I was excited to read this afternoon that Microsoft is on the verge of rolling out a new version of the MSN.com homepage to its 100M+ users.
A preview of the redesigned homepage is available here. The redesign finally gives the site a more modern look (farewell “iconic” blue background) and introduces some cool features around search, social media and local news. However, the following feature is potentially the most interesting:
Headlines on the page will now be customized based on user behavior, so, for instance, people who tend to be more interested in entertainment news will be more likely to see those type of stories.
I love this direction…. given the loyalty of their audiences, the big portals like MSN, Yahoo and AOL should be able to do a really good job of dynamic personalization (the sort of personalization that happens in the background without requiring the user to make choices or selections). As far as I can tell, Yahoo and AOL aren’t doing dynamic personalization (yet), so it seems that MSN may get a headstart in this area.
Hopefully MSN will be forthcoming with performance stats over the coming weeks / months as users adjust to the new design and features.
comScore’s Digital Year in Review 2009 reports that U.S. consumers viewed 4.3 trillion online display advertisements, including static and rich media ads, during 2009 (as measured by comScore’s Ad Metrix system). This represents a 21% increase over 2008, driven by increases in both the number of people exposed to display ads online (+8%) and the average ad frequency (+12%). What I found interesting about these stats is that the top 10 publishers (shown above) accounted for 1.8 trillion (or 42%), with the thousands upon thousands of other publishers, including all the major newspaper brands (Gannett, Hearst, NYT, Tribune etc), accounting for just 58%.
The Economist had an interesting article this week on the data deluge, in which it argued that, to help users feel like they retain control over their online data, sites need to make more data available to their users:
First, users should be given greater access to and control over the information held about them, including whom it is shared with.
I totally agree that sites should provide greater transparency with respect to tracking and data collection / storage. The Economist highlights Google which allows its users to see what information Google holds about them, and lets them delete search histories or modify the targeting of advertising.
Other sites are increasingly doing this too. For instance, I really like how the Newstogram technology has been implemented on DailyMe.com with a dedicated “My Newstogram” page which shows me what data the site is stored about me, explains how the data will and will not be used, and gives me the ability to correct the data or to opt out of tracking altogether.
Yahoo has similar functionality available through its Ad Interest Manager page (although Yahoo is either tracking a lot less about me or is not as good at determining my interests as they only have me pegged as a generic sports fan).
Last week Google Reader introduced two new features to help users find interesting content. Google claims that one of these, the new and improved Recommended items section, has items “selected just for you”.
Today was the first time I had the chance to play with the Recommended items section and I have to admit to being totally unimpressed. For some reason, Google Reader thought I’d be interested in ctrl+z stationary (above), glass toilets, little people and some research about women’s preference for hairy geeks! In fact almost every item in my Recommended items section was a popular (100+ ‘likes’) photo or cartoon with no relation to the hundreds of items I read every day through Google Reader. If there is personalization happening it is either incredibly subtle or not very good.
Google recently announced it was changing the way ads were selected for placement alongside Gmail messages:
Until now, the ads you’ve seen next to a message were picked based on the content of that message only. For example, if you’re looking at a confirmation email from a hotel in Chicago, you might see ads about flights, restaurants or other things relevant to your trip to Chicago.
But sometimes, the ads related to a particular message aren’t good enough. Rather than show less relevant ads, Gmail can now instantaneously serve ads based on another recent message on the same page of your inbox, helping make the ads more relevant to you. For example, if your friend sends you a message to say happy birthday, but there aren’t any good ads to show related to birthdays, you might see ads related to another message in your inbox instead — like flights to Chicago.
Sounds like a minor change, but essentially they’re moving away from strict contextual advertising towards more behavior-based advertising. Google has clearly observed what is apparent when spending time on many online news sites… strict contextual advertising often just doesn’t work.
I wonder how long before they start taking a similar approach with AdSense ads?
Earlier this month Quantcast announced a Series C funding round of $27.5m (led by Cisco Systems and also including existing investors Polaris Venture Partners, Founders Fund and Revolution Ventures), increasing total investment in Quantcast to around $50m.
Today, Techcrunch is reporting that NuConomy is being acquired by LivePerson for around $3m.
Although they take different approaches, both of these companies are focused on making online analytics more useful and actionable for sites and advertisers – it is great to see investment activity in this space.
Microsoft LiveLab’s new visualization tool Pivot looks amazing…. almost worth getting a Windows 7 machine to check it out!!
The feedback on my tree map visualization was very insightful. Colleagues pointed out that, while interesting, the tree map suffered from the same problem as my other attempts to visualize the Newstogram data: namely it doesn’t address the time dimension. While tree maps and other ’static’ visualizations (such as bar charts) can display data over a number of different time periods, they don’t really show how the data is changing over time. In the case of many data sets, including the ‘news interest’ data we are tracking through Newstogram, this is the most interesting aspect of the data.
A possible solution is to use a stacked graph visualization. Stacked graphs have been used to visualize a number of data sets including movie revenues, music listening habits, twitter posts, baby names and how people spend their time. So, armed with Lee Byron’s Streamgraph whitepaper, my latest visualization project is to display Newstogram data in a stacked graph.
After seeing Nick Mihailovski’s Google Analytics / Protovis mash-up last week, I couldn’t resist playing around with the Protovis visualization package over the weekend.
My first visualization effort is a treemap showing the popularity of sub-categories within DailyMe.com based on Newstogram data for October 2009 (built upon the Protovis treemap example).
The colors represent primary categories, while the size of each sub-category corresponds to its popularity as measured by the ‘Digital News Affinity’ (DNA) score for October 2009.
The search field at bottom of the treemap highlights certain categories / sub-categories (e.g. searching for “sports” highlights the 14 sports sub-categories).
Check out the working demo (requires a modern browser e.g. Firefox, Safari).
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