Tag Archive for 'social media'

What is going on with Twitter?

This week has been really interesting for me. I started a new job and left an old one behind. I made some great friends and really enjoyed my time at Nielsen. It was a lifetime of learning in a year. Thanks to all my Nielsen friends.

I guess the last few lines has you wondering where my career has taken me. The answer is to Atlas Solutions as a TAM. I am super excited and have been there three days but learned so much its amazing. I am looking forward to this path and all the challenges it has to offer it.

But, I digress. This post is about Twitter and the recent influx of followers I have recently received. As Twitter gains in popularity, I expect to see more notifications from people with backwards followers ratios but this week has seen a influx of dotcoms following me.

Is there something in the water that is making these folks think intruding into my lifestream will make me follow them back?

The Digital Walt Whitman Theory

In the days of BI (Before Internet), poets would scrawl in their notebooks chosen words that would carefully compose a masterpiece of creativity. It was an age-old tradition, and these notebooks are sacred testaments to the accomplishments of man. Their notebooks would wither, rip and turn into relics of a past time; the knowledge passed down to the next generation to inspire in a creative cycle.

Those days are long gone and a new trend is emerging in its place. What is this trend? I am tentatively calling it the Digital Walt Whitman Theory. Its analysis based on my observations as both a creative person and researcher of sorts.

The main gist of the theory is: the creative arts adopt new technologies at a much faster rate than the general public due to above average overlap between technology and art. For example, artists are problem solvers, which leads to experimenting with new technologies as forms of expression. This insistence on experimenting for solutions to creative problems is common in artist and creative folks from all fields.

Furthermore, as society becomes more connected and digital adoption rates amongst artists’ trends higher than the general publics rate of adoption, will we see more artistic folks take leadership roles as inventors? Consumers are savvier then ever and no touch point is safe yet the fine arts remain a beacon of experimentation into these new technologies. While consumers slowly grasp at the new world, artists are experimenting with Twitter, YouTube and other social networks and learning what works and what fails.

Is Damien Hurst the next Bill Gates?

Tweetniks

A quick post to shout out about Pete Blackshaw’s latest post for ClickZ. In it, he discusses Twitter segments and different classes of individuals on the site. As the micro-blog evolves it will be interesting to see all the different types that join up and further the analysis.

One interesting footnote, Pete actually used Twitter to gather his data by proposing this tweet to this followers, “ok i think im going to write my mkt column about twitter “types” (user segments) send thoughts 03:55 PM May 08, 2008 from web.” The tweet stoked some thoughts in my head. As I have been thinking about that very thing for quite sometime and was happy to help. I added a few segments including: TweetSquatters and Tweetniks.

I wanted to talk about the Tweetniks, or someone who uses Twitter to write 21st Century prose. Listed below are a few examples of these modern day Whitmans.

Society’s becoming more connected and much more digital. Artist are sometimes the first to adopt new technology for purposes of expression. Social platforms provide a natural fit for artist to express themselves and explore new mediums. How will digital change creative endeavors? Tweetniks might be blazing a trail of digital creativity that is a game changer but only time will tell.

What do you think?

FYI - Here is Pete’s website dedicated to the topic. Please visit and leave him some feedback on users you have encountered. Additionally, if you would like to add me to your twitter list feel free to do so @stemato.

London Mayor’s Race Analytics

Building from last week’s story about the London Mayor’s election, I wanted to look at some baseline analytics behind the race. Keeping in mind that Boris Johnson eventually wins the race all these charts seem to take on an interesting look. Is it possible to predict an election based on buzz, volume and traffic? If you believe these charts the answer is yes.

Buzz

First look at the below Blogpulse chart (query here) showing the buzz leading up to the May 1, 2008 results. Conversations appear equal through the second week of April but after that they begin the initial spike in Boris Johnson’s favor. The old adage goes “no publicity is bad publicity” and although I have not looked at sentiment it seems to bare true here as Boris peaks much higher than Ken in the buzz chart. (Additionally, Boris Johnson also shows up on the Key People chart here at number thirteen.)


Volume

Volume is an interesting metric online. Ultimately it is about your brand popularity and reach. Or how much the press is talking about you. This Google Trends chart shows that Boris Johnson outpaced Ken Livingstone in news volume too. How did an incumbent so quickly lose press mentions? Did all the online squatters have an effect on Mr. Livingstone’s ratings?

Traffic

Finally, looking at traffic can show you interest about a candidate’s platform. Compete.com’s analytics tool shows backboris.com getting much more traffic than kenlivingstone.com. Which actually did not even register on their graph. Does this mean people were just not intrigued enough about the incumbent to check his website?

Buzz, traffic and volume metrics give us different insights into online behaviors and working in tandem they can help complete the story. They give us an interesting look at the Mayor’s election in London and how a candidate swung the tide in his favor. Was it his online savvy or the help of other’s acumen that helped Boris Johnson?

Miami Dolphins Draft

Saturday was the NFL draft and my favorite team the Miami Dolphins had the top pick. I was naturally curious about the level of discussion in the blogosphere and then something interesting happen. The Dolphins announced early that they had signed Jake Long as the top pick ending months of speculation.

This buzz chart identically follows the way the story broke. His name is first mentioned very sparingly and then on April 10 we see a small spike due to speculation about negotiations beginning. And on April 22 you see the announcement that they had signed him four days ahead of the draft. Then Miami Dolphins buzz spikes again on the actual day of the draft.

Actionable Data for the Miami Dolphins

The Miami Dolphins could use this chart for marketing in a variety of ways. Qualitative and quantitative analysis lies within this study. The Miami Dolphins could make operational decisions such as whether a Jake Long jersey would be a viable choice for the coming year and how many to order. Marketing decisions like promotions and which brands may be interested in using Jake Long are also a viable options.

Deeper qualitative drill downs are also available via clicking through to the points on the chart. For instance, scoring some of the listings from draft day yields valuable PR insights that could overt misinformation. Below is one of the quotes:

  • “Now that the Dolphins have signed their #1 pick, Jake Long, it’s now time for the organization (and the trifecta, to be specific) to move on to other things….And as CBS Sports’ Clark Judge writes, the Dolphins are already working hard on moving Jason Taylor” http://www.thephinsider.com/2008/4/22/2155/03979

Social Media Speeds Up Reaction Times

In the old world sports model a reporter would find out about negotiations and write about it to be published for the next day. Then the team’s official PR department would issue its statement regarding the draft pick. Relationships have changed and the world has become much more social. Media has cut down on its delivery times and PR departments are scrambling to keep up. Measuring social media and listening to your fans is crucial to keep up with changing relationships in an increasingly social world.

How will the Dolphins react to this buzz-touchdown and help further their PR strategy for next year?

My guess is they may have a small team devoted to “listening.” I have not seen many sports teams actively using social media as a viable means of listening and reacting. The Colts (mycolts.net) have a social network but I have not seen much feedback to its success for the team. I would suspect that they have an amazing amount of data and hope they are using it gather valuable insights. Insights that could be quickly gathered and analyzed to facilitate on the fly changes to the marketing and PR strategy.

The Future

Social media is predicted to evolve into a vertical driven space (ie. mycolts.net). Leaving little room for brand invasions to drive consumers to trust them less. Mining your base for crucial insights to help evolve your marketing plan can become social overnight. Will you take advantage?

Pope Benedict & Recession

Yesterday I watched the Papal Mass on television and I started to wonder how much buzz the trip received. Here is a Blogpulse chart, comparing the Pope’s visit to the US, with American Recession.

Here is a link to the actual query.

Pope Benedict

China - Tibet - Olympics Torch Chart

Blogpulse Chart

With all the news about the trial and tribulations of the Olympics torch this week, I thought to run a chart and see the blogosphere’s reaction to the issues. It is interesting to see that the torch is driving much more buzz than the issues. I cannot help but wonder if the events have actually overshadowed the reasons leaving no one to gain.

Protest is patriotic but just make sure your ideas, do not get lost in your methods.

Social Networking Users

A recent report, from OfCom of the UK, about social-networking shows their prolific growth and deep saturation in the UK. I first read about it in a MSN UK story located here and I found its classification system to oversimplify these users. Surely, we can come up with a more profound classification than: Alpha Socialisers, Attention Seekers, Followers, Faithful and Functionals. It seems to only scratch the surface of what is a much more complex eco-system driven by many different types of users and scenarios.

Lets first take a look at scenarios that could evolve as a result of shifting user profiles and maturation of the space. As my company reported last month, Facebook’s numbers have slowed in recent months but its not endemic of the death of social-networking in the UK. The fact is the numbers were growing at a rate that could not have been endured much longer.

But, have they reached critical mass?

This is an interesting question, but with 23% penetration in a country that has only 30 million people total online, it would seem social-networking is still red-hot in the UK. Certainly with that kind of reach, users would fall into more than a handful of types and morph from one classification to another. In fact, I believe that user intentions on social networks are so varied and amorphous that any attempt to classify must be primarily organic.

Lets take deeper look at my organic classification system.

Instead of a linear zoological approach to classes, it should appear more as a hexagon with overlapping interest and a sliding scale. Something like this:

Social Networking Users

Using this hexagonal approach, you could then further define user personality traits based on aggregate sentiment analysis. What does this mean? If you could take a predefined number of UK social network users evenly dispersed across the three majors and parse out there profiles into text. Using that text you could then score the sentiment into different buckets (eg. dating, networking, spammer) based on keyword recognition.

Further refining your chart to something like this:

Social Networking Users Profile

Building out these finite profiles, you get a clearer picture of social networking users and how they interact and relate to one another. The more data ascertained the better the profile. Time of day, age and other demographics can also enhance the map to show more in-depth details of how people engage.

In a very general sense OfCom gets it right, they just leave out a big part of the picture. User interactions and how they effect user profiles. My father said it best when he said “you cannot be, all things to all people.”

Social Media and Ad Spend’s shift to Digital.

Yesterday eMarketer reported that online advertising spend is approaching 10% of all media spending and will be there by 2009. Considering the accountability, that digital commands and traffic quality it should come as no surprise that money is shifting to online at a quicker pace than other media. But what are some of the social media trends that this move will precipitate? Here are three that I think will be important part of my work here at Nielsen Online.

1 - Social Media become increasingly salient as connection hotspots - As trust continues to erode in traditional media, consumers will look increasingly to social media as a trusted opinion for all sorts of decisions, from which restaurant to eat at or what jeans to buy. Malcolm Gladwell describes, in his book The Tipping Point, “weak links” as influential to humans for making connections that make ideas tip. These individuals will become even more important as online migration triggers even more diverse and larger groups of connections who will exert overwhelming force over trends and ideas. (As I write this, I have over 100 twitter friends most I do not know but they shape many of my opinions on any number of things)

2- Brands continue to fortify their digital positions - With dollars shifting to the internet so quickly, brands will rush to keep up with the digital consumer migration. Brands will increasingly face the tough questions about social media and what they should do in this new platform based web. Corporate blogs are not for everyone but opening up the lines of communication can benefit brands. The question is, what is the best way to leverage social media, to empower your consumers and gain valuable insights.

3- Web trust factor becomes site currency - Inevitably, web sites will come that try to game the system and erode consumer trust in social media. From this, will arise a digital trust factor that will eventually become a web currency. It could come in an organized fashion or maybe it will just be semantic based - meaning you don’t travel far from home on the web. You have a few sites you visit and trust based on history, promotion and recommendations and only visit them frequently. This trend will hasten the move to platforms that portalize you to the web at large - Facebook applications are a good example of this in action.

As we see all media continue its move to digital, these three trends are one to watch. Any I missed?

Social-Network Funnel Effect

The growth of the FB economy has created an unlikely division amongst my online social contacts. I see it is as an social-network funnel effect, where the top funnel represents opted-in spam (friends, emails and newsletters) and the bottom your your close friends (real-life contacts and favorite influencers). While the middle portion usually contains varying degrees of friends, all adding some measurable value.

While sorting through this social-network funnel has become an everyday battle to gleam useful content or information for me. Everyday it seems to get bigger and I am constantly looking to cut the time I spend searching for valuable information. This is where a funnel process helps.

If I could apply an overall funnel or class system to contacts based on their history of providing me with value it would help me to quickly indentify quality. How would this work? I am imagining an engine that aggregates all my social media into one spot.

From there an algorithm based on certain factors including history, real-life relation and inbound links would identify users, contributors, and influencers. These contacts would then be broken down into three buckets. For this blog lets call them levels one (most important) to three(least important). You could either sort these buckets individually or apply another set of algorithms to that content.

The next algorithm would then filter content by text-analysis for certain tags similar to Google Alerts. For instance, I would set socia-media as a tag and anytime a mention from a real friend or favorite blogger used social media online it would sort into a “social-media” bucket.

How are we to process all this content? As we progress into digital citizenry honing our filters to maximize utility across all platforms will become an overriding tool of workplace success. And quickly filtering content value will be the best weapon to have in your arsenal.