Posts Tagged ‘Data’

Watch This: Chartbeat Data Science at DataGotham 2013

October 23rd, 2013 by Juliana

Chartbeat Data Scientist Josh Schwartz spoke a few weeks ago at DataGotham about his series of lab studies on how users read content – and how that research drives insights across our network.

You can now watch his talk in this blog post or on YouTube and get the scoop on what we're cooking up these days in the Chartbeat Data Science Lab.

Got a question for Josh? You can reach him here.

Listening to the Data

October 9th, 2013 by David

As a former sound studies student and radio/music/audio geek, I tend to think a lot about the various aural phenomena I confront on a daily basis. On the job, it’s mostly the gentle roar of Broadway and the whisper-quiet discussions of my Chartteam colleagues hard at work…  Thankfully the Chartbeat record player is actually a thing and we’re slowly building out our library (thanks to @tovah at the Lansing State Journal for the killer batch of vinyl!).

we keep the Dylan records as chew toys for the office puppies

Ok, but when I’m not burying everything in headphones full of blissful fuzz I’ve got to listen to what’s going on around me and filter out the signal from the noise. It’s a common problem; one that Chartbeat’s data science team confronts everyday. When you’re looking at a large dataset it can be tough to pick out the useful bits, so you graph them out, relying on your eyes to pick out the anomalies (obviously there’s much more to it than that, but I’m not the data scientist ‘round here, so let’s just let bygones be bygones and keep on truckin’, cool?). This works in most cases, but in the real-time paradigm you’re frequently monitoring data as it comes in… and you’ve only got one set of eyes, so how are you going to mustachify that picture of your CEO and watch the data at the same time?

Recently I’ve been seeing a bunch of sonification projects that are attempting to free up those eyes so you can monitor real-time events passively while working on something else. Data sonification has been around for a while (cue image of guys in hazmat suits walking around with Geiger counters), but I thought I’d take a moment on the ol’ Chartbeat blog to throw around some links for the interested data/sound nerds who are still reading….

Listen to Wikipedia

This one has been going around the web quite a bit recently…. basically a real-time sonification of various types of Wikipedia activity, particularly notable for the thoughtful sound design and accompanying visuals (github).

Listen to BitCoin

The inspiration for Listen to Wikipedia. Both of these make excellent use of the howler.js library, which defaults to Web Audio API with an HTML5 Audio fallback (github). [BONUS: If you’ve got half an hour to kill go play around with these Web Audio API demos].

Tweetscapes

A real-time sonic feed of German tweets. There’s a lot of cool stuff about this one, but I love how complex the composition is... tweets are spatialized in the stereo mix according to which side of the country they came from, and of course you get different sounds for replies, retweets, and hashtags.

The Sound of Github

Listen in on all of the public Github activity. This one was put together by choir.io as a demo for their real-time data sonification service (DSAAS anyone?), which allows you to create your own custom event monitoring streams.

Junction

An art installation that tracks the position of taxis at busy New York City intersections and synthesizes the data into a soundscape in real-time.

Higgs boson

Ok, so this one isn’t real-time, but I mean come on… we’re listening to data from a particle collision at the LHC.

and finally….

ChartWAVE

Crafted by our very own @dbow1234, this one creates an ambient soundscape from your site’s historical traffic data. The link above is using Chartbeat’s data for gizmodo.com, with frequency range governed by total concurrents and distortion/reverb mapped to social traffic. Swap in your domain and API key to get your own sounds. Danny already wrote a bit about this on the blog, so check out his post for technical details and peep his other hackweek projects.

If you want to learn more, here’s a few academic resources because I’m a super nerd and so are you:

Georgia Tech sonification lab

Monitoring Real-time Data: A Sonification Approach [pdf]

Improving the Aesthetic Quality of Realtime Motion Data Sonification [pdf]

 

Hit me up here, in the comments, or @dvdokkum if you’ve got more to share.

Data That Matters – Chris Boutet of The Globe and Mail

September 11th, 2012 by Lauryn

Data is everywhere. Big data, ambient data, real-time, benchmarking – there’s so much that there’s no one metric or one way of using it that works for every company or every industry. The data leaders are the ones who take risks, who look at all the information available and decide what matters right now. We’re spotlighting these innovators in this “Data that Matters” blog series. We’re talking to people in various roles across multiple industries to see how they collect, make sense of, and act on their data. Read the full series. Today we get to hear from Chris Boutet, deputy editor, digital operations at The Globe and Mail. Chris takes a data-driven approach to audience development and editorial strategy… and why newsrooms should look to startups for inspiration. When most people think of data, they often think of it as being cold and impersonal – but in the case of web analytics, it actually brings us closer to people.

Data makes us more human-focused, behavior-focused.

Data allows newsrooms to become more closely attuned to their readers than ever before — watching how they interact with your product, what they like and don’t like, both in terms of the content and the user experience you offer. In journalism, data is changing how we think about, and go about creating, our product. Print newspapers used to be the main focus of our business and if you think about how they are made, they are traditionally built on a complex set of plans based on assumptions of what we think our audience is interested in knowing and we race towards a finished product. The reader feedback mechanism wasn’t really there in the same way it is now.

Now the idea of news is constantly changing. There is no finished product.

With online news, we don’t have to base our plans on assumptions. Web analytics tools like Chartbeat, Omniture and other make the process of gathering user feedback so much faster, and the process of improving what we do so much easier. The same principles apply to news coverage itself. User data gives newsrooms real, instant feedback on what our readership in interested in that we didn’t have before. This new insight allows editorial to plans shift and grow organically throughout throughout the newsday and over time — editors can make informed decisions about whether they should allocate more resources and stronger packaging to a particular topic or story, to provide more complete value and arguably a more relevant product. Now this is not to say that editors need to act on every single piece of data we see.

You don’t want to fall into the tyranny of the measurable. Not everything that’s measurable is valuable.

As a journalist, a news provider, it’s your job to perform a public service. So your editorial direction should never completely follow the whims of your online readership. Great journalism is the core of our business; you don’t want to diminish that, change everything you do for a few more clicks. But I do feel it’s important to consider your brand through the eyes of your audience. A lot of news providers think their brand is what they say it is, but I think it’s also what your audience defines as you – what do they come to you for? Which is precisely where data comes in. There’s something to learn there by weighing these in tandem. I believe newsrooms should look to startups as inspiration in bringing a new data-driven and risk-taking mentality into newsrooms to help us learn more about our audience and how to serve them better. Putting too much faith in things like market research and surveys as key feedback mechanisms can be dicey because it’s all hypothetical. I believe that putting our work directly the hands of users as quickly as possible, and then using data to test our assumptions and measure results, is the best way to learn what is a meaningful or useful product and what is not. Conduct experiments — construct a hypothesis, figure out how to test it, build something, send it live and iterate based on what you see. Build, measure, learn. Sometimes it works. Sometimes it doesn’t. But you always learn something. We’ll be covering a new company each week – big & small, media & not, data junkies & analytics allergic – so let us know if there’s someone you want to see featured. Hit me up at lauryn@chartbeat.com.

Data That Matters – Telegaleria

September 4th, 2012 by Lauryn

Data is everywhere. Big data, ambient data, real-time, benchmarking – there’s so much that there’s no one metric or one way of using it that works for every company or every industry. The data leaders are the ones who take risks, who look at all the information available and decide what matters right now. We’re spotlighting these innovators in this “Data that Matters” blog series. We’re talking to people in various roles across multiple industries to see how they collect, make sense of, and act on their data. Read the full series. Here are some thoughts from Fred Ackourey, creator of Telegaleria one of the largest multicultural e-commerce websites in the US. Fred discusses the creation of personas and using real-time data specifically to target, reach, influence and convert specific audience segments to purchase.

 

We use data to define our customers through distinct, niche personas.

These personas are formed from both numbers and common sense. Numbers don’t lie, but you need to use your head to figure out what they should mean to you, how you should put them to work. So we’ll start with a demographic and then create a profile of a typical, segmented customer with all the attributes of someone who would buy from us. For example, we’ll say, “The person we’re trying to reach for this particular offer in this particular channel is a 38 year old black female office worker with two children, whom she loves to spend time with, so she shops online during the day to save time, making most of her purchases on Friday afternoon.” Then we tailor our content and offers to that specific persona. Initially, it’s really trial and error. As soon as we drop a campaign based on that persona, we start measuring. We see if we hit our goals or not and then test to optimize that content from there – swapping out content, colors, images, times that people spend on the site, that kind of stuff. This tailored content is released across all different channels – online and offline – wherever we think we can reach this particular persona. Naturally, we have different metrics based on what action we want each persona to take and the goals of that channel. To define those goals, we use the AIDA formula - it guides what we want to focus on in each channel.

AIDA stands for Attention Interest Desire Action, and each channel has the job of attaining or increasing at least one of those factors.

Some people still think your site itself is a funnel. But that’s just not how it works. Your site is just the tip of your arrow. And that’s where AIDA comes in. Your message starts way out in the online and offline world – not on your landing page. We use specific channels for only getting attention, for brand awareness. And then our landing page is the point of closure. That’s where it ends, not where it begins.

We have to work like this because we’re so niche.

For instance, we rank #1 in Google on “sexy jeans.” That’s a niche customer – a very specific person who is searching for that keyword. We can’t compete with the Amazons of the world because our product is niche, our site is niche, our audience is niche. So everything is built off of these personas and every piece of communication is presented in a niche channel to reach and influence these people in a very specific way. We’ll be covering a new company each week – big & small, media & not, data junkies & analytics allergic – so let us know if there’s someone you want to see featured. Hit me up at lauryn@chartbeat.com.

Data That Matters – Interbrand

August 21st, 2012 by Lauryn

Data is everywhere. Big data, ambient data, real-time, benchmarking – there’s so much that there’s no one metric or one way of using it that works for every company or every industry. The data leaders are the ones who take risks, who look at all the information available and decide what matters right now. We’re spotlighting these innovators in this “Data that Matters” blog series. We’re talking to people in various roles across multiple industries to see how they collect, make sense of, and act on their data. Read the full series. Next up is Nora Geiss, director of verbal identity and digital for global brand agency Interbrand. In advising brands like AT&T, Feeding America, and Johnson & Johnson, Nora suggests the biggest success when working with and understanding data comes from remembering that data is people.

I think people can get so caught up in the fact that data contains numbers that they forget that those numbers are really about people – and that’s where the story, the context gets lost.

Brands are collecting so many numbers from so many sources - their in-house web teams, their CRM agencies, their ad agencies; these guys are telling them the specifics about how certain campaigns are performing. Which is absolutely useful to tackling discrete goals. But looking only at this granular level doesn’t really tell you about whether or not people in general get your brand. Do you stand for something? And ultimately, do people actually care about what you stand for? And you, as a brand owner, have the option to not care about all that. I mean, you can look at just the short-term numbers to see if you’re making money off an ad. But if you want to be around for a while, to have real longevity and relevance through economic shifts and changing markets, then you need to care about the bigger picture. If you want to bring people back to purchase your products and services over and over again, to pay a premium for your product, to be an advocate for your brand to others -- you have to care about the people and the story behind the data.

It’s not just about the moment “before purchase” -- it can be more important, I think, to look at what happens after purchase.

What did your buyer say? Did they write a review? Did they post a picture of their purchase somewhere to share with friends? That’s where you figure out if you delivered something that’s actually valuable, something that your buyer is going to recommend to their friends, and their friends’ friends or even their not-friends through things like Amazon’s “people like me” type features. The “people telling people” part of the loop drives more purchase and has more impact on brand value than anything else these days. So if you’re 100% focused on how people experience what you offer, and how they can share that experience, then your reason for being as a brand – to deliver a product that people recommend, ultimately driving purchase and loyalty – is more easily fulfilled. Right now I notice a lot of brands looking at measurements out of context. Brands are only seeing “someone talked about me” or “4503 people are talking about me right now” and just focus on blindly increasing that number. It’s just traffic and number of likes or followers or whatever right now.

Brands are just on the what, not the why – when the why is what gets into what people are thinking, doing, experiencing, saying.

You see a lot more when you get into the reasons why: you see that “someone talked about me because they saw this, they experienced this, they touched this” or “they talked about me to this person in this place.” Context is key. You can’t succeed if you don’t know the context. If, for example, my goal as a CMO is to drive premium pricing, and most people are talking about my brand in the context of coupons or discounts, then I’m failing – and I definitely don’t want the number of those mentions to increase.  So purely looking at numbers don’t help me much in a case like this. I think the brand world hasn’t moved past the numbers yet because, in large part, exposure to data happens every once in awhile and in an already numbers-heavy environment – as part of a quarterly report or an annual review of performance against financial goals. When you’re seeing the numbers day-to-day, the constant fluctuation makes you more apt to wonder what’s happening behind those fluctuations.

Brand owners need to live in an environment of habitual measurement.

An environment that makes it possible to take action that matters. You see successful brands taking that approach, like P&G and Dell and Starbucks. You see how they listen to what’s happening in the market, how they incorporate what they learn in their go-to-market strategy, how the audience is reacting to their reactions – the feedback loop. And I think you’re starting to see the change take root internally – it’s not just the marketing department participating, but the product teams, and the agency partners, which leads to much more agile internal process for everyone and everything. Feeding America actually did an amazing job of listening and delivering when they went through their rebrand. Every single person in that organization understands who they serve and what that audience needs most, so they know how to reach them, what to learn from the actions they take, and how to change the way they deliver accordingly. These guys doubled their revenue in one year after their brand relaunch. It’s amazing what can happen when you’re really paying attention to the right data – the data that tells a story about the people you serve. This is such a crucial shift. If your brand is only talking not doing -- using data and or feedback just in marketing and not using it to actually improve your products, quite frankly you’re screwed. 

Because your brand is not just what you say, it’s what you do.

 And if you set an expectation and fail to deliver – believe me, people notice.       We’ll be covering a new company each week – big & small, media & not, data junkies & analytics allergic – so let us know if there’s someone you want to see featured. Hit me up at lauryn@chartbeat.com.