Posts Tagged ‘Guest Post’

Phillip Smith is a digital publishing consultant who focuses on news innovation, specifically “the technology and ideas that are shaping how users interact with journalism online.” You can find him on Twitter and at

Phillip Smith Chartbeat

When I created my first Chartbeat account back on March 23, 2010, I didn’t anticipate that just a few short years later I’d be asked to host a talk at Chartbeat’s NYC HQ to explore how publishers are going “Beyond the Click” to get to actual engagement.

I also didn’t anticipate the impact of that event on my thinking about the nexus of publishers, the technology companies working in the publishing space, advertisers and media buyers, and — most importantly — the engaged users.

At the conclusion of the event I had a good hunch that this loose collection of ideas and initiatives, which fall under the heading of “new metrics for publishers” — happening very openly at companies like Chartbeat and Disqus, but also unfolding in newsrooms around the world — was likely to be a key theme in 2014, along with unprecedented technology innovation in newsrooms, the disruption of the existing advertising models,  and the changing demands of users.

Phillip Smith Chartbeat

Publishers take center stage on the Web

If you take it as face value, recent research tell us that roughly 78% of adult internet users in the U.S. go online to “get news.” Add to that some of the other main reasons that people go online — e.g., “to look for information about a service or product they are thinking of buying” or “to find information on a hobby or interest” — and you’ll find that online publishers are often providing that information too.

This puts publishers in a very enviable position, I would propose, as the producers, purveyors, curators, and gatekeepers of much of the Internet’s most sought-after commodity: fresh, timely, contextual, and relatively-objective information. One by one, publishers appear to have navigated their ships’ course to adapt to the changing landscape. They are focusing attention on a new, quickly evolving role as the central marketplace of information, attention, and engagement.

Newsrooms as software innovation labs

More interesting still is the relatively new trend of publishers investing in digital staff that are not stuck in the outdated role of “IT.” Working at a distance from those folks that are managing the servers and infrastructure, these new “news apps” and “good Internet” teams are embracing experimentation. They are pushing the envelope of what users have come to expect as “content” and “information.” The outcome is new forms of journalism and storytelling that invite the user to be more engaged, whether through data, interactivity, or awe.

One side effect of these investments is a quickly-maturing technical acumen in newsrooms and a wealth of contributions back to the open-source software community — the same community that helped to make much of the innovation possible in the first place. A natural feedback loop is born: more technical innovation and open-source contributions by newsrooms lures more talented developers away from other sectors, and more talented developers often means more innovation in those same newsrooms.

Another upside of this publisher-driven innovation, is the pressure it exerts on the ecosystem of technology vendors they collaborate with, compelling those same vendors to evolve their products more rapidly and to open up new ways for programmers to work with their products.

Disruption of the display advertising model

Pressure is also being exerted on many of the players in the traditional online display advertising space, in many parts due to the experiments that online publishers are undertaking.

For example, just one factor out of several — the increased consumption of online content on mobile devices — has meant that forward-thinking publishers have all but eliminated traditional display ad formats from their now “mobile first”  Web properties; the lonely “big box” display ad is almost all that remains in many recently launched “responsive” sites that aim to provide an all-in-one experience for readers arriving from phones, tablets, laptops, or desktops. The Boston Globe,, and NPR are good examples.

Other pressures, like low reader engagement with display advertising, and the complicated web of ad-delivery networks, slow ad-serving technologies, and the increasing practice of “programmatic buying” that sidesteps the publisher’s sales team, have lead to a wave of publishers experimenting with new ad formats that fall under the term “native advertising”  (or “sponsored content”), where the distinction between advertising and content blurs considerably. However, almost overnight, publishers have bootstrapped their own solutions to two challenges: ad formats that adapt well to the mobile reading experience, as well as, in many cases, increasing reader engagement. Some recent numbers suggest that as many as 3/4 of online publishers in the U.S. are now offering native advertising.

These shifts away from timidly accepting what technology vendors have to offer, or what advertising agencies are pitching, and toward producing in-house solutions to the challenge of increasing their readers’ satisfaction and engagement exemplify publishers pushing the envelope at a time when they’ve come to see the role they play as one of the convening places on the modern Web.

Users start to pay for content, but want privacy too

At the other end of these shifts, however, are some established technology companies making quick moves to address these new challenges head-on with their existing products. For example, Chartbeat’s push to create a new metric for publishers, “Engaged Time” is one great example (and they didn’t ask me to say that!). Thought leadership is coming from all directions, and it is often touching on this intersection of publishers, advertising, and users.

There is, generally speaking, a surge of analytics and “big data” technology coming onto the market that is aimed at helping online publishers make sense of their mountain of accumulated “user data.” A focus of many of these new analytics platforms is to help publishers understand their audience better, as well as which content performs the best, and publishers are increasingly in the position of making tough decisions about which visits matter to them most when they decide where to invest their editorial budget.

One voice is still often missing, however, or perhaps it is one billion voices: the end-user, the news consumer, the reader, the individuals who use the Web. This coming year, I predict, is going to be about the unfolding story of a new contract between readers, publishers, technology platforms, and advertisers.

 The continued, and relatively successful, introduction of pay walls at mainstream news sites, experimental subscription strategies at the heart of a new bread of entrepreneurial journalism initiatives, and the continued success of “crowd funding” to help support expensive types of journalism all point in one direction: publishers will rely less on “selling users to advertisers” as the exclusive strategy for financial sustainablity.

At the same time, however, users are growing leery from the ongoing revelations of the invasions of their privacy by the companies they once thought were infallible, and thus many are growing more reluctant to unwittingly hand over their information. Practices like programatic ad buying, which make online tracking more directly evident to end-users, and efforts like Mozilla’s Lightbeam for Firefox, which shine a light on how much data is being shared, and with whom, will continue to push users to ask for more privacy from publisher, advertisers, and platforms.

The dynamics at play above — publishers, technology platforms, advertisers, and users — and the tensions being exerted as each one tries to optimize their online experience — whether it’s sharable content, ad delivery, better metrics, or more privacy — is why I’m predicting that “the ascendance of publishers and users” will be a key narrative of the Web in 2014.

What do you predict will happen in online publishing in 2014? Do you agree with Phillip’s predictions? Share your ideas in the Comments below.

It’s easy to get excited about metrics, measuring content effectively, and the related tools and features that accompany these advancements in thinking and strategy. That said, it’s always nice to take a step back and think about how journalism in the context of analytics is evolving in a broader sense. Tow Fellow Caitlin Petre frames some interesting ideas about quantifying journalism in her blog post for the Tow Center blog, and we’re reposting it here for you all to enjoy. Throw your ideas in the Comments section – we’d love to hear what you’re thinking.

This post originally appeared on the Tow Center for Digital Journalism Blog on October 30th, 2013.

Journalists are seeing an explosion of quantitative data about how readers interact with what they write. To date, much of the conversation about metrics and news has focused on the dangers of using metrics to guide news judgment or, on the other hand, the risks of ignoring metrics completely. But crucial empirical questions about how metrics are produced and put to use remain largely unanswered. How do analytics firms measure complex qualities like engagement, make predictions about the future performance of content, and communicate with journalists about the value of metrics? And how do journalists at different types of news organizations use analytics in their day-to-day work? Are increasingly sophisticated measures of stories’ performance shaping journalists’ ideas about what is important, interesting, or newsworthy? Has the availability of such data changed the internal dynamics of news organizations?

These are some of the questions I aim to tackle in my Tow project, using qualitative methods, such as ethnographic observation and in-depth interviews, to better understand the development and use of metrics in an analytics firm and two news organizations. But before I can answer these questions, I have to ask a different one – one that is as dreaded in my field (sociology) as it is common: What is this a case of? Even though researchers have a tendency to become infatuated with the most minute details of our subjects, what we’re ultimately trying to do is identify and account for patterns in the social world. The classic “what is this a case of?” question prods us to zoom out, to put things in context, to consider the broader implications of whatever it is we’re studying.

So, what are metrics a case of? While there is a burgeoning movement to measure journalism – especially non-profit and investigative pieces – more qualitatively, most metrics categorize and count – page views, unique visitors, time on page, drop-off rate – with the aim of comparing things: pieces of content, news organizations, authors, readers. Metrics, and the big data trend of which they are a part, represent what philosopher Ian Hacking calls “an avalanche of numbers” made possible by astonishing advances in the ability of computers to collect, store, and process huge amounts of data. And metrics aren’t the only numbers in the avalanche – more and more journalists are now deriving stories from their analysis of quantitative datasets.

Sociologists Wendy Espeland and Mitchell Stevens have argued that quantification, like speech, is “a social action that…can have many purposes and meanings” that arise and shift through use. Scholars who study quantification have sought to uncover these purposes, meanings, and uses: here are two ideas from their research that can guide our thinking about the role of numbers in the production of contemporary news. The first concerns metrics, the second concerns the growing prevalence of data journalism.

  • Numbers can discipline, even in cases where they aren’t intended to. Michel Foucault famously argued that statistical measures have been used in attempts to control and “normalize” populations that were considered deviant. But sometimes numbers that were meant merely to measure inadvertently serve a disciplining function. U.S. News and World Report’s law school rankings were designed to provide prospective students better information about schools they were considering, but Wendy Espeland and Michael Sauder discovered that law school personnel internalized these measures, and began to change their admissions and financial aid policies to better conform to them. In other cases, however, the implementation of quantitative accountability measures faces considerable resistance and resentment, such as in Tim Hallett’s ethnographic study of the faculty at an urban elementary school. My preliminary research (as well as work by C.W. AndersonPablo Boczkowski, and others) suggests that both internalization and resistance are present in journalists’ response to metrics.
  • Numbers can establish trust where it is lacking. Historian Theodore Porter has argued that because of numbers’ longstanding association with rationality and objectivity, quantification can be a useful “strategy for overcoming…distrust,” especially in professional fields that are susceptible to outside criticism. At a time when public trust in journalism has dropped precipitously, then, we might expect the standards of journalistic evidence to become increasingly quantitative. As Tim Berners-Lee puts it in The Data Journalism Handbook, “it used to be that you would get stories by chatting to people in bars, and it still might be that you’ll do it that way sometimes. But now it’s also going to be about poring over data and equipping yourself with the tools to analyze it and picking out what’s interesting.”

Contemplating the increasingly important role of quantitative data in journalism also leads us to interesting questions about the idea of “objectivity,” and specifically about the relationship between scientific and journalistic definitions of this term: How do they overlap? Where do they conflict? If we are indeed seeing a quantitative turn in journalism, will it push these two conceptions of objectivity to be reconciled? These are questions I’ll address in future posts.

Caitlin Petre is a Tow Fellow working on a project on Metrics:Production and Consumption for the Tow Center for Digital Journalism.  The Metrics:Production and Consumption project is made possible by generous funding from both The Tow Foundation and the John S. and James L. Knight Foundation.  To learn more about the Tow Center Fellowship Program, please contact the Tow Center’s Research Director Taylor

Our guest blogger today is Michael Lovitt, VP of Engineering at Vox Media.

Last month, Vox engineers spent three days at Chartbeat’s NY office hacking on digital ad measurement. I want to share Vox’s take on the current state of online advertising and tell you how and why we’re working with Chartbeat to make things better.

The current state of online advertising

The state of digital advertising — and brand advertising, in particular — is suboptimal. In short, as an industry, we’re showing ads that readers don’t want to see and measuring using techniques that don’t tell us enough about whether ads are successful.

The good news, from our perspective at Vox Media, is that digital advertising has enormous room for improvement. We believe that by designing beautiful ads that delight instead of annoy, elegantly integrating these beautifully-designed ads alongside premium brands and content and for a premium audience, and employing measurement techniques that reveal a complete picture about who viewed an ad and to what degree readers engaged with and were influenced by it, that we can provide an advertising experience that does a better job of pleasing everyone involved: publishers, advertisers, and readers alike.

We’re making progress on all of the above, but solving these problems isn’t easy. It helps to have great partners.

Solving problems with Chartbeat

On measurement in particular, we were excited to work directly with Chartbeat because, like us, they’re convinced that the current state of digital ad measurement is not good enough and are actively working to make it better. Of course, Chartbeat is in the business of knowing how users engage with websites, and they’ve started to put that expertise to work tracking ads. (We had nodded our heads all the way through reading their recent blog post on the superiority of Engaged Time over impressions and clicks and awesome study showing a strong correlation between Engaged Time and brand recall.)

We’re also passionate (OK, addicted) users of Chartbeat’s products. Screenshots of important Vox milestones as visualized by Chartbeat litter our Campfire transcripts. These people do awesome work and it’s fun to hack with folks whose work you admire.

For all of these reasons, when Chartbeat invited us to attend one of their Hack Weeks, we immediately said yes.

Pre-hack planning

The Hack Week invitation was made at an opportune time, as Vox had just released an early alpha version of a new ad product metrics dashboard. The system was still in its early stages, but it was functioning in at least a basic way at every layer, and it served as a foundation for us to hack on.

We arrived at Chartbeat with a mock of a few changes to the dashboard — we knew we wanted to start reporting, for every ad, both the Average and Total Engaged Time. As Chartbeat has shown, Engaged Time correlates well with brand recall, so being able to provide this level of insight to our advertisers and to ourselves would be one important step forward in moving beyond standard clicks and impressions

So we came with one concrete thing that we wanted to accomplish (having validated the idea with Chartbeat beforehand to make sure what we had in mind wasn’t crazy); beyond that, we were ready to play it by ear.

Hack, hack, hack

Here’s a quick rundown of what happened during our three days at Chartbeat:

Trei, Niv, Pablo, Aaron, and I arrived late Wednesday morning and kicked off with a short presentation to the Chartbeat team about Vox, and then settled into Chartbeat’s Stark Tower conference room and got to work.

We sat down with some of the Chartbeat team — Harry, Matt, Wes, Shaun, and Alex — and reviewed the dashboard mock. It turned out that Chartbeat’s existing ad product would be sufficient to record all the data we needed, but that a new API would need to be built to return that data back to us. Vox engineers got to work adding Chartbeat tracking to Vox ads, and Chartbeat engineers started building out the new API.

By the end of the first day, we had a Chartbeat-instrumented Vox ad running in production and a new Chartbeat API running on a laptop and returning data from Chartbeat’s production data store. From there, we could run our metrics dashboard in our dev environment and start to see real data flow in. Hurray!

On the second day, we solidified what we had built the day before. We wrote the front-end code to beautifully display metrics on the dashboard and got the Chartbeat API running on a server on the web so that we could push our metrics dashboard changes live.

Since we were making good progress on our primary goal, we also took some time to hack on Chorus, Vox’s publishing platform. We used an existing production Chartbeat API to integrate real-time Chartbeat metrics into the Chorus layout editor — so that, for example, an editor on Polygon, when deciding what stories should be placed on the home page, can easily see the current visitor count on each currently-placed story.

The morning of the third and final day, we asked ourselves if we could get one more metric, Engaged Concurrents, integrated into the dashboard before the 1pm demo. It seemed feasible so we tried and got it done.

We showed off what we had all built to the Chartbeat team over pizza. After declaring total victory, the Vox crew said goodbye and stopped for celebratory drinks while we waited for our train back to DC.

Closing thoughts

We had a blast hacking with Chartbeat. It’s fun to make things with smart people, especially when they’re focused on the same problems as you are. Beyond ad measurement problem-solving, we enjoyed getting to know the team and talking shop: approaches to team organization, benefits and trade-offs of remote versus centralized workers, respective merits of modern JavaScript frameworks, and on and on.

Finally, we’ve been able to maintain post-hack momentum and have made great progress taking these projects to completion — an important final step in any hackathon, and especially a cross-company hackathon like this one. Chartbeat has already released the APIs they built during our visit into production and we’re working this week at Vox to update the API client code in our metrics dashboard.

Now that we have this ad engagement data, what’s next? To start, we’ll be using this data internally to better understand how well our ads are performing — by feeding it into our ad design process, measuring ad performance, and iterating. We’ll consider this data alongside other metrics that reveal how users are viewing and interacting with our ads. As we continue to take on the hard problem of optimally measuring digital ads, we look forward to having partners like Chartbeat at our side.


PS- Check out Chartbeat CTO Wes Chow’s guest post for the Vox Product blog.

What’s your story Dion?

My background is in software engineering, and in the past I’ve specifically done things in the pre-Android/iOS mobile space, worked on both the consulting and sales engineering sides of the fence and been a Solution Architect helping plan large technology deployments. Now I’m VP of Engineering at CreativeWorx where my days are spent architecting applications that put data and analytics about how our customers’ work in their hands.  I’m also a volunteer for the Coalition for Queens where we are working hard to build a tech ecosystem in Queens that supports the growth of tech in my home borough.

Where did you first learn about Chartbeat?

I was at a MongoDB Meetup maybe two years ago when I first saw the work Chartbeat was doing. I had limited knowledge of MongoDB, so I started attending Meetups to learn more about how companies were using it. When I was first introduced to MongoDB in its earlier days, there was a lot of skepticism – a lot of my colleagues weren’t convinced it would survive.

Chartbeat stood out at this Meetup because you guys were pushing for real-time decision making based on large volumes of data. Seeing how you were helping companies conduct business around these large data sets, getting real-time feedback from a large audience, making in-the-moment data-based decisions was all very interesting to me.

How has the MongoDB work Chartbeat is doing influenced your own work?

More so than other companies, Chartbeat showed me that you can achieve goals in MongoDB that would normally take a lot of infrastructure and complex technical overhead to implement. What Chartbeat was doing with MongoDB destroyed a lot of the assumptions and skepticism I’d inherited from people who weren’t familiar with using MongoDB. After that Meetup, I just dove right in and started learning it.

Chartbeat’s MongoDB work led me to start building applications with it and test the tech’s true potential. In the end I really did enjoy switching from the world of traditional databases to a set of data where I can do anything I want.

With MongoDB, I have to accept responsibility for maintaining on the application level some of the rules that traditional databases have baked in but in return I have the control to use and alter that data to build more scalable and higher-performing applications.  It creates a world where I feel you are truly constructing your data to best serve your application and not trying to have your application be driven by the database’s rules.

What advice would you give to people considering working with MongoDB?

First piece of advice I would give is download it, read the SQL to Mongo Query table and give it a try. Building a simple application that just queried and inserted data was enough for me to really understand how I could use it. And when I say use it I mean use it as its intended building a document instead of a traditional flat row. There are many videos online about MongoDB Schema Design which will help you understand the advantages and new ways of thinking when building applications with the freedom of a document database.

The second piece of advice is with all my praise MongoDB isn’t necessarily right for every application. While I love how easy it is to scale the tech and how fast it is, if you are building a system that relies heavily on transactions you will be challenged. By that I mean systems that require an all or nothing approach to updating several pieces of data will find that there currently isn’t a solution for grouping together a set of updates and only doing a commit if all of them can be done successfully. As you can imagine there are creative ways to get around this depending on your situation by using nested objects so the changes are in one document or building your own rollback into your application but these choices may not be realistic for your application.

Third is get involved in the community. Tech is in a pretty amazing place now as compared to where it was when I first started my career. Companies are so open and helpful today in the ways they share their success and failure. I recently attended MongoNYC and was shocked that I was sitting in a room listening to a presentation from Goldman Sachs about not only how they are using MongoDB in house but how they built their architecture to easily spin up dev and production environments for developers to build applications.

If you aren’t involved in the rising community of tech you are really missing out.

Chartbeat is just one of the many companies that are using MongoDB to solve the big data problem and I’m glad you and others are sharing your experiences with the tech community.

Anna Li will be graduating with an MA in Journalism from Stanford next month. She focuses on multimedia reporting and digital journalism with an emphasis on data visualizations, photography and visual storytelling. She visited the Chartbeat HQ back in March, and was awesome enough to share her impressions on our blog. You can get in touch with Anna via email, or post your comments below.

My team of graduate journalism and computer science students from Stanford University visited Chartbeat’s office, a few blocks away from the bustling Union Square in Manhattan, to learn about the start-up’s latest projects.

For the past three days, we had visited top-tier publishing companies in New York, many of which use the Chartbeat Publishing dashboard on a daily basis. I had heard good things about their real-time analytics, valuable for making editorial decisions on the web.

Chartbeat’s team didn’t disappoint.

Data Scientist and self-identified “machine learner” Josh Schwartz showed us Engaged Time, a metric that measures the amount of time an audience is actively consuming content. Engaged Time correlates with a reader’s likelihood of returning to a specific site. Loyalty to a site is a concept often discussed but rarely effectively tracked because it’s difficult to accurately determine a loyal online user.

In the days of print newspapers, a loyal reader might be a subscriber who has had the same paper delivered to the same address for twenty years. Today, it’s harder to tell. How many people are actually reading the articles? Are they coming back? What can I do to increase the odds of them coming back tomorrow?

Alex Carusillo, Chartbeat’s advertising product guru, self-titled as “smash brother” on Chartbeat’s website, shared insights on what he believes advertisers placing ads in print and online newspapers are seeking.

As part of my team’s visit, we shared an innovative project we’re working on at Stanford. My team is building a system that allows publishers to better understand their published content and who is reading their news articles by tagging news articles and incorporating social data about readers. Josh, Alex and Suneet Bhatt, VP of Marketing, provided great feedback for our project.

Looking ahead, we’re hoping there will be opportunities to partner with Chartbeat. It was a great experience — I certainly learned a lot about pain points in the journalism industry, through the lens of a start-up focused on connecting the business and editorial sides of online publishing through actionable, universal metrics.