October 2012
1 post
THE Social KPI: Time to Insight
Here is the one criteria you should use to select a product that collects social media data: time to insight. Time to Insight defined: How long does it take me to get the information I need to exercise judgment? After that, it’s up to governance models and my degree of empowerment to do something about it (or decide not to do something about it, as the case may be). I can control how long...
Oct 11th
May 2012
3 posts
Making Waves →
At long last, there’s a follow-up to the 2010 Q2 Forrester Listening Platform Wave. I’m sure I can only begin to imagine the hours and hours of interviews, research, travel, and testing that goes into creating a new Wave. Based on my brief interactions with Zach, he clearly knows and cares quite a bit about the social intelligence space and its potential. I hold him in high regard,...
May 6th
Where’s Your Forum Strategy? →
A great article from Jason Falls (and sure, I’m biased*). There’s a real danger to thinking about an amorphous mass of the “Social Media Landscape.” I’m glad when I hear someone at a brand say they want to benchmark themselves against someone else, but all too often they want to benchmark against an “aspirational brand” like Starbucks, Nike, or Apple....
May 3rd
Bitly to Launch New Consumer Version →
I’m a fan of bitly. They’re looking at an area of social media activity that most other tools ignore. As much insight as one can derive from public action and sharing, there’s a whole realm of intent and consumption that also has value. This is where bitly shines. The article also ends with a list of cool tidbits that I suggest you check out.
May 2nd
April 2012
12 posts
Social Media Sentiment: Competing On Accuracy |... →
Seth Grimes is a smart dude, and he makes some thoughtful points. Of course, I would prefer if he had mentioned my employer… But on a more serious note, for a long time there was an apocryphal stat floating around that college-educated people will agree on sentiment only 85% of the time. I have no idea how valid it was, but it’s a point that needs to be investigated and considered.
Apr 22nd
7 notes
Why Netflix Never Implemented The Algorithm That... →
The great pain of every analyst is when they send their work off into a black hole. That isn’t what happened here. This is a story of the second greatest pain an analyst experiences: when their work is no longer necessary, but nobody bothered to tell them. On the other hand, this is also a story of one of an analyst’s favorite geek-out moments: sexy new sources of data to inform even...
Apr 21st
“Now enter Google Consumer Surveys, a potentially disrupting force in market...”
– MKTGR » Blog Archive » Google Consumer Surveys Great analysis by my former Nielsen colleague Dave Martin on the implications of Google’s move into market research.
Apr 20th
What You Can Learn From Kaggle's Top 10 Data... →
The article reads kind of press release-y, but it’s interesting to get a peek into the heads of the people proving the value of crowdsourced math.
Apr 18th
Klout Launches Brand Pages To Help Companies... →
I’m still not particularly thrilled with the black box nature of Klout scores, but they’re not going away. PR firms are going to go nuts for this new feature; it will drastically reduce the amount of time they need to spend identifying influencers for outreach. They can spend their time vetting existing lists instead of trying to find them in the first place.
Apr 18th
Incredible video shows how 100 years of shipping... →
I don’t talk much about data visualization here, but I really ought to. This video reminds me of the replays at the end of a game of Civilization.
Apr 18th
Gnip Adds Sina Weibo, 300-million member Chinese... →
This is a big deal to anyone interested in ex-US social media data. While I didn’t call it out by name, it was one of those big sites like Quora and Orkut that have been challenging for social media data collectors to obtain.
Apr 16th
On Correlation vs. Causation
Interesting article in this week’s The Atlantic on the birth and evolution of microtargeting: All of these online movements contribute to what Gage calls “data exhaust.” Email, Amazon orders, resume uploads, tweets — especially tweets — cough out fumes that microtargeters or data brokers suck up to mold hyper-specific messaging. We’ve been hurled into an era...
Apr 15th
Big (Data) News
I’m excited to tell the collected internets that I have decided to join the team at NetBase. I’ll miss my team at Porter Novelli, but the top-secret stuff I’m here to do was mind-bendingly awesome enough to tear me away. (The PN Strategic Digital Analytics team will be coding this post as Sentiment: Mixed) The only changes here will be disclosures when competitive issues come up...
Apr 9th
Sunday Times Analytics Wrap
There was a nice assortment of articles in today’s Times worth sharing. Mining Our Own Personal Data, for Self-Discovery I’m not sure how I managed not to share his original blog post, but the Times has just caught up on Mathematica inventor Stephen Wolfram’s quest to quantify his life. I feel like he and Nick Felton (aka Feltron) need to join forces for the good of humanity....
Apr 8th
Consolidation in the social listening tool space
I was in an airport desperately trying to catch up on my Twitter stream when I saw the news that Visible Tech is buying Cymfony. I remember a period in 2009 where Cymfony seemed like it was outflanking my then-employer Nielsen Buzzmetrics on tons of opportunities, and Visible kept us from gaining much traction within Microsoft. And then suddenly in 2010 all these market researchers and marketers...
Apr 7th
How much does that penny for your thoughts weigh?
I’m surprised that neither Stephen Wolfram nor Nick Felton haven’t yet tackled the “change in my pocket” analysis. What’s a Pound of Change Worth?
Apr 5th
March 2012
24 posts
Spam-churian candidates
I’ve talked before about issues with using social media data to predict election outcomes. Yesterday Mashable’s 78th infographic of the day looks at a new wrench in the gears: spam: The same techniques used by social spammers advertising free iPads and Viagra are now being used to spread bogus political messages across social media, blogs and news sites. Yet another instance that...
Mar 30th
Data on Rails
This is the blog post-equivalent of arriving on the platform just as the 3 train arrives. Two items on NYC Subway data came on my radar this morning: The infographic above uses ridership data to reveal the busiest and calmest stations. The MTA is going to open up real-time data on trains to developers. I have an app on my phone that does some whiz-bang things with augmented reality and...
Mar 28th
“To that end, if the ongoing competition in computer security between those...”
– I’m Not a Real Activist, But I Play One on the Internet | Truthiness in Digital Media Here’s a Big Problem for practitioners of social listening to solve: what happens when the “people” responsible for Consumer-Generated Media aren’t actually people? Whether you’re...
Mar 17th
Let’s End The Magical Thinking About Social Media... →
Yes, please
Mar 16th
Conde Nast to Provide Ad Metrics for Tablets →
Forgive the Mashable link, but it gets the point across.
Mar 15th
March Mathness
I didn’t have a chance to pick an NCAA bracket this year. I’m not too upset, as it means that my winning streak is intact (I won my office pool several years ago with a bracket titled “I actually hate Duke”). While they don’t account for the psychology of an office pool, I take a hard look at predictions from FiveThirtyEight’s Nate Silver and others before I...
Mar 15th
“Numbers can tell us a lot about technology, but only if we know them. Here are a...”
– The Numbers We Don’t Know
Mar 15th
6 Surprising Pizza Pie Charts →
Happy π Day!
Mar 14th
Predicting a story's popularity on Digg | Digg... →
I’ve been playing with this car metaphor for using social media data. I really need to give it its own post. But the idea boils down to using it as a rearview mirror (that is, backward-looking), as a dashboard and a dipstick (seeing how you’re doing right now), and a windshield (seeing where you’re going). The first two are quite common, the third, much less so. But...
Mar 14th
“So if I were a GM, there are a number of data analysis projects that I think...”
– Finding the Right Problem to Tackle: When Web Analytics Technologies Chase Problems - SemAngel I recognize that the point of this post is measuring what matters in the digital space, but this section totally reads like the treatment for Moneyball 2. Somewhere Jonah Hill is getting ready for his...
Mar 13th
Why Klout really matters: Money, money, money —... →
I’m going to skip past the “be wary of any black box algorithm” rant. I assume many companies are already taking similar approaches to using Twitter as a marketing campaign. Step 1 might be finding out how people feel about a particular product, show, etc., by analyzing the Twitter firehose. But Step 2 should be finding out which Twitter users are influential in that space and...
Mar 13th
“So for 2012, we can expect campaigns to make use of aggregated structured data...”
– Vote for me: How data will change the 2012 elections — Cloud Computing News I find it interesting how the tone here is so much more nonchanalant than it was for the New York Times piece on Target a little while ago
Mar 12th
The video associated with this post is great and well worth your 15 minutes. But two bullet points deserve to be shared in their entirety:
5. "Data quality sucks, just get over it."
That is the title of my post from June 2006. And look how far we've come. : )
The core thrust of my post was that data on the web will never get to 95% clean and it will have big holes and it will be sparse in some areas. We should aim to collect, process and store data as cleanly as humanly possible, but after that we should move on to using the data, because we will still have more data about the web than what God's blessed any other channel with. Let's not become the type of people who continue to waste time on quality beyond the point of diminishing returns. Let's not become persistent javascript hackers and sprop variable tweakers at the cost of delivering value from data now.
Multiply all of that a million times when it comes to big data. We will have dirty data. We will have no idea what to do with videos or spoken text or (omg!) social media overload. We will be missing primary keys. We will suffer from a lack of clean meta data (or sometimes any meta data!). We will realize the shallow limits of sentiment analysis. We will cry from the pain of the painful business process fixes that usually result in good data.
And yet, we are standing on a mountain of gold.
Do the best you can in terms of collecting, processing, and storing data of the cleanest possible quality. Know when to shift to data analysis. Start making decisions. Make small ones at first. (Remember, even they will be revolutionary, as these datasets have never come together!) Make bigger ones over time, as you understand the limitations of what you are dealing with.
Here's the kiss of death: Big data implementation projects where the first touch of an Analyst will come 18 months after the project was first conceived. You see, the world would have changed so dramatically in 18 months that nothing you possibly spec'ed for is relevant any more.
Think smart. Move fast. Slowly become Godlike over time.
6. Eliminating noise is even more important than finding a signal.
This might be a little controversial. But stay with me.
Thus far in the history data analysis the objective for our queries has been trying to find the signal amongst all the noise in the data. That has worked very well. We had clean business questions. The data size was smaller and the data set was more complete and we often knew what we were looking for. Known knowns and known unknowns. (See video above.)
With big data, it is so much more important to be magnificent at knowing what to ignore. You must know how to separate out all the noise in the disparate huge datasets to even have a fighting chance to start to look for the signal.
It is amazing but true. If you are not magnificent at knowing what to ignore, you'll never get a chance to pay attention to the stuff to which you should be paying attention.
Your business savvy. Your analytical gut instinct. Tuning your algorithms to first ignore and then hunt for insights. That is what will have a material impact.
http: //www.kaushik.net/avinash/big-data-imperative-driving-big-action/
Mar 12th
“For one thing, digital skills are no longer a plus but expected. Mobile and...”
– Wanted: Social, Mobile and Gaming Guru | News - Advertising Age Sorry folks, I’m taken :-)
Mar 12th
“Because it isn’t the social media per se that you should be attending to;...”
– Blinded by Facebook - Mark Lee Hunter - Harvard Business Review Blogs and message boards still matter. Heck, if you care about Linux users, Usenet groups still matter. The key to understanding stakeholder media is this: its users don’t focus on the same objectives as social media users or...
Mar 8th
“My experiment’s outcome was crystal clear: Dunbar’s number kicked my...”
– Is Dunbar’s Friend-Limiting Number Still Relevant in the Facebook Era?
Mar 7th
Self, Quantified, Quantified
When I wrote my similarly-themed post, I had no idea there was actually a “Quantified Self” blog, but lo and behold, there is. As populations age and health-care costs increase, there is likely to be a greater emphasis on monitoring, prevention and maintaining “wellness” in future, with patients taking a more active role—an approach sometimes called “Health 2.0”. With their sleep...
Mar 6th
“The ultimate challenge for both Twitter and Facebook was summed up recently by...”
– Twitter & Facebook share a problem: Proving social ads work — Tech News and Analysis
Mar 5th
“For I.B.M., Rio is a crucible. By 2050, roughly 75 percent of the world’s...”
– I.B.M. Takes ‘Smarter Cities’ Concept to Rio de Janeiro - NYTimes.com Look at how social media, in this case Twitter, factors into the use cases: At the operations center, employees alerted the fire and civil defense departments and then asked the gas and electric companies to shut down service...
Mar 5th
“The actual threat comes not from Big Data, Inc.’s size in and of itself,...”
– RSA 2012: Bruce Schneier on the Threat of “Big Data, Inc.”
Mar 5th
“Like a CSI episode, where the evidence at first is invisible but then magically...”
– The CSI era of digital marketing insights | Joel Rubinson on Marketing Research
Mar 2nd
Mar 1st
“By any measure, that’s a lot of data. Saenz says that P&G does...”
– Strata 2012: 3 Essential Skills of a Data Driven CEO In general, I am not a fan of dashboards and “command centers.” They tend to exist more for PR purposes than for practical ones. While the name “Business Sphere” throws off warning bells, I think that this P&G one...
Mar 1st
1 tag
Return on imagination
Today I’m going to invent a new metric. I’m sure everyone out there remembers when their high school math teachers introduced them to set theory and the hierarchical classification of numbers. Right? complex / \ imaginary real / \ irrational ...
Mar 1st
February 2012
20 posts
The 2010/2011 Feltron Biennial Report →
The previously mentioned Nicolas Felton (one of Facebook Timeline’s masterminds) just released a double feature report. I am proud to say I spent more time in Staten Island than he did.
Feb 28th
1 tag
Quick Reads and Reactions
I apologize for the recent lack of activity; I had some unexpected travel, a dying computer, and other distractions keep me from stringing together meaningful thoughts. In the short term, I wanted to share some recent content that caught my attention: Privacy management on social media sites | Pew Internet & American Life Project Pew’s hot-off-the-presses report addresses changing...
Feb 27th
1 tag
A Data Stew to Serve Man
I feel a little late to the party in linking to this, but let’s pretend my analysis is so incisive that it merits the delay. Almost every major retailer, from grocery chains to investment banks to the U.S. Postal Service, has a “predictive analytics” department devoted to understanding not just consumers’ shopping habits but also their personal habits, so as to more efficiently market to...
Feb 21st
“Everyone in the economics department quickly noticed Mr. Wolfers’s brash...”
– Economics of Family Life, as Taught by a Power Couple - NYTimes.com Speaking as a reader of Mankiw’s introductory Economics textbooks, there were definitely times I wished I could say bollocks to his face.
Feb 17th
1 tag
Pinterest Measurement Trick →
Found a really helpful tip on tracking Pinterest content this morning: Discover What Are People Pinning from Your Web Site When clicked, every image on Pinterest displays corresponding information like comments, “likes,” other images in the same board and more. The info I find interesting is the area on each pin that shows what other pins came from a specific web domain. Take a look here for...
Feb 17th
1 note
How to Tell When You Need Professional Social... →
I really enjoyed this post Signs that you need to upgrade to a professional social media platform or SaaS (Software as a Service) application: It’s getting too cumbersome to track a bunch of separate RSS feeds You want to know the sentiment of each relevant post that pertains to your business Other marketing tactics aren’t producing the desired results and you’re ready to shift budget to a...
Feb 17th
1 note
1 tag
“With the possibility that nearly 50% of social network users could be fake or...”
– The hollow emptiness in social media numbers - most accounts are fake or empty | ZDNet I’ve been concerned by these same issues lately. Using tools like SimplyMeasured and SocialBro to analyze accounts for large brands, the proportion of followers that have 0 tweets, suspiciously identical...
Feb 16th
1 note
“To grasp the potential impact of Big Data, look to the microscope, says Erik...”
– Big Data’s Impact in the World - NYTimes.com A bit late to this, but it’s always nice to hear you’re working on the Next Big Thing.
Feb 15th
1 note
“OKCupid also mines its data sets to conduct market research for brands, such as...”
– OkCupid’s Key to the Business of Love? Data, of Course | Digital - Advertising Age Happy Valentine’s Day
Feb 14th
1 tag
Why Radian6 is wrong for you - a Radian6 review...
The short answer: Abysmal Facebook data quality. For the longer answer, read on… Image caption: I fight for the user First, I want to reiterate the considerations I shared in Part I: I am going to call out some specific scenarios. I freely acknowledge that the plural of anecdote is not data, but I believe these situations to be representative of serious issues, based on my personal...
Feb 14th
1 note