The most unique aspect of Silk is the fact that it splits functionality between the mobile device and the cloud. Although others have done this in the past, Amazon hopes to take it to a new level.

What are your initial thoughts of Amazon Silk? Share your thoughts.

Al Hilwa, an analyst with IDC, spoke with WebProNews and told us that he actually wasn’t surprised that Amazon made this move. As he explained to us, Amazon is a leader in backend cloud services as well as cloud support capacity. The move was actually natural since Amazon also has a content-based motive with Kindle Fire.

“It wasn’t really a completely new idea, but it made perfect sense for what Amazon is doing,” he said.

Opera is the browser that is most recognized for the split browser, but according to Hilwa, its approach is different from Amazon’s. He said that Opera wants to make its browser available on every network and every device, while Amazon does not. Amazon is more concerned with making its devices extremely optimized and responsive as well as potentially allowing the browser to support its advertising backend.

Although Silk will not be released until next month, Hilwa believes that the technology behind Silk creates a lot of opportunities for Amazon. For instance, Amazon may decide to put it on very inexpensive devices that do not have a lot of processing. This would then allow it to put 3G or 4G on the devices, which is a move that Hilwa thinks would be “synergetic” for tablet makers.

“A browser architecture like this makes is possible to have real economical network consumption patterns that either Amazon pays for or the user pays for,” he said.

In spite of the excitement surrounding Silk, there are also some concerns. The browser leverages Amazon’s Elastic Computer Cloud (EC2) in order to allow for speedy information retrieval. However, to deliver this speed, Silk tracks the traffic patterns of individuals’ behavior.

“This kind of browser puts it in charge of a lot of information from browser users, and therein lies one of the issues with this kind of technology, which is that Amazon simply has a lot of information that you might otherwise keep cached on your desktop machine and not aggregated in any one place,” said Hilwa.

“Whenever one particular location/place/vendor aggregates too much information about people, particularly about you, me… a single individual, then there’s a danger that the information will get abused somehow. [There's] something spooky about these vendors knowing too much about you and targeting you very, very specifically with the amazingly targeted advertising that’s based on a search you may have done… that’s a little difficult for people to swallow,” he pointed out.

Silk has an “off-cloud” mode that users can use that will prevent Amazon from aggregating information, but it’s unclear, at this point what the default settings will be. Hilwa told us that, while these are concerns, there are certain capabilities that could not be possible without such a browser.

Overall, he said that Silk has the potential to be very successful but that it was hard to speculate before it is actually released.

“This is great synergy for what they’re doing,” he said. “It makes a lot of sense for them. Of course, we’ll have to wait and see if this technology actually works in terms of when it’s demoed [and] when it’s actually available on devices.”

He also told us he could see other browsers makers including Google and Microsoft adopting this type of technology in the future.

“This coupling of backend clouds with frontend devices – we’re going to see more and more of that and more and more optimizations across it,” said Hilwa. “The browser is going to be the crucial link that helps that happen.”

Do the cool features of Silk outweigh the privacy concerns or vice versa?

Researchers from Japan’s ATR Computational Neuroscience Laboratories have developed new brain analysis technology that can reconstruct the images inside a person’s mind and display them on a computer monitor, it was announced on December 11. According to the researchers, further development of the technology may soon make it possible to view other people’s dreams while they sleep.

Then, when the test subjects were shown a completely new set of images, such as the letters N-E-U-R-O-N, the system was able to reconstruct and display what the test subjects were viewing based solely on their brain activity.

(Utopic and dystopic scenarios: leasing parts of your brain space to a big corporation for a side income; building a problem solving computer based on low level brain growing farm; big brother supervising thoughts to crack down on dissidents; drawing tools; advanced lie detectors; brain exporting and importing of movies, smells, feelings…)

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Pace’s findings contradict what a recent analysis of Google Trends revealed.  They should, however, stack up well against David Utter’s article on the Republican field (since both used Compete statistics).

According to Compete, then, the campaign website with the most traffic belongs to Barack Obama; Obama’s site received 318,179 unique visitors in November.  Hillary Clinton’s website was the closest runner-up, but it got just 289,615 visitors.

Things looked even more dismal for John Edwards, whose site received only 136,002 unique visitors.  Pace got into the geographic distribution of visits, though, and wrote, “Edwards’ focus on Iowa, where polling shows him very competitive, is evident as he appears to be drawing a considerable following in Iowa to rival Obama and Clinton.”

Kucinich, Biden, Richardson, Dodd, and Gravel all trailed the top three candidates, and did so in that order.  Still, with the better part of a year left to go before the election, there’s plenty of time for any person to shake (or muck) things up.

Visual analytics will be the key. Science Blog said “analysts must meld the encyclopedic eye of Google with the inductive genius of Sherlock Holmes” to accomplish this.

The inspiration of Edward Tufte, visual data display legend, motivates the ongoing work by DHS and its associated research partners:

The centers

]]> http://www.webpronews.com/dhs-emulating-doctorows-scroogled-tale-2007-11/feed 0 http://www.webpronews.com/facebook-myspace-ad-analysis-2007-11 http://www.webpronews.com/facebook-myspace-ad-analysis-2007-11#comments Wed, 07 Nov 2007 20:35:05 +0000 Robert Scoble http://www.webpronews.com/?p=41716 Here’s a 20-minute video where Jeremiah Owyang, Forrester Research’s new social media senior analyst, discusses with me Facebook and MySpace’s new ad platforms. He was briefed by both companies and has the best analysis out there right now.

]]> Here’s a 20-minute video where Jeremiah Owyang, Forrester Research’s new social media senior analyst, discusses with me Facebook and MySpace’s new ad platforms. He was briefed by both companies and has the best analysis out there right now.

Oh, and he invents a new word “fansumer.” Listen to the video and tell us whether you’re a fansumer of a brand. Oh, and my brother’s bar is on MySpace. We’ll play around with MySpace’s new hyper-targetted ads and see if they work.

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]]> http://www.webpronews.com/facebook-myspace-ad-analysis-2007-11/feed 0 http://www.webpronews.com/adwords-quality-score-keyword-analysis-service-2007-10 http://www.webpronews.com/adwords-quality-score-keyword-analysis-service-2007-10#comments Wed, 24 Oct 2007 18:59:26 +0000 Navneet Kaushal http://www.webpronews.com/?p=41371 Inside AdWords introduces the Quality Score Keyword Analysis Service which will help advertisers provide more information about the Quality Score for their keywords.]]> Inside AdWords introduces the Quality Score Keyword Analysis Service which will help advertisers provide more information about the Quality Score for their keywords.

To launch Keyword Analysis page, click the magnifying glass icon beside any keyword in your account; then click one of the ‘Details and recommendations’ links.

This is a sample of the Details and recommendations page

This tool ‘gives you a detailed view of your keyword’s Quality Score — including how Quality Score impacts your keyword and ad’s performance, and how you can improve it.’

To view the Keyword Analysis page for any keyword, follow these steps:

• Sign in to your account at https://adwords.google.com.
• Click a campaign.
• Click an ad group.
• Click the ‘Keywords’ tab above the Ad Group Details table.
• Click the magnifying glass icon beside any keyword to launch the Keyword Analysis page. You can also see an overview of your Quality Score and ad visibility by pointing your cursor over the icon.

How to Use the Keyword Analysis page

At the top of the Keyword Analysis page, you’ll see your CTR, minimum bid, current bid, and keyword status (i.e. active or inactive for search). Below this information, there are two tabs — an ‘Ad showing?’ tab and a ‘Quality Score’ tab.

• Ad showing tab: Click the ‘Ad showing?’ tab to see information from the Ads Diagnostic tool. Find out whether or not your keyword is triggering ads to appear on Google, reasons why, and ways to improve your ad performance. Results are based on specific Google search and geographic criteria. To test using different criteria, click the ‘Ads Diagnostic Tool’ link on the page or from your ‘Tools’ page.

To learn more about the Ads Diagnostic Tool, visit How can I find out whether my ads are showing?

• Quality Score tab: Click the ‘Quality Score’ tab to get details and recommendations about your keyword’s Quality Score. At the top of the tab, find your Quality Score rating — Great, OK, or Poor. Next, find tips on what to do in order to achieve the best ad results. Finally, see how different components that factor into your Quality Score as a whole are performing. Our system checks your keyword relevance and landing page quality. For each problem that we may find, we’ll provide ways to help remedy it.

To learn more about Quality Score, visit What is Quality Score and how is it calculated?

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]]> http://www.webpronews.com/adwords-quality-score-keyword-analysis-service-2007-10/feed 0 http://www.webpronews.com/google-helps-with-keyword-analysis-2007-10 http://www.webpronews.com/google-helps-with-keyword-analysis-2007-10#comments Tue, 23 Oct 2007 18:19:10 +0000 WebProNews Staff http://www.webpronews.com/?p=41331 The vagaries of keyword Quality Scores for AdWords have caused advertisers to ask for more information from Google.

Via the AdWords blog, Google delivered some news that should be of some help to its ad clients.

A new Keywords Analysis page became available in AdWords, as part of the Ad Group Details table. The magnifying glass icon launches Keyword Analysis:

At the top of the Keyword Analysis page, you’ll see your CTR, minimum bid, current bid, and keyword status (i.e. active or inactive for search). Below this information, there are two tabs – an ‘Ad showing?’ tab and a ‘Quality Score’ tab.

Ad showing tab: Click the ‘Ad showing?’ tab to see information from the Ads Diagnostic tool. Find out whether or not your keyword is triggering ads to appear on Google, reasons why, and ways to improve your ad performance. Results are based on specific Google search and geographic criteria. To test using different criteria, click the ‘Ads Diagnostic Tool’ link on the page or from your ‘Tools’ page.

Quality Score tab: Click the ‘Quality Score’ tab to get details and recommendations about your keyword’s Quality Score. At the top of the tab, find your Quality Score rating – Great, OK, or Poor.

Next, find tips on what to do in order to achieve the best ad results. Finally, see how different components that factor into your Quality Score as a whole are performing. Our system checks your keyword relevance and landing page quality. For each problem that we may find, we’ll provide ways to help remedy it.

The usual advice about ad relevance still stands. Google has been more aggressive since last year about weeding out ads it deems less relevant to a query. Failing to make ads and their landing pages more suitable to Google’s expectations could mean few or no ad displays for a campaign.

]]> http://www.webpronews.com/google-helps-with-keyword-analysis-2007-10/feed 0 http://www.webpronews.com/jaw-dropping-salary-raising-quantitative-variables-2007-10 http://www.webpronews.com/jaw-dropping-salary-raising-quantitative-variables-2007-10#comments Mon, 22 Oct 2007 18:37:46 +0000 Gary Angel http://www.webpronews.com/?p=41296 I'm teasing of course. I don't expect to raise anybody's salary with a discussion of quantitative variables (or anything else).

But I do hope to explain one of the more important differences between web analytics and most of the traditional BI marketing analytics that has been done in the last twenty years. In addition, I'm going to make the case for why a new tool from WebTrends is a lot more important than you may be inclined to think. Along the way, you just might get a little richer - in understanding if not in take-home pay!
]]> I’m teasing of course. I don’t expect to raise anybody’s salary with a discussion of quantitative variables (or anything else).

But I do hope to explain one of the more important differences between web analytics and most of the traditional BI marketing analytics that has been done in the last twenty years. In addition, I’m going to make the case for why a new tool from WebTrends is a lot more important than you may be inclined to think. Along the way, you just might get a little richer – in understanding if not in take-home pay!

What actually got me to write about quantitative variables is a product from WebTrends that I first saw in late July and re-visited at the Engage Conference in Vegas. The product is called Score and it’s a product direction that I believe to be significant. One that echoes back to a great deal of work we did in the first six or seven years at Semphonic.

To explain why I think Score is significant, I’m going to have to have to delve into a bit of analytic theory. Don’t groan – I’ll do my best not to be too digressive!

For many years, multi-dimensional analysis has been the staple of business intelligence systems. Products from companies like Business Objects, Cognos and MicroStrategy have provided rich multi-dimensional reporting and analysis for probably a good decade. Web Analytics tools like Discover 2.0, Visual Site and WebTrends VI are just beginning to provide the similar levels of capability to web analytics.

What is multi-dimensional analysis? It’s simple stuff really and this is ground I’ve gone over before. In basic statistics, you typically start an analysis with a Frequency table. A Frequency table gives you the counts for all the values of a single variable. Here’s a example:

Gender	Count	Percent
Male	1549	37%
Female	2238	53%
Unk	413	10%

A frequency is a 1 dimensional analysis – it looks at a single variable. The next step up in complexity is called a cross-tabulation. And cross-tabulation typically begins with two variables. Here’s a classis 2-way cross-tabulation:

	Gender
Age	Male	Female	Unk
16-25	540	400	60
26-40	525	900	75
41-65	325	780	195
65+	159	158	83

Cross-Tabulation is 2 dimensional analysis – and the basic method can be infinitely extend into three, four, five and potentially even more dimensions. In three way analysis, we might add a variable like income and be able to see the count of all High-Income, Age 16-25, Males versus the count for all Low Income, Gender Unknown, Age 65+.

What’s happening when you do multi-dimensional analysis is, implicitly, visitor segmentation. Each cell in the n-dimensional table can be reasonably considered a specific visitor segment. And by adding metrics around success or usage, you can map these descriptive variables to real-world differences in performance.

 

N-Dimensional analysis is powerful. But it also has some fundamental limitations that are poorly appreciated both in the BI world where it has been the dominant paradigm and in the web analytics world where it has looked like the holy grail.

When you use multi-dimensional analysis, you are segmenting visitors (or visits) into finer and finer units. Eventually, you might have a success count for an extremely small population defined by six or seven different factors. But as powerful as this is, there are some things it just can’t do.

First, multi-dimensional analysis is like a series of implicit AND filters. A visitor must be 18-35 AND male AND High-Income AND located in California. But suppose you want to add an OR filter. Suppose, for example, that you want 18-35 and MALE and (High-Income OR Medium Income) AND located in California. You can do this (in a way), by adding up cell counts. But the multi-dimensionality works against you now, because the OR may add 500 (50 states x 5 age categories x 2 gender categories) cells to keep track of. That isn’t very practical. So here’s a key capability to look at when you evaluate a multi-dimensional reporting system – can you collapse some values in a dimension easily. Some systems let you do this – – but many don’t. It’s a subtle point but it makes a big difference in the real world.

Even more significant, however, is the difficulty that ANY multi-dimensional analysis system has with quantitative (continuous) variables. Classic multi-dimensional analysis evolved in the CPG world where demographic variables were almost always the dimensions. Demographics aren’t usually quantitative. You are either Male or Female, 18-35 or 60+. It’s true that variables like age and income COULD be treated as quantitative values, but they are almost always used as Category variables. These variables aren’t treated as numeric variables where the value difference is signficant.  From a marketers perspective, 25-40 is just a category. and 26 is the same as 40 but different than 24.

This is a key fact about Multi-Dimensional analysis – it isn’t particularly useful for anything except the analysis of variables as CATEGORY variables. Multi-dimensional analysis doesn’t treat values as numerically significant.

In web analytics, however, the key dimensions are behavioral. And virtually every behavioral variable IS quantitative. We are commonly interested in HOW MUCH a visitor did: how many page views of Product Material, how many petitions they signed, how long they spent on site, how often they visited, how much product they purchased. In all of these cases, good analysis of the data requires numerical comparison of the variable values.

There are behavioral variables that aren’t quantitative (Is Customer, Is Registered) but they are much less common than quantitative variables. In web analytics, by far the most important behavior is page view. And page views are quantitative in every sense. They are numerically comparative and the number is ALWAYS significant.

Multi-dimensional analysis doesn’t handle these quantitative variables. You HAVE to bucket variables before you can analyze them – so you’re reducing quantitative data to category data at the very outset. And if the variable isn’t bucketed, it isn’t available as a dimension. So suppose you want to analyze the effect of viewing Product X feature pages or spending time in the Product X feature area. In multi-dimensional analysis, you can’t do it unless you can bucket Product X feature page views or Product X feature time.

In many, many systems, you can not bucket these variables. That means you can’t do multi-dimensional analysis on them. And even when you can bucket them, you are limited to the ranges in the buckets. You aren’t ever analyzing them numerically. And here’s where our AND issue strikes again, because if I want to evaluate visitors with High Pages OR High Content Time, I’m back to adding up cells. And the methods of multi-dimensional analysis don’t give me anyway to take advantage of the fact that the actual value of a quantitative variable IS significant and can be usefully compared to other actual values.

Without the ability to flexibly bucket and collapse range variables, doing multi-dimensional analysis on quantitative variables is impossible. With them, it is extremely clumsy and not very useful. No matter how powerful the multi-dimensional model is, it’s really the wrong tool for the job.

So what’s the right tool? Well, that brings us back to my opening. Because the answer is something like Score.

Score lets you assign values to actions – and those values are additive. So I can produce a visitor score based on the number of product content views. Or the total time in a content area. Or on ANY combination of those two values that exceeds a threshold I set. What is virtually impossible to do with even the most flexible and powerful multi-dimensional analysis tool is trivial with a scoring system.

Before we began using off-the-shelf software, scoring was the primary analytic technique we used at Semphonic. We didn’t do it by hand (the way Score has you do it) – we used neural networks to score visitors across dozens of different dimensions. But Score’s user driven approach is still vastly more powerful for a host of important web analytics tasks than mulit-dimensional analysis.

What tasks are these? One of the obvious ones is measuring Engagement – which is why Score was discussed so prominently at Engage. You can’t measure Engagement with a single measure. And nearly every significant component of Engagement is quantitative – how much you do of something is CRITICAL. Which makes analysis of Engagement in multi-dimensional tools problematic.

But the utility of a product like Score is hardly limited to Engagement. For obvious reasons, scoring methodologies allow for significantly richer visitor segmentation than rules based around dimensional filtering.

CRM integration is a third – and particularly significant application for scoring methods. When I first saw Score, its potential uses for driving customer contact programs seemed obvious. Many of our clients do both regular and event-driven email messaging based on site behavior. Using multi-dimensional filtering, these cuts are quite limited. Scoring makes this process both much simpler and much more powerful.

A travel site, for instance, could easily establish threshold values for receiving an email alert on a particular destination. That threshold might include ANY combination of actual trips to the destination, planned trips to the destination and actual trips to similar destinations. Trying to accomplish a similar filter with multi-dimensional cells is either impossible or tortuous.

Here’s an even an even more difficult problem – suppose I send my customers a once-monthly newsletter and I want to target a dynamic offer to the destination they are MOST interested in. This is flatly impossible with multi-dimensional filtering. It is possible with scoring systems (though not – sadly – with Score which doesn’t currently support this).

Effectively, what scoring methods let the analyst accomplish is the analysis and combination of quantitative variables. In web analytics, this turns out to be an immensely useful capability because all of the core variables ARE quantitative.

Score is a ways from being perfect – it’s Version 1.0 after all. You can’t use all the variables you should be able to. You can’t compare scores. You can’t use negative scores. There are limitations on the number of scores you can build. The rule building process isn’t terribly flexible when it comes to integrating with large amounts of content. There is no data driven scoring.

But despite these V1.0 weaknesses, Score is a very, very significant upgrade in capability compared to multi-dimensional analysis within web analytics. It’s already a great tool for a number of key web analytics tasks. With continuous improvement, it has the potential to become one of the most important tools in web analytics. Once analysts start using tools like Score, they are going to realize something that should have been fairly obvious all along. Web Analytics is all about quantitative variables.

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]]> http://www.webpronews.com/jaw-dropping-salary-raising-quantitative-variables-2007-10/feed 0 http://www.webpronews.com/social-network-for-usability-professionals-2007-10 http://www.webpronews.com/social-network-for-usability-professionals-2007-10#comments Wed, 03 Oct 2007 22:24:32 +0000 Kimberly Krause Berg http://www.webpronews.com/?p=40852 A new networking community called Catalyze.org has made its debut. In Beta, its niche is the usability industry, specifically business analysts and user experience professionals. Anyone involved in web site design will find something of interest there. ]]> A new networking community called Catalyze.org has made its debut. In Beta, its niche is the usability industry, specifically business analysts and user experience professionals. Anyone involved in web site design will find something of interest there.

The homepage features immediate links to blog and forum posts. The last column is set aside for files. Additional sections target education, events, a jobs board and articles. It is joint venture provided by the International Institute of Business Analysis and the Usability Professionals Association.

From their About Us page:

Catalyze is a member-driven community for all professionals involved in defining business systems, designing software applications and creating websites. If you are a business analyst, usability professional, UI designer, information architect, interaction designer, product manager, project manager or anyone else involved in the definition process of software applications, this community is for you and will be worth your time.

Professionals approach application definition from many different angles and this community will “catalyze” or gather strength from all points of view to heighten the importance of this space. The challenges, issues and topics are similar across all of these professional functions, and Catalyze is the first community to bridge these diverse disciplines.

Catalyze is free to join. You don’t have to be a member to gain access to all the content, but once you do register, your experience with the site is more robust, intuitive and designed to permit more networking.

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