Follow-up articles like this one in Business Insider mention the lower CTR on Facebook ads that CTR-focused people grew to like on Google. While the comparison seems completely beside the point, the mere use of the CTR metric is what really strikes me as very wrong. Would that be how GM measured the success of their campaign? Let’s hope that was not behind their 10 million dollar decision.

I don’t have to bore you with the arguments of why CTR is no ROI metric, but I think that this whole debacle shows how the industry has not agreed on which metric really is right.

Much depends on your goals. For ad-supported publishers we work with, when evaluating the complete value of a Facebook referral (measured in FloPower, which includes the expected future financial value) and comparing it to referrals from other sources, Facebook seems to create a lot more value per referral. That would suggest that it pays to be seen on Facebook, whether through advertising, content links, sponsored stories etc. When all is said and done, one might even conclude that the ROI is higher for Facebook than it is for Google (see chart).

Granted, these data focused on ad-supported publishers only who make money from increased user engagement. But one might argue that that is very close to the goals of a brand marketer.

An immediate conversion may be better served by a search referral, but it is hard to imagine that GM really expected consumers to convert on the first click? I think another look at the data could be revealing. – Anke Audenaert

JumpTime is listed in the latest Display LUMAscape published by LUMA Partners. JumpTime was included in the Publisher Tools category.

As described on LUMA Partners’ site, “Our Display Advertising Technology landscape is one of the most viewed, used, referenced and copied slides in the industry. And now we’ve expanded the collection to include “LUMAscapes” for all the digital media sectors — DISPLAY, SEARCH, VIDEO, MOBILE, SOCIAL, COMMERCE, and GAMING.

We have produced a variety of content that reflects our focus on and understanding of the digital media ecosystem — how it works and where its going.”

What is the equivalent to e-commerce conversions for ad-supported publishers?

I have often felt a bit envious of the e-commerce websites.  Not just because I like to shop, but working with ad-supported publishers to better monetize their hard earned website traffic always left me hungry for better data.  Granted, every analytics tool provides a ton of data, but key KPIs for these publishers are missing.

There is no lack of data describing the traffic acquisition mechanisms.  I understand who comes to my site, when and where they come from.  That is absolutely valuable, and it helps me to hone my traffic acquisition strategy… a bit. I also get data on what all these visitors are doing on my site, i.e. which pages are popular, what do they click on etc. However, the big thing I am missing is this:  what content really engages my visitors and delivers value to me? After all, as an ad-supported publisher it is my goal to keep people engaged for as long as possible with the content that monetizes best (read: has the best paying ads).

But how can I figure out which content is conducive to doing so? Traditional analytics tools are not great at answering that question. I can look at the time people spend on a page, but that is not really answering this question. In theory I could set up thousands of goals (where the goals would align with getting users to my most valuable content), or I can endlessly study the traffic flow/funnels on my site to try and determine which paths lead to the highest value. But, with an almost infinite number of paths, I won’t ever feel like I completed that task.

So, that is where my e-commerce envy comes in. In e-commerce the goal can be neatly attached to an ‘event’, a conversion that I can easily teach the analytics tools to pick up.  Hence, I can understand which paths deliver value or not, which content works or not etc. But the ad-supported publisher does not have that luxury.

That is why we developed the FloPower algorithm, to give publishers an alternative to measuring value of their web traffic and optimize accordingly. FloPower attaches a value to every piece of content, based on observations of how the traffic flows through the site, and aligning that with revenue data per page. This allows a publisher to understand how value is created on their site, which content is most valuable to them, and which traffic sources are best at driving people to that content.  Or, in e-commerce terms, ‘converting visitors into high value content users.’ – Anke Audenaert

I agree that it is a futile exercise to keep finetuning targeting and the resulting segments endlessly. After all, one could argue that the ultimate targeting effort (one we are supposedly striving towards with increasingly finetuning the segments) hits the person who was guaranteed to convert – hence making the whole exercise mute (or a waste of money).

But instead of “too much data is too much distraction”, I would argue “when the flood of data is not translated into actionable metrics, too much data becomes unmanageable.” However, when funneling the data into the right metrics that can support decision-making, having a lot of data can prove to be a real asset.

I think people get paralyzed when they see too much data, but when handed a metric that supports their decision-making, they embrace that metric, especially if it can help them to improve their bottom line. The increasing amount of data allows us to finetune those metrics and translate them into better decision making. – Anke Audenaert

“Choose the right metric and they’ll create the most glorious digital experience in the universe, the perfect acquisition campaign, the most amazing customer service channel. And they will shock you with the profits they deliver. Choose the wrong one and they’ll create self-serving, sub optimal, non-competitive, tear-inducing outcomes that will, slowly over time, bleed the business to death.”

And this shout out to JumpTime: 

And this: “Changing the lens through which you view success can ensure that you watch the right thing, you debate and deliberate, you choose to slowly experiment, you shift budget.”

And finally: “Friends don’t let friends measure Page Views. Ever.”

If the web analytics dashboard prominently measured Visitor Loyalty, would they still create link pukes?

Would they not think: “Even my mom hates our site, how can I earn her love, the thing that has eluded me all my life?”  Would they then not focus on relevance and not generic link puking? Would they not buy simple behavior targeting solutions to use past behavior to customize some of the experience to deliver delight?

Would they not buy a solution like JumpTime to, in real time (!), look at the FloPower of every link and economic value it is delivering (still in real time!) to go from 500 to just 200 links? Would they not obsess about speed because both mom and dad despise waiting?

I believe the answer to every single one of those questions is yes. Yes, they would. Read more.

The news media never really made most of their revenue from news. Instead, the old model in the media business basically used bundling. Take the case of newspapers. If you wanted to browse the football scores, check stock quotes or browse the help wanted ads, you had to buy the whole newspaper. The revenue from the help wanted ads, the business section, the real estate section, etc., subsidized all the other parts of the news business.

That cross-subsidization model, which consists of subsidizing the actual news content, which consumers do not seem willing to pay a lot for, by bundling it with other content they do want to pay for, does not translate well online (as was pointed out by Google’s chief economist Hal Varian in his talk on Newspaper Economics).

As the supply of content grows more diverse and the content tail grows longer, it becomes harder for users to find the content they like. Over the past decade, increasingly sophisticated search algorithms have been developed to help consumers confront this challenge and match them with the content they like. While the demand-side matching problem has largely been solved for consumers of online content, this new technology has arguably made things more challenging for publishers.

Users have now become increasingly sophisticated in finding the exact content they need on tailor-made web sites. They no longer need to buy the whole newspaper in order to find all the real estate listings in their city. Cross-subsidization of content no longer works.

Because the bundling model is broken, it’s become critically important for publishers to understand the value of each piece of content they create. However, the analytics industry has been slow in providing answers.

Content Valuation is Critical to Re-constituting the Bundle
To manage a content business with authority, publishers need command of which content to produce; which content to promote on high traffic pages; they can even decide to buy traffic for particular content by bidding for search keywords.

While search has made strides in the demand-side rankings of content (through algorithms like Google’s Page Rank) these rankings are disconnected from the actual value the content generates for publishers.
Publishers need a different ranking of content than their search counterparts. In fact, they need a valuation algorithm that tells them what a piece of content is worth to them (just like page rank does when it assesses relevance for every piece of content online): how much will a typical surfer landing on a piece of content generate in additional dollars? The answer to that simple question really consists of two parts:

1. The revenue earned on that page (e.g. from display ads), and
2. The additional revenue earned on the pages the surfers subsequently visits.

Why Today’s Valuation Approaches Fall Short
While the answer to the first question is often intuitively understood (although there are no clear analytics reports that provide this information), the second question seems daunting, because it requires identifying all of the possible future paths a surfer can take, attaching probabilities to each of these paths and then average over all of them. Just thinking about the number of possible paths a surfer can choose makes your head spin! This valuation problem had not been solved until now.

Some providers, like Omniture, have decided to focus on a couple of “important” paths, just to make progress on this. While that’s certainly a promising approach for e-commerce, it just does not really work for publishers, because there is no obvious set of common paths.

JumpTime’s science has made this daunting problem manageable by breaking this problem down into lots of little pieces. Rather than immediately valuing all future paths of the surfer, which means going one, two, three etc…clicks downstream, we just focus on valuing the transitions to the next pages (one click downstream), and then the next pages, and the next pages…and we simply keep doing that until we have solved the original problem of valuing all of the entire future paths. This is an old trick from the field of dynamic programming that’s commonly used in engineering, economics and other fields. JumpTime applies this very same trick to valuing web content.

Getting the right metric actually matters for the bottom line. Using simulations on actual publisher data, we found large increases in revenue (more than 120%) when we rearranged all of the links according to our metric. Rearranging all links is obviously artificial but it turns out that most of the gains can be achieved by only rearranging a few critical links. Real-life data show that using our metrics to make programming decisions indeed lifts revenue by 20-36%.

Without this new line of sight, publishers often rely on a short-sighted policy in which they only look at immediate revenue a page generates and rearrange links and social promotion to flood traffic to those pages, with no notion of the actual economic value of these pages, in fact economics and our modeling have show that those short-sighted traffic flow decisions produce a much smaller economic effect and may even hurt engagement…

Once publishers have the means to value their content properly, they can make better investment decisions. They can use their online real estate more rationally. They can identify “undervalued” pieces of content that should get more traffic and overvalued content that is subsidized. More importantly, they could bid for traffic with confidence because they know in real-time how much each user is worth. By removing the ambiguity about pricing, our novel content valuation method could provide the foundation for a major increase in trading in markets for online traffic, in the same way that the Black-Scholes option pricing formula increased trade in derivatives markets in the early 70s.

Conventional Metrics Fall Short, A New Metric Can Solve an Old Problem
The online analytics industry has been distracted by a different question: how can we identify different types of users and get these different groups to see our content? However, they skipped the most important question: how much is each of these users really worth to us? They simply do not know.

The revolution in big data allows the creators of online content to track lots of different metrics, even in real-time, about the behavior of users. The key of course is to look at the right metrics. If you’re looking at a metric that has no direct relation to the bottom line, or you don’t understand that relation, then it’s probably not a great metric.

For a full analysis, read our recent white paper entitled “Asset-Valuation-Based Ranking: Bringing Economics to the Web” authored by JumpTime colleagues Anke Audenaert, Andres Rodriguez, Tomas E. Uribe and myself. - Hanno Lustig

ABSTRACT:  We develop an economics-based approach to the ranking of internet content by valuing the content as assets that produce streams of cash flows. We do so by computing the dollar value of an additional visitor landing on a given page. This dollar value comprises not only the current immediate revenue generated on that page (which is what existing methods focus on), but also the expected future revenue, by taking into account the role of every page as a node in the web graph. The dollar value of content thus reflects its ability to keep visitors engaged, generating further revenue.

We present an algorithm to compute this valuation, assuming that the average Web surfer transitions between pages are Markovian. As a result, we obtain a simple recursive characterization of each page’s value that can be computed in real time from an updated transition matrix. These values can then be used to promote content, bid for keywords or ad impressions in auctions, and develop pricing for content and traffic.

To validate the benefits of our approach, we use simulations and analysis based on actual data. Using the random surfer model, we estimate the potential benefits of an ‘optimal’ traffic optimization policy using our valuation methodology. We provide additional support by analyzing (and simulating) data from two large internet properties. We find large revenue and engagement increases relative to the baseline and a ‘myopic’ policy, which uses only current revenue to rank content.

In many cases, proxy metrics provide insights into quantifying the size of an audience, but not much about the full economic value of that audience. As more and more brands take advantage of Content Marketing, new and more comprehensive value-based metrics will be needed to measure the effectiveness of content-based marketing.

JumpTime works hard to help marketers understand and manage the comprehensive value of their content assets. We address this in two primary ways — first we look at both engagement AND revenue, as we believe they tell equally important stories. We also look at the immediate value and well as the downstream value of every piece of content, to help marketers understand the most valuable assets in their network. This is all done to deliver what we believe content marketers of the future will need: a content value managment system.
- Michele DiLorenzo

Established in 1986, the SIIA CODiE Awards recognize excellence in the business software, digital content, and education technology industries. All nominated products and services are extensively reviewed by judges with deep industry expertise. CODiE finalists represent companies who are developing the applications, services, infrastructure and tools that are driving the software and services industry forward.

JumpTime provides content value management solutions that help publishers and marketers define the true value of their content assets, increasing the ROI for their business operations. JumpTime was founded by a leading economist, the former head of research for Yahoo, an expert in artificial intelligence, and a media veteran from Viacom, MTV Networks and Virgin Interactive.

The Traffic Valuator suite is based on “FloPower,” JumpTime’s proprietary valuation algorithm that calculates the revenue and revenue potential of every piece of content in a network, in real time. FloPower recognizes that content has two jobs to do: 1) meet user needs, which delivers immediate financial value and 2) drive users deeper into the experience, which delivers future financial value.

Media and entertainment companies are using the Traffic Valuator suite to inform product development, partnerships and pricing decisions, and seeing significant lift in engagement and revenue.

“We are honored to be recognized by the Software & Information Industry Association. The CODiE Awards have long been a bellweather of innovation and creativity, and we are proud to be named a finalist along with other leading business software companies,” said JumpTime co-founder and CEO Michele DiLorenzo.

Last week, DiLorenzo presented “Moneyball for Media: Unlocking ROI with Content Value Management” at Federated Media’s Signal: San Francisco event.

About JumpTime, Inc.
JumpTime is a Los Angeles-based technology company whose patented FloPower algorithm solves the problem of monetizing high-quality digital content. JumpTime provides Content Value Management solutions that help publishers and editors define, measure and manage the value of their business and product decisions. The Traffic Valuator™ suite delivers decision-support tools that maximize revenue and engagement. Clients include Hearst Newspapers, msnbc.com and The Nation. For more information, visit http://jumptime.com/.

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Press contact:
Christine Mohan
christine at jump-time.com
718-308-6467