Institutions reduce the choices available to their members. (This is Ronald Coase’s famous argument about transaction costs.) This reduction allows better focus on the remaining choices they face.

The editors meet every afternoon to discuss the front page. They have to decide whether to put the Mayor’s gaffe there or in Metro, whether to run the picture of the accused murderer or the kids running in the fountain, whether to put the Biker Grandma story above or below the fold. Here are some choices they don’t have to make at that meeting: Whether to have headlines. Whether to be a tabloid or a broadsheet. Whether to replace the entire front page with a single ad. Whether to drop the whole news-coverage thing and start selling ice cream.

Every such meeting, in other words, involves a thousand choices, but not a billion, because most of the big choices have already been made. These frozen choices are what gives institutions their vitality — they are in fact what make them institutions. Freed of the twin dangers of navel-gazing and random walks, an institution can concentrate its efforts on some persistent, medium-sized, and tractable problem, working at a scale and longevity unavailable to its individual participants.

All fair arguments (emphasis is mine) and very much in line with our thinking at Visual Revenue. Institutions reducing choice materializes in such procedures as Editors agreeing upfront about some articles not being eligible for front page exposure. This could be as simple as the publisher deciding that Articles older than 4 hours cannot be shown in the Hero Spot, that only 2 sports articles can be above the fold at any point in time, or that 60% of the Articles must be from the region of their primary constituents. This type of choice reduction is realized by having us ask Editor’s to outline their Editorial Tone as a set of Persistent Editorial Instructions.

However, the state of affairs is still one of astronomical choice, where the initial limitation of choices, in the online news media industry, still leave you with an inhumanely amount of possible front page layouts. Unfortunately not thousands of choices, as Mr. Shirky so kindly suggest.

In conclusion;
Modern newsrooms either need to reduce choices so dramatically that a human editor can easily and timely decide how to program the front page, or the organization must deploy technology that help reduce choice and calculate best performing outcomes within an editorial framework. This is all we do at Visual Revenue!

Cheers :-)
/ Dennis (@dennismortensen)

• Return of the Editor: Why Human Filters are the Future of the Web
• How Algorithms and Editors Can Work Together to Burst the “Filter Bubble”

I am largely in agreement with folks like Eli Pariser, that we run the risk of creating a filter bubble, as he so politely calls it, in his book and the above Mashable article.

“It’s clear the current [personalization] platforms don’t get us there on their own. But by striking a balance between editors and code, Pariser thinks we can get the best of both worlds.”

So, sorry about the advertising, but welcome to Visual Revenue! I am super happy to see I am not alone in the belief that Algorithms and Editors Working together is a winning formula! The Visual Revenue platform allow Editors to teach and bend our Algorithms as they desire, and I am proud to state that we are, however corny it may sound, the editor’s knowledgable sidekick, certainly not the other way around.

Features like the following speak directly to Editors teaching and bending our Recommendations, in regards to what content to promote on their homepage in real-time;

• No more than 10% of the stories can be Gossip. Showing the engine that our editorial tone is in hard news.  Though entertainment stories are allowed, don’t turn my front page into a Jersey Shore fan page.

• Pinning a story to the Hero spot for 4 hours. Telling the engine to bugger off and NOT recommend other stories to this position, and by the way, don’t suggest this content to move elsewhere.

• Pass on this recommendation for the next 30 min. Telling the engine, that I get it, but you know what, I am comfortable with what I have for now.  However, if it still resonates with my audience a bit later, please bring the recommendation back to my attention.

I think you get the gist of how we operate and who we serve! It is not just about making the biggest revenue opportunity for our publishers; it is about making sure, while doing so, that we help and assist the editor in keeping their integrity and editorial tone intact.

Cheers :-)
/ Dennis (@dennismortensen)

The three of us took to the stage and pitched our respective products to a panel of judges that included John Cantarella, president of digital at Time Inc. News Group; Charlie O’Donnell, principal at First Round Capital; David Tisch, managing director of TechStars New York;  Alexa Von Tobel, founder and CEO of LearnVest.com; and Margaret Tuohy, director of product for CNNMoney.

After the pitches were over, the judges headed off to deliberate and returned to announce that…drum roll please…

Visual Revenue had won!

We’ve spent the last two years interviewing editors, wire framing, coding, tweaking, more interviewing, alpha testing, beta testing, (more interviewing :)) and finally launching the Visual Revenue Recommendation Platform!! We’re extremely fortunate to have such an awesome team (pretty aren’t they!) and I know I speak for all of us when I say we’re truly humbled to have won this event – GREAT job all!

Sadly I was unable to attend the event, but managed to follow it on the train (on my way up to ONA’11) via Twitter. Here are some of the Tweets that were bouncing through the twittersphere:

@ctull13: Key takeaway from #StartUpCNNMoney – if you want that capital, you’d best show some pride in (and passion about) your product.

@lyndabauer:”Really having the value proposition for CNNMoney right up front is most important” Margaret Tuohy #StartupCNNMoney #nyc-tech

@CNNMoneyTech: It’s official. @visualrevenue has won the first-ever #StartupCNNMoney event. Congratulations!

Thanks to the CNNMoney Team for the opportunity to pitch alongside the great guys from Qwanz and Roboinvest and we look forward to partnering with you!

We’ll also be LAUNCHING our new Collaborative Editorial Environment for our Front Page Recommendation Platform at the Conference, so do drop by and visit us at our booth (#15) to find out more:

In order for us to provide our recommendations for what to put where on the front page, we use a plethora of signals as inputs for our model (our secret sauce if you like!). One of these is how well each article you promote on a front page drives further ‘down-stream’ engagement or, put another way, how deep that article drives a user into other site content once they’ve finished reading it. We choose to expose some of the metrics we use for our modeling – article engagement will join others such as individual front page position value and its real-time CTR.

As always, our approach has been a simple one for the UI – the modeling we do to come up with the engagement score itself, is somewhat more sophisticated! Simply put, the more ‘orange dots’ you have displayed the better that article is at driving your readers on to consuming more content.

Two examples:

1) Whilst this article might be a great read, it is not driving your readers deeper into your property. This is reasonably typical of new stories that have no related content or back stories:


2) This article is a compelling piece of content, it possibly has a lot of background material or has great surrounding content (an Editor’s Picks, Must Read or Don’t Miss module) helping drive readers deeper into your property:


The engagement is calculated (as with everything else we do!) in real-time, and the score can therefore change during the day. It should be noted that we separately calculate for different content types (text article, galleries and the like) – this will ensure that an article that drives readers deeper doesn’t get eclipsed by a gallery just because it is perceived to have many page views.

This is a ‘tasty morsel’ to wet your appetites and we’ve plenty more to come over the coming month!

For each content recommendation in each time period, we assign a value.  This value could be in monetary terms, page views, engagement, or any other metric the media property uses to measure performance.  The Recommendation Value takes into account the specific value of that piece of content, content type, the depth into the site it drives the reader and the monetization methods used by the media property.

Based on the action of the Editorial Team, the Recommendation Value is categorized into either Realized Value or Opportunity Cost (See figure below).  Realized Value is the value captured by the media property by acting on the recommendations.  Opportunity Cost is the potential value loss from not taking the recommendations.  Opportunity Cost comes in two flavors:

1. the recommendation was ignored or not taken in time
2. as discussed in an earlier editorial instructions post, editors can put in instructions to shape our recommendations and recommendations prevented by these instructions are counted as Opportunity Cost. For example, if a two-day old Mayor Bloomberg article would generate the most value in the top spot but the editor has decided ahead of time that nothing older than 4 hours can be placed in the top spot, we have traded performance with editorial tone.

We don’t have an opinion on how a media property should set its tone.  We do execute on the publishers tone down to the T and keep track and report on those actions.

Recommendation Value provides full transparency into how the Visual Revenue decision support platform and enables us to clearly communicate the importance of individual recommendation to the editors.

What do you think? What else can we do to support the editorial process while maximizing value?  We would love to hear from you in the comments – or feel free to email us at hello@visualrevenue.com.

I firmly believe this validates our approach of visual revenue supporting a data driven media room of the future. Also, if there was ever any doubt, we can underline and bold the statement of Visual Revenue providing the most sophisticated and powerful value-driven programming tool for publishers in the world today! We have 731 unique front pages under management and have the largest customer base of any programming tool vendor.

If you’re in media, or an Editor (or just a friend), and you want to follow this story, do go sign up for our RSS feed or Twitter stream. OR even better, shoot me an email, so we can come by and present our solution to you and your team.

This certainly wouldn’t have happened without the dedicated and enthusiastic work of the brilliant Visual Revenue team. Thanks guys!

Cheers :-)
/ Dennis (@dennismortensen)

The official Press Release
Yahoo! News
Dennis Mortensen’s Visual Revenue secures Series A Seed Funding

Temporary Editorial Instructions have been designed so the Editor can communicate with the Platform.

Take Larry, the Editor in charge for the home page. We see him push the “Dutch roof collapse” story into a prominent Feature1 position in the morning, but as the day evolve we start recommending that the “News of the World” story goes into Feature1. For very valid reasons, a regional tie in, Larry is not ready to move this story just yet, so he tells the engine to snooze on the “News of the World” story for the next 30 minutes, and allow us to: a) come back with the recommendation for this story in this position if it still resonates with the readership and b) put the story back into circulation, so we can recommend the second most optimal placement for it.

This is where algorithmic and generally Data Driven Editorial instructions really have the opportunity to add a lot of value – assuring that the editor-in-chief can set the tone and apply a set of guidelines that are always kept by his team of editors. Such as the following example of persistent editorial instructions which work perfectly in conjunction with the temporary and very much in the moment editorial instructions:

• We must promote at least 60% local stories on the front page at any given point in time
• We must use a story with picture material for position 1, 2 and 3
• We cannot show content in the top carousel older than 16 hours
• We cannot have more than 3 stories from the entertainment category above the fold
• We cannot have a gallery in the hero spot
• We cannot use more than 30% AP stories

Exciting isn’t it!? If you are not yet a customer, you are more than welcome to connect directly and we can setup a chat.

Cheers :-)
/ Dennis (@dennismortensen)

I am most sure none of us could imagine walking into the trading floor of Deutsche Bank and see 50 traders engaged in the market, based on experience, intuition and an idea of what is important only. Every single one of them will have a Bloomberg terminal or similar data support, some of their decisions will certainly be automated, but a lot will be human driven decisions assisted by data.

Today, it is acceptable to walk into a newsroom, and have 50 producers and editors engaged in creating and promoting news of the moment, without any decision support platform at all. To me, asking for targets, whether in engagement, unique visitors, page views or more sophisticated metrics, seems almost unfair and to some degree unrealistic – if they are not armed with the proper backup and data driven decision support systems.

I am biased of course, but it comes from the heart.   I do truly believe that change is in the making and the future of media is bright.  Our vision of putting the visual revenue content recommendation platform in every newsroom is absolutely sane!

Cheers :-)
/ Dennis (@dennismortensen)

Randomly picking a week in April, I looked at all of the recommendations Visual Revenue provided for two of the properties we work with in the daily national news space.  Their stories cover categories like sports, entertainment, local, national, world, politics news etc.

The below two figures show the ten most valuable recommendations for each news property during the week. *The actual recommendations are of course masked to keep our client data confidential.

Only the 9th and 10th most valuable content recommendations are in the gossip category for the US property, and only the 7th, 8th and 9th content recommendations of the European news property are entertainment related. It is worth noting that this is when no editorial instructions are applied.  Gossip and Entertainment do drive a large amount of value, but I think it is important to reaffirm that News and Sports are equally represented in content recommendations, and that this happens without any filters in place.

These two examples are pretty good representations of the distribution we see with our customers in the general news space and as much as conventional wisdom tells us that readers cares only about gossip, I really think the data has spoken.  There is a place in the readers’ hearts for other news categories.

Lindsay Lohan doesn’t always win! ;-)