February 14, 2012

Editor’s Note: This is the second post in a new Q&A series with Parse.ly Dash customers. Every other week we’ll feature an awesome publisher that’s using Dash and dig into how they’re making use of freshly grown insights.

Parse.ly recently interviewed Christian Lowe, Managing Editor at US News & World Report, and Carson Smith, Web Analyst at US News & World Report, to gain a better understanding of how they’re using Dash to inform editorial decisions. Data has long been at the foundation of US News, and as is such we were eager to learn how our publishers-built tools and data insights performed in the hands of data-hungry infromavores. Read on to see what Christian and Carson have to say about data and editorial intuition, the analytics playing field, and specifically how they’re leveraging Dash at US News.

The Thoughts of Christian Lowe, Managing Editor

Parse.ly: What type of advantage does Dash give you?

Christian: Easy UI, ability to check immediately what content is doing well–both internally and externally—and why it’s doing well.

Parse.ly: What are some of the primary use cases for Dash at your publication?

Christian: Check trending stories and past story performance. Chart referrers. Make editorial decisions based on global story trends.

Parse.ly: How often are you and/or your team using Dash on a typical day? Are you in the system constantly? Do you check on an case-by-case basis? How is it integrated into your workflow?

Christian: I have Dash running all day from the moment I log into my workstation to the minute I leave. I’m near constantly checking the performance of our content and am benchmarking against past performance. I also have started to look at Macro trends like overall site traffic etc.

Parse.ly: What’s your favorite story (crazy, funny, surprising, etc.) about using Parse.ly?

Christian: Using Dash’s “Worldwide Trends” function, we noticed midway through the day that the search terms Vladimir Putin and McCain were trending high. Within 45 minutes from assignment to posting, our story on the controversy was the top result in Google search on the subject.

Parse.ly: What new features would be most useful to your business?

Christian: I would like a more accurate way to dig down into the referrals. For example, I can see that a story had traffic from, say, Yahoo News, but I can’t see whether that traffic came from an internal link within a previous story in Yahoo, or just a stand alone URL on the Yahoo News page.

I would also like a more robust realtime metrics page which shows which posts are trending and where the traffic is coming from. I don’t care so much about topics or keywords.

Parse.ly: What are some tips you would give to a peer about using data and analytics to make editorial decisions?

Christian: Let the data inform your editorial decisions, don’t let them drive your content.

Parse.ly: Do you use Dash more for getting more value out of existing content, help determine what new content you should create, or to evaluate performance of authors, topics, posts, etc?

Christian: Again, I don’t really use the topics data – we already know what topics we’re going to write on. We need to find out what sorts of stories within those topics are working or not and why. I also find the ability to input URLs and evaluate specific stories very useful.

Parse.ly: Do your writers use Dash at all? How has it affected the way they choose, or find, stories they want to write?

Christian: Not yet, but I am going to selectively give access to some of them. I’d like there to be a way to customize how much data each sign in can get.

The Thoughts of Carson Smith, Web Analyst

Parse.ly: Why did you choose to use Dash at your publication? What were the pain points or opportunities you were trying to address?

Carson: The learning curve for enterprise analytics solutions can be steep. While basic information like top pages were accessed frequently by editors, more advanced features often went ignored.

Dash gives our editors the power to easily access insights that were either not available or required an analyst.

Parse.ly: I’m sure you use or considered using other products. How did you decide on Parsely Dash?

Carson: At first I compared Dash directly with some other real time analytics products. But I realized it’s fundamentally a different tool. In addition to real time, it’s both backward and forward looking.

Parse.ly: What type of advantage does Dash give you?

Carson: Dash’s focus on action-oriented insights over data dumping gives it a big advantage over traditional tools. Our editors want to know why something happened and what will happen. Dash helps answer both questions quickly.

Parse.ly: What are some tips you would give to a peer about using data and analytics to make editorial decisions?

Carson: Don’t throw intuition out the window. Use analytics data to hone your instincts so your intuition becomes more reliable.

Parse.ly: A lot of people are talking about different types of data journalism, but few people are really doing it. As one of the early movers on this trend, what is the most important lessons you’ve learned?

Carson: Data has long been a foundation of US News’ journalism, but not until recently have we been inundated by so much of it. An important lesson is to identify what data really matters for our business and readers. Analytics tools help to sift wheat from the chaff.

Thanks to Christian and Carson for providing their insight!

• Tags
• qaseries
• dash
• usnews

By: Sachin Kamdar

Over two years ago, Parse.ly graduated from the then Philadelphia-based (now in NYC and Israel) accelerator, DreamIt Ventures. At DreamIt we planted the seed of an idea that grew into the Parse.ly Reader, an intelligent news reading application that got better as you used it. Parse.ly Reader was successful – it grew in size to several thousands of users in a matter of weeks and had great reviews (ReadWriteWeb, ZDNet, Louis Gray, Thrillist, to name a few).

However, we knew what we built had the potential to not just change the way people consumed content, but how content was created and delivered.

New Yorkers at heart, we came back to the city after DreamIt, itching to contribute to one of New York’s biggest industries – media. Some of the biggest and best publishers on the web call NYC their home, and virtually all of them are looking to leverage new technologies that push the boundaries of traditional content sites.

Several months and meetings later, it was clear that publishers were entering the age of big data – billions of pageviews, millions of readers, thousands of active pages, hundreds of writers and editors. Despite all these signals created by the web, there was a big gap in the tools available to leverage them.

The Early Days

Initially, we thought the problem at hand was content delivery - which is why we built the Parse.ly Reader. The Reader was built to understand a user’s interests, and evolve with the user as his or her interests change. On the web, there were clear examples of other technology companies leveraging personalization technology to fine-tune a user’s experience (Amazon/products, Netflix/movies, Pandora/music). Yet, when it came to content, most online publishers were treating each user the same.

This was our initial Aha! moment and with confirmation from the publishers we were talking to, we were off to the races. We built P3, the Parse.ly Publisher Platform, to deliver personalized recommendations of content to users based on a slew of inputs, ranging from the context of the current article to what other, similar users were interested in. We launched on a few publishers including a top 100 news site and were increasing engagement and readership across the board.

Then, a curious thing happened…

It’s The Data, Stupid!

Some of our publishers started to ask us how we were recommending content. Editors, in particular, were really interested in how we decided what article to show to one user versus another. So, being the tech geeks that we are, we began explaining the whole stack:

• We analyze all content on your site to understand exactly what each post is about from a topic perspective
• We measure reader interest across these topics and start to build interests graphs between users
• We look at topic, post, and author velocity combined with referral information to give us cues on what might pop
• We mash up the treasure trove of data that’s on your site to come up with recommendations that your users will love

Specifically, editors at separate organizations asked us the same question: Can you share some of that data with us? You know, the topic data and the data on authors?

Begrudgingly, we agreed, and started to send out reports on a monthly basis.

Editors: “Hmm, this is great! Can we get this quicker?”

Parse.ly: “Uh, sure. We can give it to you weekly.”

Editors: “Awesome! Actually, it’d be great if we could get this daily.”

Parse.ly: “OK, what’s up here? Why do you care more about the data than the recommendations?”

Well, as it turns out, nobody had really showed them this data before, and the data was simply eye-opening for the editorial team. They were using it to go beyond monitoring individual articles to understanding what was resonating with their audience.

Queue the second Aha! moment in early 2011. We took a step back and did some research on analytics tools for online publishers. What we found was astounding. Almost no innovation had happened on the analytics side for online publishers. Most tools were one-size-fits-all systems that treated an e-commerce site the same as a content site, and obviously, that’s not the way to do it.

Content-based sites are dramatically different than an e-commerce property from both a data and business perspective.

It’s no wonder these publishers were clamoring for data that provided fresh insights on their property. Publishers need to know how their content breaks out by topic, what causes a post to go viral, why one author does better with search traffic than another, and a bevy of other key insights that are specific to their needs. We knew this was a big opportunity, and decided to dive head-first into the analytics space.

Meanwhile, In The Workshop…

2011 was the year Parse.ly Dash was born. We quickly built a bare bones tool to surface some of the data that we were collecting for publishers in the early months of 2011, and released it into private beta shortly thereafter. The response after showing a few major publishers the first version of Dash was both invigorating and a bit unexpected.

Not only did they understand what we were building, but they were extremely vocal with feedback that helped shape and evolve Dash throughout the year. This feedback can be summarized through three key areas that represent he biggest opportunities for improvement:

• Tracking. Publishers had tools that tracked data, but unfortunately they were not tracking the data that these publishers really cared about. Key metrics around topics, authors, sections, referrers were just not available. Luckily, our backend technology was built to pick up on exactly these areas.
• Planning. Tracking wasn’t enough to really be competitive in the media industry. Publishers needed to be proactive around topics that were trending on their site and across the web. Further, they needed tools that look at what would happen in the next several minutes, hours and days. We spent many engineering resources developing technology that would measure trends local to a property against trends that are happening across the entire web. This allowed publishers to not just identify patterns, but actually understand what was causing them. This has become invaluable for many of our customers.
• Promoting. As social media became a major distribution channel for content, so has the need to understand exactly how content goes viral and who on the social web has the most influence. Marketing to the right audience and in the most effective way is incredibly important to publishers moving forward, and Dash gives them this capability by actually plugging directly into the biggest social APIs.

We are also proud to say that Dash has offered a humane interface for analytics. We built the product with the user in mind. Most analytics tools are clunky, have a steep learning curve, or don’t go far enough with their analysis. Dash is different. It’s beautiful to look at, simple to use, and almost unassumingly powerful. The data, and as a consequence the insights, are what shine here.

Finally, Dash was built with the understanding that most publishers aren’t interested in doing heavy integrations. We make it a snap to integrate with Dash. You simply drop a Javascript include on the footer of your site, and we give you the most powerful analytics tool on the market in about a week. Really, that’s it. No coding, customization, or painful backend integrations required!

Without further ado, meet Dash

I’d like to invite any publisher who’s interested in trying out Dash to do so. We offer a 30-day free trial and tiered pricing to match your size and needs.

Thank You

I’d like to thank our early pilot customers. You’ve been incredible to work with, and have provided us with invaluable feedback. We’ll continue to work tirelessly to give you the best analytics tools on the market.

I want to thank our investors and advisers for giving us the resources, experience and insight to capture this opportunity and many more in the future.

And of course - a big shout out to the Parse.ly team.  I’ve lost count of the tireless hours and late nights that have gone into Parse.ly Dash — from the earliest days in 2009 to present. The team here is inspiring to work with, and I can’t wait to keep pushing online media forward.

There’s much more work ahead of us, and we’ve already started on the next phase of Dash, so stay tuned for latest updates and more from the team, right here on the blog, or you can follow us on Twitter.

• Tags
• parsely
• dash
• launch
• dreamit

You may have seen that Parse.ly was featured in a TechCrunch article a couple of days ago. It was a great writeup by Sarah Perez, and we wanted to share it with you here.

Parse.ly Will Launch Its Pageview-Generating Machine Called “Dash” This Month:

http://techcrunch.com/2012/01/03/parse-ly-will-launch-its-pageview-generating-machine-called-dash-this-month/

The article actually includes a few screen shots of Dash that had not been seen before, so this is really the first public look at Dash. Now that it’s out in the open though, we encourage you to take a look!

Here’s a quick summary of the article as well: 

Parse.ly has been in stealth mode, but we’ll be launching Dash publicly this month. We have had an amazing group of early adopters that have helped us tweak Dash until we got it just right. Now, we have a fine tuned product that is designed specifically for large-scale content publishers…the biggest publishers in the world honestly. Dash is designed to help publishers maximize their pageviews by surfacing insightful trends and directly actionable opportunities. We’re taking predictive analytics into new territories. 

There’s much more to Dash, and you’ll be hearing more about it very soon. For now, definitely check out the TechCrunch article. Say hello and follow us on Twitter for more updates! 

• Tags
• TechCrunch
• Parse.ly
• Dash
• Predictive Analytics

Parse.ly Dash - Insights for the web’s best publishers…

Sounds great right? But who are some of these publishers and what type of insights can you expect from Parse.ly? Well, you’ll have to wait just a bit longer for a full answer, but here’s what we can tell you now….

Our semantic analytics have been breath of fresh air to editorial, audience development, analytics, and ad sales teams at some of the biggest content publishers on the web. We are finishing up what has proven to be a very successful pilot program and are really excited for the public launch of Dash (coming very soon!). 

We’ll have much more info to come, so make sure you check back with us, or drop us a line now. We’d love to hear from you.

 

• Tags
• Parse.ly
• Dash