization Blog | 12.0 | 3.9 | 3.2 | 11.3 | 10.6 | 40.9 |
| 66 | New Communications Review | 12.0 | 4.1 | 2.5 | 11.8 | 10.5 | 40.8 |
| 67 | Forrester – The Future Of Agencies Blog | 12.0 | 3.7 | 4.5 | 11.4 | 9.2 | 40.8 |
| 68 | Cutter Blog | 12.0 | 3.5 | 4.8 | 15.9 | 4.6 | 40.7 |
| 69 | Gartner – Tom Bittman | 12.0 | 3.7 | 6.6 | 13.0 | 5.5 | 40.7 |
| 70 | Local Mobile Search | 7.2 | 3.2 | 8.5 | 12.8 | 9.0 | 40.6 |
| 71 | Gartner – Jim Holincheck | 12.0 | 2.2 | 2.5 | 9.6 | 13.9 | 40.2 |
| 72 | Deborah Schultz | 12.0 | 4.0 | 3.7 | 12.4 | 8.0 | 40.1 |
| 73 | Supply Chain Matters | 9.6 | 4.3 | 3.2 | 10.5 | 12.4 | 40.0 |
| 74 | BlogERP – Jim Holincheck’s HCM Software Blog | 12.0 | 3.1 | 2.5 | 11.6 | 10.7 | 39.9 |
| 75 | Gilbane Group Blog | 14.4 | 4.2 | 1.6 | 11.8 | 7.8 | 39.8 |
| 76 | Groundswell | 0.0 | 5.1 | 0.0 | 17.0 | 17.7 | 39.8 |
| 77 | Brandon Hall Analyst Blog – Gary Woodill | 12.0 | 2.8 | 2.5 | 10.5 | 11.9 | 39.7 |
| 78 | Forrester Blog for Customer Intelligence Professionals | 0.0 | 2.5 | 3.2 | 17.9 | 16.1 | 39.7 |
| 79 | Greg’s Storage IO Blog | 9.6 | 3.3 | 3.2 | 11.0 | 12.5 | 39.6 |
| 80 | Global Watchtower | 12.0 | 3.9 | 5.9 | 12.6 | 5.1 | 39.5 |
| 81 | Gartner – Neil MacDonald | 12.0 | 2.9 | 5.0 | 10.3 | 9.2 | 39.4 |
| 82 | Gartner – Thomas Otter | 12.0 | 3.1 | 2.5 | 10.5 | 11.0 | 39.1 |
| 83 | VisionMobile blog | 12.0 | 3.8 | 6.1 | 12.5 | 4.7 | 39.1 |
| 84 | Analytics Evolution | 9.6 | 3.3 | 1.6 | 10.0 | 14.6 | 39.1 |
| 85 | Gartner – Ray Valdes | 12.0 | 2.0 | 0.0 | 9.9 | 15.1 | 39.0 |
| 86 | HDTV Almanac | 9.6 | 6.0 | 10.5 | 6.9 | 6.0 | 39.0 |
| 87 | Gartner – Mark McDonald | 12.0 | 2.4 | 4.1 | 9.5 | 10.9 | 38.9 |
| 88 | The Enterprise System Spectator | 12.0 | 4.5 | 4.5 | 12.2 | 5.5 | 38.8 |
| 89 | BuddeBlog | 12.0 | 3.6 | 2.5 | 8.9 | 11.6 | 38.6 |
| 90 | Gartner – Greg Young | 12.0 | 2.6 | 3.2 | 11.2 | 9.4 | 38.4 |
| 91 | Gartner – Kathy Harris | 12.0 | 2.2 | 1.6 | 9.7 | 12.9 | 38.4 |
| 92 | Travel Technology | 9.6 | 4.0 | 0.0 | 13.0 | 11.7 | 38.2 |
| 93 | IT Blog Watch | 14.4 | 5.0 | 0.0 | 12.4 | 6.1 | 37.9 |
| 94 | Gartner Blog by Mike McGuire | 12.0 | 2.1 | 1.6 | 9.2 | 12.9 | 37.8 |
| 95 | The Future of Enterprise Software | 12.0 | 4.1 | 3.2 | 9.5 | 8.9 | 37.6 |
| 96 | View from Forrester | 16.8 | 3.8 | 5.0 | 7.1 | 4.8 | 37.5 |
| 97 | BriefingsDirect Transcripts | 12.0 | 3.9 | 8.7 | 8.1 | 4.9 | 37.5 |
| 98 | Gartner – French Caldwell | 12.0 | 1.9 | 2.5 | 8.8 | 12.2 | 37.4 |
| 99 | 451 Take on information management, Too much information | 14.4 | 3.4 | 1.6 | 13.1 | 4.9 | 37.3 |
| 100 | Javelin Strategy and Research | 14.4 | 3.6 | 0.0 | 13.6 | 5.7 | 37.3 |
| 101 | Forrester: Application Dev & Prog Man. Profs | 12.0 | 3.7 | 4.8 | 9.7 | 7.2 | 37.3 |
| 102 | Judith Hurwitz’ Weblog | 9.6 | 3.5 | 0.0 | 12.5 | 11.6 | 37.2 |
| 103 | Gartner – Mark Driver | 12.0 | 2.1 | 0.0 | 10.0 | 12.9 | 37.0 |
| 104 | Gartner – Lydia Leong | 12.0 | 3.3 | 3.2 | 10.7 | 7.6 | 36.8 |
| 105 | Teblog | 9.6 | 4.2 | 0.0 | 9.9 | 13.2 | 36.8 |
| 106 | Gartner – Anthony Bradley | 12.0 | 2.5 | 4.1 | 11.2 | 6.8 | 36.6 |
| 107 | Opus Research | 9.6 | 2.1 | 4.5 | 7.5 | 13.0 | 36.6 |
| 108 | NPD Group Blog | 14.4 | 3.7 | 4.1 | 10.4 | 4.1 | 36.6 |
| 109 | Security and Risk Management Strategies Blog | 12.0 | 0.0 | 3.7 | 11.2 | 9.7 | 36.5 |
| 110 | The Guidewire | 12.0 | 3.5 | 1.6 | 10.3 | 9.0 | 36.4 |
| 111 | Kelsey Group Blogs | 12.0 | 0.0 | 1.6 | 14.3 | 8.5 | 36.4 |
| 112 | Spire Security Viewpoint | 12.0 | 3.5 | 2.5 | 14.3 | 4.0 | 36.3 |
| 113 | The Brampton Factor | 14.4 | 1.0 | 0.0 | 18.2 | 2.8 | 36.3 |
| 114 | Tech – Surf – Blog | 9.6 | 3.8 | 6.2 | 10.6 | 6.0 | 36.2 |
| 115 | The Hot Aisle | 9.6 | 4.6 | 2.5 | 11.0 | 8.5 | 36.2 |
| 116 | Gartner – Whit Andrews | 12.0 | 3.2 | 1.6 | 10.2 | 9.2 | 36.1 |
| 117 | The Outsourcing Blog Horses for Sources | 14.4 | 5.0 | 0.0 | 11.5 | 5.3 | 36.0 |
| 118 | Peter O’Kelly’s Reality Check | 12.0 | 4.5 | 0.0 | 11.4 | 8.1 | 36.0 |
| 119 | Gartner – Jim Lundy | 12.0 | 1.9 | 0.0 | 8.8 | 13.3 | 36.0 |
| 120 | Altimeter Group | 0.0 | 3.0 | 6.9 | 13.7 | 12.3 | 35.9 |
| 121 | Gartner – Tom Austin | 12.0 | 1.8 | 2.5 | 9.4 | 10.1 | 35.8 |
| 122 | Gartner – Mark Raskino | 12.0 | 1.9 | 0.0 | 9.1 | 12.6 | 35.6 |
| 123 | Forrester Blog For Enterprise Architecture Professionals | 12.0 | 2.8 | 2.5 | 10.0 | 8.3 | 35.5 |
| 124 | Gartner – Jeff Roster | 12.0 | 2.1 | 0.0 | 9.2 | 12.2 | 35.4 |
| 125 | Out of the Box | 7.2 | 4.0 | 0.0 | 9.6 | 14.6 | 35.4 |
| 126 | DisplaySearch Blog | 12.0 | 3.7 | 3.7 | 11.2 | 4.6 | 35.2 |
| 127 | THINK IT Services | 12.0 | 3.8 | 3.7 | 9.7 | 5.9 | 35.0 |
| 128 | kirkk.com | 7.2 | 2.9 | 7.3 | 13.3 | 4.1 | 34.8 |
| 129 | Parks Associates | 12.0 | 4.0 | 0.0 | 12.6 | 6.3 | 34.8 |
| 130 | Pattern Finder | 9.6 | 3.8 | 1.6 | 10.4 | 9.4 | 34.8 |
| 131 | Health Content Advisors | 9.6 | 2.4 | 5.3 | 8.5 | 8.7 | 34.4 |
| 132 | Gartner – Andrew White | 12.0 | 1.8 | 1.6 | 10.5 | 8.5 | 34.4 |
| 133 | Forrester: eBusiness & Channel Strategy Pros | 12.0 | 3.2 | 4.8 | 9.8 | 4.5 | 34.3 |
| 134 | Ron Shevlin’s Marketing Whims | 12.0 | 4.5 | 0.0 | 15.1 | 2.6 | 34.2 |
| 135 | Gartner – Brian Prentice | 12.0 | 2.4 | 6.1 | 9.7 | 4.0 | 34.1 |
| 136 | The Pervasive Datacenter | 14.4 | 2.5 | 0.0 | 10.5 | 6.6 | 34.0 |
| 137 | Gartner – Michael Maoz | 12.0 | 4.2 | 1.6 | 0.0 | 16.0 | 33.8 |
| 138 | Gil Yehuda’s Enterprise 2.0 Blog | 7.2 | 4.1 | 6.4 | 3.3 | 12.9 | 33.8 |
| 139 | Z Trek – The Alan Zeichick Weblog | 9.6 | 3.9 | 3.7 | 10.9 | 5.7 | 33.8 |
| 140 | The TEC Blog | 9.6 | 3.5 | 3.7 | 10.9 | 6.1 | 33.8 |
| 141 | Enterprise Search Blog | 14.4 | 4.0 | 0.0 | 10.6 | 4.7 | 33.8 |
| 142 | Gartner – Nick Gall | 12.0 | 2.4 | 0.0 | 10.6 | 8.7 | 33.7 |
| 143 | Jon Arnold’s Blog | 12.0 | 4.7 | 3.7 | 7.4 | 5.9 | 33.6 |
| 144 | All Aboard | 12.0 | 2.8 | 0.0 | 12.2 | 6.6 | 33.6 |
| 145 | Business Continuity – Pandemic Threat | 14.4 | 4.1 | 1.6 | 7.9 | 5.6 | 33.5 |
| 146 | James Kobielus’ Blog | 12.0 | 3.6 | 5.0 | 8.2 | 4.3 | 33.2 |
| 147 | Enterprise Mobility Matters | 9.6 | 3.8 | 5.7 | 9.0 | 4.7 | 32.9 |
| 148 | Security and Risk Management | 12.0 | 4.0 | 0.0 | 11.3 | 5.5 | 32.8 |
| 149 | Gartner – Frank Kenney | 12.0 | 2.9 | 0.0 | 10.4 | 7.5 | 32.7 |
| 150 | Analyst Xpress | 12.0 | 2.5 | 3.2 | 10.8 | 4.3 | 32.7 |
| 151 | Michael Fauscette | 9.6 | 3.5 | 2.5 | 7.1 | 10.0 | 32.7 |
| 152 | Laurie McCabe’s Blog | 9.6 | 3.2 | 2.5 | 6.7 | 10.5 | 32.6 |
| 153 | Plausible Deniability | 12.0 | 3.3 | 2.5 | 11.4 | 3.4 | 32.6 |
| 154 | Supernova Hub | 12.0 | 4.3 | 7.1 | 3.8 | 5.3 | 32.5 |
| 155 | Osterman Research Blog | 9.6 | 3.9 | 0.0 | 10.0 | 8.8 | 32.4 |
| 156 | Richi Blog | 7.2 | 4.0 | 0.0 | 12.2 | 8.9 | 32.2 |
| 157 | Executive Advisory Blog | 12.0 | 2.6 | 2.5 | 8.0 | 6.8 | 32.0 |
| 158 | Corporate Integrity, LLC | 12.0 | 3.6 | 3.2 | 9.7 | 3.3 | 31.8 |
| 159 | The Real Truth about Technology and IT | 9.6 | 2.3 | 4.1 | 9.0 | 6.6 | 31.6 |
| 160 | Ceci N’est Pas Un Bob | 12.0 | 4.0 | 2.5 | 11.1 | 1.8 | 31.4 |
| 161 | IDEAS Insights | 9.6 | 2.9 | 5.0 | 8.8 | 4.8 | 31.1 |
| 162 | Gartner – Andrew Frank | 12.0 | 2.8 | 2.5 | 10.6 | 3.1 | 31.1 |
| 163 | KnowledgeForward | 7.2 | 2.9 | 4.8 | 11.1 | 5.1 | 31.0 |
| 164 | Karen Hobert’s Connecting Dots | 12.0 | 3.8 | 3.7 | 7.6 | 3.9 | 30.9 |
| 165 | Forrester: Sourcing and Vendor Management Pros | 12.0 | 3.5 | 0.0 | 8.2 | 7.2 | 30.9 |
| 166 | Werblog | 14.4 | 4.8 | 0.0 | 11.6 | 0.0 | 30.8 |
| 167 | Gartner – Daryl Plummer | 12.0 | 3.7 | 0.0 | 12.6 | 2.5 | 30.8 |
| 168 | XML Technologies and Content Strategies | 12.0 | 2.6 | 3.2 | 10.5 | 2.4 | 30.7 |
| 169 | Gartner – David M. Smith | 12.0 | 2.1 | 0.0 | 8.3 | 8.1 | 30.6 |
| 170 | Gartner – Cameron Haight | 12.0 | 2.8 | 0.0 | 9.9 | 5.9 | 30.6 |
| 171 | Supply Chain Reaction | 12.0 | 3.8 | 2.5 | 6.4 | 5.8 | 30.5 |
| 172 | Brandon Hall Analyst Blog – Richard Nantel | 12.0 | 3.8 | 0.0 | 11.1 | 3.6 | 30.5 |
| 173 | Forrester Blog for IT Leaders in Asia Pacific | 12.0 | 2.5 | 0.0 | 8.2 | 7.5 | 30.2 |
| 174 | Attic Dust | 12.0 | 0.0 | 4.8 | 3.8 | 9.6 | 30.2 |
| 175 | Robin Bloor’s Blog: have Mac will blog | 9.6 | 3.2 | 0.0 | 10.5 | 6.8 | 30.0 |
| 176 | Gartner – Debbie Wilson | 12.0 | 3.8 | 0.0 | 10.0 | 4.2 | 30.0 |
| 177 | Irwin Lazar’s Real-time Blog | 12.0 | 4.3 | 1.6 | 7.7 | 4.2 | 29.9 |
| 178 | Gartner – Scott Nelson | 12.0 | 2.0 | 0.0 | 3.8 | 11.8 | 29.7 |
| 179 | Ferris Research | 9.6 | 3.4 | 0.0 | 9.5 | 7.1 | 29.5 |
| 180 | Richard Nantel | 12.0 | 3.8 | 0.0 | 11.1 | 2.6 | 29.5 |
| 181 | BriefingsDirect | 12.0 | 4.1 | 8.4 | 0.0 | 4.7 | 29.2 |
| 182 | Click | 12.0 | 3.1 | 3.2 | 10.0 | 1.0 | 29.2 |
| 183 | Consider the Source | 12.0 | 3.5 | 1.6 | 7.4 | 4.8 | 29.2 |
| 184 | Globalization Blog | 12.0 | 3.7 | 0.0 | 9.1 | 4.4 | 29.2 |
| 185 | Unified-View | 12.0 | 4.3 | 0.0 | 8.7 | 3.8 | 28.7 |
| 186 | Brandon Hall Analyst Blog – Tom Werner | 12.0 | 2.8 | 0.0 | 7.9 | 6.0 | 28.6 |
| 187 | Unified Communications Strategies | 12.0 | 3.2 | 0.0 | 9.2 | 4.1 | 28.4 |
| 188 | RedMonk Radio Podcast | 12.0 | 2.6 | 0.0 | 8.7 | 5.1 | 28.4 |
| 189 | INPUT Blog | 9.6 | 1.8 | 0.0 | 9.1 | 7.9 | 28.3 |
| 190 | Forrester Blog For CIOs | 12.0 | 2.7 | 0.0 | 10.2 | 3.3 | 28.1 |
| 191 | Blog Mike Ferguson | 9.6 | 4.2 | 4.1 | 3.3 | 6.9 | 28.0 |
| 192 | Network and Telecom Strategies Blog | 12.0 | 2.0 | 0.0 | 8.4 | 5.5 | 27.9 |
| 193 | Forrester Blog For Consumer Market Research Professionals | 0.0 | 2.5 | 5.7 | 8.2 | 11.4 | 27.9 |
| 194 | Fuld’s Competitive Musings | 12.0 | 3.0 | 1.6 | 9.5 | 1.8 | 27.8 |
| 195 | Amy Wohl’s Opinions | 9.6 | 3.8 | 0.0 | 10.7 | 3.6 | 27.7 |
| 196 | The Monash Report | 12.0 | 3.8 | 0.0 | 9.4 | 2.4 | 27.6 |
| 197 | Nucleus Research | 14.4 | 2.3 | 0.0 | 7.5 | 3.4 | 27.6 |
| 198 | Fern Halper’s data makes the world go round | 9.6 | 3.2 | 1.6 | 10.2 | 2.9 | 27.5 |
| 199 | Gartner – David McCoy | 12.0 | 2.3 | 0.0 | 10.0 | 3.3 | 27.5 |
| 200 | Gartner – Wes Rishel | 12.0 | 2.4 | 0.0 | 9.5 | 3.5 | 27.4 |
| 201 | Amy Wohl’s Opinions on SaaS | 12.0 | 3.8 | 0.0 | 0.0 | 11.5 | 27.3 |
| 202 | Celent Banking Blog | 9.6 | 2.3 | 0.0 | 10.5 | 4.7 | 27.1 |
| 203 | E-Communications and Community | 12.0 | 3.7 | 0.0 | 8.1 | 3.3 | 27.1 |
| 204 | Binstock on Software | 12.0 | 0.0 | 0.0 | 13.0 | 2.0 | 27.0 |
| 205 | CCS Insight Blog | 7.2 | 2.6 | 0.0 | 10.1 | 7.0 | 26.9 |
| 206 | Lux Populi | 12.0 | 1.2 | 0.0 | 8.4 | 5.3 | 26.9 |
| 207 | Thinking Global | 12.0 | 3.4 | 0.0 | 7.2 | 4.1 | 26.7 |
| 208 | Forrester Research – Customer Experience in Japan | 12.0 | 3.3 | 0.0 | 9.9 | 1.4 | 26.6 |
| 209 | Ironick | 9.6 | 3.6 | 0.0 | 9.3 | 3.9 | 26.4 |
| 210 | Lower (Carbon) Footprint | 0.0 | 2.8 | 0.0 | 22.2 | 1.4 | 26.3 |
| 211 | Gartner – Dan Sholler | 12.0 | 2.0 | 0.0 | 6.4 | 5.8 | 26.1 |
| 212 | elemental links | 7.2 | 3.8 | 2.5 | 9.1 | 3.5 | 26.1 |
| 213 | First Thing Monday | 12.0 | 3.5 | 0.0 | 9.5 | 0.8 | 25.7 |
| 214 | Gartner – Toby Bell | 12.0 | 2.0 | 0.0 | 9.4 | 2.2 | 25.6 |
| 215 | Data Management Strategies | 12.0 | 2.6 | 0.0 | 6.7 | 4.1 | 25.4 |
| 216 | Strategic Messaging | 12.0 | 3.7 | 0.0 | 7.7 | 1.9 | 25.4 |
| 217 | The Geo Factor | 12.0 | 3.7 | 0.0 | 9.7 | 0.0 | 25.3 |
| 218 | Gartner – Gene Alvarez | 12.0 | 1.7 | 0.0 | 8.9 | 2.7 | 25.3 |
| 219 | TelcoTV-View | 9.6 | 2.4 | 0.0 | 11.2 | 2.0 | 25.3 |
| 220 | Gartner – Adam Hils | 12.0 | 1.8 | 0.0 | 6.4 | 5.0 | 25.2 |
| 221 | Adam’s Heart Valve Surgery Blog | 7.2 | 3.7 | 4.5 | 2.6 | 7.0 | 25.0 |
| 222 | Gartner – Eric Goodness | 12.0 | 1.7 | 0.0 | 9.6 | 1.7 | 24.9 |
| 223 | Gilbane Events Blog | 12.0 | 2.3 | 0.0 | 6.4 | 4.2 | 24.9 |
| 224 | Home Theater View | 7.2 | 3.6 | 10.5 | 0.0 | 3.7 | 24.9 |
| 225 | eurotechnology.japan.blog | 9.6 | 3.8 | 0.0 | 9.4 | 2.2 | 24.9 |
| 226 | Software Memories | 12.0 | 3.7 | 0.0 | 7.4 | 1.7 | 24.7 |
| 227 | Mostly Enterprise Architecture | 7.2 | 2.4 | 0.0 | 4.9 | 10.1 | 24.7 |
| 228 | Connections | 9.6 | 3.8 | 0.0 | 6.7 | 4.5 | 24.6 |
| 229 | IT Depends | 9.6 | 3.5 | 0.0 | 3.3 | 8.1 | 24.6 |
| 230 | Gartner – Brian Gammage | 12.0 | 1.7 | 1.6 | 4.6 | 4.6 | 24.5 |
| 231 | Gartner – Dave Cappuccio | 12.0 | 2.6 | 0.0 | 7.0 | 2.8 | 24.5 |
| 232 | Insecure about Security | 9.6 | 3.8 | 0.0 | 7.1 | 3.9 | 24.4 |
| 233 | comScore Voices | 16.8 | 3.8 | 0.0 | 0.0 | 3.9 | 24.4 |
| 234 | doingITbetter | 9.6 | 4.0 | 0.0 | 8.8 | 2.0 | 24.4 |
| 235 | Gartner – Roberta Witty | 12.0 | 2.0 | 0.0 | 6.4 | 3.8 | 24.2 |
| 236 | MacehiterWard-Dutton | 9.6 | 4.1 | 1.6 | 3.8 | 4.9 | 24.0 |
| 237 | Celent Insurance Blog | 9.6 | 3.2 | 0.0 | 7.6 | 3.7 | 24.0 |
| 238 | Freeform Comment | 9.6 | 3.5 | 0.0 | 8.4 | 2.5 | 23.9 |
| 239 | Content Nation | 9.6 | 2.2 | 0.0 | 7.7 | 4.3 | 23.8 |
| 240 | The InfoCommerce Blog | 9.6 | 3.8 | 0.0 | 7.2 | 3.1 | 23.7 |
| 241 | NanoMarkets TOP Blog | 9.6 | 3.6 | 0.0 | 9.3 | 1.2 | 23.6 |
| 242 | fasol.blog | 9.6 | 2.9 | 0.0 | 9.1 | 1.9 | 23.4 |
| 243 | Gartner – David Norton | 12.0 | 1.7 | 0.0 | 6.6 | 2.8 | 23.1 |
| 244 | Gartner – Eric Knipp | 12.0 | 2.0 | 0.0 | 5.7 | 3.3 | 23.0 |
| 245 | Gartner – Debra Logan | 12.0 | 2.1 | 0.0 | 7.5 | 1.3 | 22.8 |
| 246 | Tom Raftery’s Social Media | 9.6 | 2.7 | 0.0 | 0.0 | 10.5 | 22.8 |
| 247 | Gartner – Richard Fouts | 12.0 | 1.8 | 0.0 | 5.7 | 3.2 | 22.7 |
| 248 | Cote’s Weblog | 12.0 | 3.2 | 0.0 | 1.6 | 5.9 | 22.7 |
| 249 | billtrippe | 12.0 | 0.0 | 0.0 | 6.4 | 4.2 | 22.6 |
| 250 | The Bourne Report | 9.6 | 3.0 | 0.0 | 7.7 | 2.1 | 22.4 |
| 251 | Gartner – Bruce Robertson | 12.0 | 1.6 | 1.6 | 4.6 | 2.5 | 22.3 |
| 252 | Gartner – Benoit Lheureux | 12.0 | 1.6 | 0.0 | 5.5 | 3.2 | 22.3 |
| 253 | NewMediaWise | 9.6 | 3.4 | 0.0 | 9.2 | 0.0 | 22.1 |
| 254 | Leadership Drives Business | 0.0 | 2.9 | 0.0 | 12.2 | 7.0 | 22.1 |
| 255 | IT BULLETins | 12.0 | 3.9 | 0.0 | 4.6 | 1.5 | 22.0 |
| 256 | Beagle Research | 12.0 | 0.0 | 0.0 | 9.9 | 0.0 | 21.9 |
| 257 | The Business of Talent | 0.0 | 2.9 | 0.0 | 12.2 | 6.8 | 21.9 |
| 258 | Berlecon Analyst Weblog | 12.0 | 0.0 | 0.0 | 7.2 | 2.7 | 21.9 |
| 259 | IT Services and Outsourcing | 12.0 | 2.5 | 0.0 | 7.4 | 0.0 | 21.8 |
| 260 | Gartner – Carol Rozwell | 12.0 | 1.6 | 0.0 | 5.2 | 3.0 | 21.8 |
| 261 | TeleGeography News and Analysis | 14.4 | 2.6 | 0.0 | 2.6 | 2.0 | 21.7 |
| 262 | Andy on Enterprise Software | 9.6 | 2.7 | 0.0 | 6.7 | 2.6 | 21.6 |
| 263 | Pike Research Blog | 9.6 | 1.6 | 0.0 | 4.9 | 5.3 | 21.5 |
| 264 | Localization Industry 411 | 7.2 | 3.4 | 0.0 | 10.0 | 0.9 | 21.5 |
| 265 | Optimal Friction | 7.2 | 3.2 | 0.0 | 7.1 | 3.4 | 20.9 |
| 266 | Gartner – Donna Fitzgerald | 12.0 | 1.9 | 0.0 | 3.8 | 3.2 | 20.8 |
| 267 | Gartner – Michael Blechar | 12.0 | 1.8 | 0.0 | 5.5 | 1.4 | 20.7 |
| 268 | Blogging at Zinnov | 4.8 | 0.5 | 0.0 | 7.0 | 8.4 | 20.7 |
| 269 | Liquefying IT | 12.0 | 3.8 | 0.0 | 0.0 | 4.9 | 20.7 |
| 270 | iLocus | 7.2 | 3.2 | 0.0 | 8.3 | 1.7 | 20.5 |
| 271 | Gartner Voice | 14.4 | 2.4 | 0.0 | 0.0 | 3.5 | 20.3 |
| 272 | Contentblogger(TM) – Industry Events | 9.6 | 1.9 | 0.0 | 7.7 | 0.9 | 20.1 |
| 273 | Got Tannins? | 9.6 | 4.1 | 0.0 | 4.9 | 1.5 | 20.0 |
| 274 | Thinking Out Loud | 12.0 | 2.5 | 0.0 | 0.0 | 5.5 | 19.9 |
| 275 | Gartner – Phillip Redman | 12.0 | 1.8 | 0.0 | 3.3 | 2.7 | 19.8 |
| 276 | Chipworks Blog | 9.6 | 2.9 | 1.6 | 0.0 | 5.6 | 19.7 |
| 277 | Security Architect | 9.6 | 2.7 | 0.0 | 4.6 | 2.7 | 19.6 |
| 278 | what’s next? | 9.6 | 2.8 | 0.0 | 4.6 | 2.5 | 19.5 |
| 279 | Gartner – Van Baker | 12.0 | 1.7 | 0.0 | 3.3 | 2.5 | 19.4 |
| 280 | Thus Prate the IT Pundit | 7.2 | 3.2 | 0.0 | 6.4 | 2.6 | 19.4 |
| 281 | Open Reasoning | 9.6 | 2.3 | 0.0 | 4.9 | 2.5 | 19.3 |
| 282 | Technology Marketing Blog | 7.2 | 3.0 | 0.0 | 6.1 | 3.0 | 19.3 |
| 283 | Forrester Blog for Technology Sales Enablement Professionals | 0.0 | 2.1 | 3.2 | 5.7 | 8.3 | 19.3 |
| 284 | John Katsaros | 7.2 | 0.7 | 0.0 | 6.7 | 4.5 | 19.2 |
| 285 | Joel Orr’s World | 7.2 | 0.7 | 0.0 | 6.7 | 4.5 | 19.2 |
| 286 | Techaisle | 7.2 | 1.9 | 2.5 | 4.3 | 3.2 | 19.1 |
| 287 | The Bigger Truth | 0.0 | 2.2 | 0.0 | 11.2 | 5.5 | 18.9 |
| 288 | Gartner – Rob DeSisto | 12.0 | 1.6 | 0.0 | 1.6 | 3.6 | 18.8 |
| 289 | The Future of Publishing | 9.6 | 3.2 | 2.5 | 0.0 | 3.5 | 18.8 |
| 290 | Gartner – Brian Burke | 12.0 | 1.7 | 0.0 | 3.8 | 1.2 | 18.7 |
| 291 | Total Immersion | 7.2 | 2.8 | 0.0 | 7.7 | 0.9 | 18.6 |
| 292 | Mark My Words | 9.6 | 3.5 | 0.0 | 0.0 | 5.4 | 18.5 |
| 293 | No Jitter Weblog – Melanie Turek | 12.0 | 1.9 | 0.0 | 0.0 | 4.6 | 18.5 |
| 294 | No Jitter Weblog – Michael Finneran | 12.0 | 1.8 | 0.0 | 0.0 | 4.6 | 18.4 |
| 295 | Global Trends and Benchmarks | 0.0 | 1.0 | 0.0 | 12.2 | 5.3 | 18.4 |
| 296 | No Jitter Weblog – Irwin Lazar | 12.0 | 1.4 | 0.0 | 0.0 | 4.8 | 18.2 |
| 297 | No Jitter Weblog – Zeus Kerravala | 12.0 | 2.6 | 0.0 | 0.0 | 3.5 | 18.1 |
| 298 | Identerati | 9.6 | 2.4 | 0.0 | 6.1 | 0.0 | 18.0 |
| 299 | The Technology Garden | 7.2 | 2.2 | 0.0 | 8.6 | 0.0 | 17.9 |
| 300 | Steve’s IT Rants | 4.8 | 0.6 | 0.0 | 12.5 | 0.0 | 17.9 |
| 301 | Geosophical technologies | 7.2 | 2.6 | 0.0 | 6.4 | 1.7 | 17.9 |
| 302 | Heavy Lifting Analyst Notes | 12.0 | 1.8 | 0.0 | 0.0 | 4.0 | 17.8 |
| 303 | Jon Peddie Blogs | 9.6 | 1.1 | 0.0 | 3.8 | 3.2 | 17.7 |
| 304 | JPR Staff Blogs | 9.6 | 1.1 | 0.0 | 3.8 | 3.2 | 17.7 |
| 305 | No Jitter Weblog – Sheila McGee-Smith | 12.0 | 1.2 | 0.0 | 0.0 | 4.5 | 17.6 |
| 306 | Burton Group Inflection Point | 7.2 | 3.5 | 0.0 | 4.3 | 2.6 | 17.6 |
| 307 | Craig Mathias’s Blog | 0.0 | 3.6 | 0.0 | 9.1 | 4.9 | 17.6 |
| 308 | ABI Research Analyst Blogs | 12.0 | 1.7 | 0.0 | 0.0 | 3.8 | 17.5 |
| 309 | Learning on the Leading Edge | 0.0 | 0.0 | 0.0 | 12.2 | 5.3 | 17.5 |
| 310 | Mobile Insight and Search | 7.2 | 3.3 | 0.0 | 6.6 | 0.0 | 17.1 |
| 311 | No Jitter Weblog – Tom Nolle | 12.0 | 1.0 | 0.0 | 0.0 | 4.1 | 17.0 |
| 312 | Gene Phifer’s Personal Blog | 7.2 | 1.2 | 0.0 | 8.7 | 0.0 | 17.0 |
| 313 | Nothing to Declare | 4.8 | 3.5 | 0.0 | 6.4 | 2.2 | 16.9 |
| 314 | bit blue blog | 7.2 | 3.3 | 0.0 | 6.4 | 0.0 | 16.9 |
| 315 | Gartner – Frank Ridder | 12.0 | 1.6 | 0.0 | 0.0 | 3.3 | 16.9 |
| 316 | No Jitter Weblog – Brian Riggs | 12.0 | 1.1 | 0.0 | 0.0 | 3.6 | 16.6 |
| 317 | Keeping IT Grounded | 9.6 | 1.7 | 0.0 | 5.2 | 0.0 | 16.5 |
| 318 | Connecting the Dots | 0.0 | 0.0 | 0.0 | 7.8 | 8.5 | 16.3 |
| 319 | BPMS Watch | 12.0 | 0.0 | 0.0 | 0.0 | 4.3 | 16.3 |
| 320 | Communication Innovations | 12.0 | 3.2 | 0.0 | 0.0 | 0.9 | 16.1 |
| 321 | Gap Intelligence | 4.8 | 2.7 | 0.0 | 0.0 | 8.6 | 16.1 |
| 322 | Peter Christy | 7.2 | 1.8 | 0.0 | 4.6 | 2.4 | 16.0 |
| 323 | Jen McClure’s Ruminations | 9.6 | 1.3 | 0.0 | 4.3 | 0.8 | 16.0 |
| 324 | Gartner – Tole Hart | 12.0 | 1.8 | 0.0 | 0.0 | 2.2 | 16.0 |
| 325 | Gartner – Martin Reynolds | 12.0 | 1.7 | 0.0 | 0.0 | 2.0 | 15.7 |
| 326 | Gartner – Earl Perkins | 0.0 | 1.9 | 1.6 | 8.0 | 3.8 | 15.3 |
| 327 | Gilbane Publishing Technology Blog | 14.4 | 0.0 | 0.0 | 0.0 | 0.8 | 15.2 |
| 328 | The Analyst View | 9.6 | 2.0 | 0.0 | 0.0 | 3.6 | 15.1 |
| 329 | Shosteck Group Insights | 9.6 | 1.0 | 0.0 | 3.3 | 1.0 | 14.9 |
| 330 | Technology Pundits – Rob Enderle | 9.6 | 3.3 | 0.0 | 0.0 | 1.9 | 14.7 |
| 331 | Gartner – Donald Feinberg | 9.6 | 1.6 | 0.0 | 0.0 | 3.5 | 14.7 |
| 332 | The Saltworks | 7.2 | 1.5 | 0.0 | 3.3 | 2.2 | 14.2 |
| 333 | Compass Intelligence | 7.2 | 3.5 | 0.0 | 0.0 | 3.3 | 13.9 |
| 334 | Wicked Flavory | 4.8 | 2.2 | 0.0 | 6.9 | 0.0 | 13.9 |
| 335 | Marcia Kaufman’s Weblog | 9.6 | 1.1 | 0.0 | 3.3 | -0.2 | 13.7 |
| 336 | On Target Embedded Systems | 7.2 | 3.1 | 0.0 | 0.0 | 3.4 | 13.7 |
| 337 | Rabkin’s ROI | 0.0 | 1.5 | 0.0 | 3.8 | 8.3 | 13.6 |
| 338 | Forrester Blog for B2B Market Research Professionals | 0.0 | 2.3 | 0.0 | 5.2 | 6.0 | 13.5 |
| 339 | Foro Empresarial | 0.0 | 2.6 | 0.0 | 5.9 | 4.9 | 13.4 |
| 340 | joygantic | 4.8 | 2.3 | 0.0 | 5.5 | 0.8 | 13.4 |
| 341 | Andreas Antonopoulos’s blog | 9.6 | 3.0 | 0.0 | 0.0 | 0.7 | 13.3 |
| 342 | WirelessView | 7.2 | 1.1 | 0.0 | 4.9 | 0.0 | 13.2 |
| 343 | IMHO | 0.0 | 0.5 | 0.0 | 8.9 | 3.7 | 13.1 |
| 344 | GigaOM Pro Blog | 0.0 | 0.3 | 0.0 | 5.9 | 6.9 | 13.1 |
| 345 | Innovating Government | 0.0 | 3.2 | 0.0 | 8.7 | 1.1 | 13.0 |
| 346 | Commvine | 2.4 | 1.2 | 0.0 | 6.4 | 2.9 | 12.9 |
| 347 | On Taget: Embedded Systems | 0.0 | 0.0 | 0.0 | 7.6 | 5.3 | 12.9 |
| 348 | TV Strategies | 4.8 | 2.8 | 0.0 | 5.2 | 0.0 | 12.8 |
| 349 | Burton Group Weblog | 9.6 | 3.2 | 0.0 | 0.0 | 0.0 | 12.7 |
| 350 | The Collaboration Blog | 7.2 | 3.1 | 0.0 | 0.0 | 2.4 | 12.7 |
| 351 | Chip Hatchery | 7.2 | 1.1 | 0.0 | 0.0 | 4.4 | 12.6 |
| 352 | Technology Pundits – Richard Doherty | 7.2 | 3.3 | 0.0 | 0.0 | 2.0 | 12.5 |
| 353 | iGR Weekly Blog | 0.0 | 1.6 | 0.0 | 9.5 | 1.3 | 12.4 |
| 354 | The Naked Chief Blog | 7.2 | 0.5 | 0.0 | 1.6 | 3.0 | 12.3 |
| 355 | The Innovation Zone | 9.6 | 1.1 | 0.0 | 0.0 | 1.4 | 12.1 |
| 356 | Cannell.org | 0.0 | 3.4 | 0.0 | 4.6 | 3.9 | 12.0 |
| 357 | Technology Pundits – Tim Bajarin | 7.2 | 3.3 | 0.0 | 0.0 | 1.5 | 12.0 |
| 358 | Open Source Unleashed – All Bets Off | 9.6 | 0.0 | 0.0 | 0.0 | 2.3 | 11.9 |
| 359 | MavBlog | 7.2 | 0.6 | 0.0 | 1.6 | 2.0 | 11.5 |
| 360 | Ted Ritter’s blog | 9.6 | 0.3 | 0.0 | 0.0 | 1.6 | 11.5 |
| 361 | Sageza Says | 0.0 | 1.2 | 0.0 | 5.9 | 4.1 | 11.3 |
| 362 | Digital Consumer | 0.0 | 2.0 | 0.0 | 4.6 | 4.6 | 11.2 |
| 363 | Strategy Analytisc – Digital Consumer | 0.0 | 2.0 | 0.0 | 4.6 | 4.3 | 10.9 |
| 364 | Enterprise Advocates | 0.0 | 3.5 | 3.2 | 0.0 | 4.0 | 10.7 |
| 365 | Jeff and Hennie’s Stuff | 0.0 | 1.8 | 0.0 | 7.7 | 0.9 | 10.5 |
| 366 | Retail PLM and Sourcing | 4.8 | 0.0 | 0.0 | 1.6 | 4.1 | 10.5 |
| 367 | Ben’s Tech Blog | 0.0 | 0.0 | 0.0 | 6.1 | 4.3 | 10.4 |
| 368 | NRG TechView research and analysis | 7.2 | 1.6 | 0.0 | 0.0 | 1.5 | 10.3 |
| 369 | Johna Till Johnson’s blog | 0.0 | 0.0 | 0.0 | 4.9 | 5.3 | 10.3 |
| 370 | Lopez Research Blog | 7.2 | 1.2 | 0.0 | 0.0 | 1.8 | 10.2 |
| 371 | John Burke’s blog | 9.6 | 0.0 | 0.0 | 0.0 | 0.0 | 9.6 |
| 372 | Digital Media Bulletin | 0.0 | 2.6 | 0.0 | 5.7 | 1.1 | 9.4 |
| 373 | A Springboard to Services | 7.2 | 1.0 | 0.0 | 0.0 | 1.1 | 9.2 |
| 374 | alvear.com | 4.8 | 1.7 | 0.0 | 0.0 | 2.7 | 9.1 |
| 375 | DVR Bulletin | 7.2 | 1.8 | 0.0 | 0.0 | 0.0 | 9.0 |
| 376 | Views from the Bridge | 0.0 | 0.0 | 0.0 | 5.2 | 3.2 | 8.5 |
| 377 | Collaboration service news | 0.0 | 0.5 | 0.0 | 0.0 | 7.9 | 8.4 |
| 378 | Amy’s Food Adventures | 0.0 | 1.9 | 0.0 | 3.8 | 2.5 | 8.3 |
| 379 | JapanStrategy-Blog | 0.0 | 2.6 | 0.0 | 4.3 | 1.2 | 8.1 |
| 380 | Carl Gressum’s blog | 0.0 | 1.0 | 0.0 | 4.3 | 2.5 | 7.7 |
| 381 | Government IT Infrastructure Blog | 0.0 | 0.0 | 0.0 | 1.6 | 5.8 | 7.4 |
| 382 | Product Value Management | 4.8 | 1.0 | 0.0 | 0.0 | 1.6 | 7.3 |
| 383 | Application Delivery | 0.0 | 0.0 | 0.0 | 4.6 | 2.6 | 7.3 |
| 384 | Gartner – Michael Hanford | 0.0 | 1.4 | 0.0 | 2.6 | 2.9 | 7.0 |
| 385 | MetaMurph’s Metasphere | 4.8 | 0.5 | 0.0 | 0.0 | 1.3 | 6.5 |
| 386 | Technology Pundits – Roger Kay | 0.0 | 3.3 | 0.0 | 0.0 | 3.2 | 6.5 |
| 387 | I of Innovation | 0.0 | 1.7 | 0.0 | 3.8 | 0.6 | 6.2 |
| 388 | Green IT Sourcing | 4.8 | 1.1 | 0.0 | 0.0 | 0.0 | 5.9 |
| 389 | Cloud Computing Blog | 0.0 | 0.0 | 0.0 | 2.6 | 3.1 | 5.7 |
| 390 | Annoying Design | 4.8 | 0.5 | 0.0 | 0.0 | 0.0 | 5.3 |
| 391 | Thoughts From a Software IT Analyst | 0.0 | 0.9 | 0.0 | 1.6 | 2.5 | 5.1 |
| 392 | Key Analysis Research and Consulting – Blog | 0.0 | 0.5 | 0.0 | 3.3 | 1.2 | 5.0 |
| 393 | HealthTech Industry Perspectives | 0.0 | 0.0 | 0.0 | 0.0 | 4.9 | 4.9 |
| 394 | Internet2Go – An Opus RAS | 0.0 | 0.0 | 0.0 | 0.0 | 4.6 | 4.6 |
| 395 | JBB Research Blog | 0.0 | 0.0 | 0.0 | 0.0 | 4.6 | 4.6 |
| 396 | Software Delivery news | 0.0 | 0.8 | 0.0 | 0.0 | 3.8 | 4.6 |
| 397 | The Changing Life Sciences Value Chain Blog | 0.0 | 0.0 | 0.0 | 0.0 | 4.5 | 4.5 |
| 398 | Executive Blog | 0.0 | 0.0 | 0.0 | 0.0 | 4.5 | 4.5 |
| 399 | Health Plan Business and Technology Views | 0.0 | 0.3 | 0.0 | 0.0 | 3.8 | 4.2 |
| 400 | Big Picture | 0.0 | 0.0 | 0.0 | 0.0 | 3.8 | 3.8 |
Methodology
I have taken the feedback I have received from the previous research and modified the methodology.
Scores are now calculated as follows:
Google PageRank – Google PageRank is a link analysis algorithm that interprets web links and assigns a numerical weighting (0 to 10) to each site. High-quality sites receive a higher PageRank. The ranking uses the actual PageRank as part of its algorithm.
Yahoo Inbound Links [date unlimited] – Yahoo counts the total number of inbound links that go directly to a blog. Each number was assigned to a range which was then used as part of the algorithm.
Google Inbound Links [3 months date limited] – Google allows people to search the number of inbound links to a specific blog but limit this to a predefined date period. Similar to how Technorati only looks at six months of data, this method was used in combination with the Yahoo Inbound Link count to assess which blogs were considered to be important due to the number of links that came to them, but also currently relevant as measured by the limitations on the timescale. Each number was assigned to a range which was then used as part of the algorithm.
Google Reader Subscribers – Google reader lists the total number of subscribers to a blog. I believe this is a more realistic number to that which Bloglines provides. Mihai Parparita confirms that “these numbers include subscribers across all Google services”. To account for people using other readers (e.g. Newsgator) it has been suggested that this number is multiplied by 3. Subscriber ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number that was used as part of the algorithm.
Frequency of Posts – Updating relevant and interesting content frequently onto a blog will naturally cause more people to find this blog important. This score is established via Google Reader to understand the precise number of posts per week that the blogger makes. Frequency numbers were determined and assigned to a range that was used as part of the algorithm.
Date Last Blog Post Published – Working in combination with ‘Frequency of Posts’, this score mitigates against blogs that were once popular but haven’t been updated for a long time. The number of days since the last blog post was calculated and assigned to a range which was used as part of the algorithm.
Comments – A simple way to judge how valuable a blog is to other people is through the number of comments (where this is enabled) that visitors make. In a similar way to linking and subscribing this user requested service shows a significant value. The number of comments made over the last five posts were calculated and assigned to a range which was used as part of the algorithm.
Twitter Inbound Links – There are various online tools available to count the number of links inbound to a blog from Twitter. Backtype was used to count the number of these occurrences over the past five blog posts. The number of times this happened was calculated and assigned a range which was used as part of the algorithm.
Weighting – Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish a blogs total score.
Badges
Filed under: analyst relations | 1 Comment
Contentious conversation 1 – integrity of analysts and the future of AR
Blog my Tom Bittman from Gartner – A Rant – My Integrity as an Analyst
Summary: Gartner analyst angry that he has to justify his integrity
My view: Edelman trust barometer consistently shows that over the past few years analysts are the most trusted
Key comments: Vinnie Mirchandani questioning whether Gartner’s reliance on large vendor subscriptions means that their reports are truly representative
What this means:
There is an ongoing fight regarding how independent an analyst can be if they receive money from vendors. Whereas some firms in the past have been ‘White Paper for hire’ houses, they tend to lose industry respect very quickly and go bust. What can not be in doubt is that in subscribing to an analyst house, you have the ability to pay for more time in front of the analysts leading to a greater chance to educate them – often this will result in a more favourable position. I am not saying that to be successful in AR you need to have subs, it is more a case of – it helps.
The secondary argument (and possibly more important) is by having a look at who the key participants in this debate are. On one side we have the analyst and the other we have the IT advisor. The latter group frequently comes from an analyst background (see Vinnie Mirchandani, ex-Gartner; Ray Wang, ex-Forrester) but in their current role do not have a research agenda. By default this does not make them (in their mind) an analyst.
However, I believe we are playing semantics. Our view in AR needs to be simple: if they affect IT buying then they are an influencer and need to be dealt with accordingly. AR most closely deals with these individuals – we may need to adapt a different name so that they don’t get upset by being labelled analysts but they will remain a key audience for us to engage with and should continue to enjoy the same disclosure benefits that traditional analysts enjoy. With the growth of firms like Altimeter Group, this fundamental shift towards a larger influencer group will become more important than ever over the next few years.
Contentious conversation 2 – analysts liable for ‘incorrect’ positioning
Article in IT Knowledge Exchange – Email archiving vendor sues Gartner over Magic Quadrant
Summary: Claiming that Gartner’s MQ constitute “disparaging, false/misleading, and unfair statements” about its email archiving product that have done damage to its sales prospects, ZL filed suit for damages of $132 million to account for lost sales.
My view: This fight has caused great PR for ZL but someone’s position in an MQ should not be a surprise. If a vendor believes they are unfairly positioned the time to argue this point is before the quadrant is published.
Key comments:
The power of a positive ranking in Gartner is immense because it is often the case that large purchases of technology are based exclusively on the MQ Reports…For instance, the Office of the Inspector General, Department of Veterans Affairs (VA) recently conducted an investigation into the use of the Gartner’s MQ reports in connection with the VA’s $16,000,0000 purchase of certain leases and services from Dell. The Office of Inspector General reported that the VA made this large purchase based solely on the leadership rankings in the relevant Gartner MQ report. (source: initial complaint)
In Mark Logic’s excellent analysis of this case, he makes the following comment about whether having the best technology means that someone should be positioned superior to another company who simply has better sales and marketing.
While Ingres arguably had the best database technology in the 1980s, Oracle’s sales and marketing prowess caused it to win the market and any analyst who — focused solely on the technology — would have recommended Ingres at that time would have done his customers a disservice.”
What this means:
Like it or not, Gartner are the original 800lb gorilla. Whether it is right or wrong, the fact remains that their MQ inherently has an influence in IT buying behaviour. What AR pros need to do is work with the analyst ideally six months prior to any publication to fully understand what success criteria are to be better positioned as a leader and work towards those goals. A great way to understand how to work with an MQ can be seen in the great IIAR White Paper.
We have to accept that the firm with the best technology does not always win (see Betamax vs. VHS) – for a company to be successful, they will need to have a great product that is complemented by a sound go-to-market strategy. Luckily for us this is where AR can help.
Filed under: analyst relations | 6 Comments
The IIAR (Institute of Industry Analyst Relations) has completed, via AR guru Peggy O’Neill, a certification test for everyone in this industry. As the analyst profession has matured it has become more important than ever for professionals to master best practices, analyst protocol, and basic knowledge of the industry.
This certification will form the foundation level for an Advanced AR Certification, which is currently under development.
Why is this important?
This test will allow people to show their skills in a way that is often intangible. I know from my own experience, that it is difficult enough to explain what it is I do for a living, so how are you meant to explain to your peers, superiors and potential hirers that you are as good as you are when they don’t even understand AR themselves.
On a more practical level this test is essential to help individuals who may think they know it all (looking at myself here) to understand the areas they need to brush up their skills on.
Example question
All but one of these companies acquired the other.
a) Gartner acquired META Group
b) Forrester acquired Jupiter Research
c) Datamonitor acquired Bloor Research
d) IDC acquired Meridien Research
If you want to try a sample test, you can click here – (I’ll let you know the result of the above question at the end of the post)
This is a pretty tough test with 120 multi-choice questions to be answered in one hour (i thought I had left exams behind me after university). It’s not meant to be easy and those that who have tried it all passed with flying colours. A score of 70% is considered passing, and if test takers fail, they can re-take it in three months.
Analyst relations managers who pass the test are considered “certified” by the IIAR. Certifications are deemed lifetime and applicants do not need to re-take the test periodically. The test is administered by the IIAR and is available for members and non-members. The fee is £100 for non-members and includes the opportunity for one retake if candidates initially fail the test. The exam is free for IIAR members but is not mandatory for membership.
If you practice AR and are not part of the IIAR, it’s worth joining…
I admit I am biased as I am a founding member and board member of this association but it is worth it. From sharing best practice on getting the ideal placement in an MQ or Forrester Wave to discussion with your peers about how to solve a particular issue – this group helps AR as its raise d’être. This certification is just another example of how the IIAR aims to help and promoted the analyst relations profession. Oh, and the answer to the above question is ‘c’.
Recommending reading: IIAR blog, IIAR twitter, press release
Filed under: analyst relations | 2 Comments
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