Should We Be Lowering The Social Media Marketing Bar?

analyticalsolution:

However after almost a decade of social networking, the gap between the “experts” and the average brand or marketer is widening, therefore I believe the current path isn’t resolving the complexities faced by marketers and is only serving to perpetuate the massive learning curve. Furthermore, I think that the majority will continue to be left behind after giving up, running out of time and resources, or keep on trying without realizing the promised results.

Originally posted on BundlePost:

Should we Lower the Social Media BarYes, we should. Now let me explain…

In my recent post entitled Top 2015 Social Media Predictions – Disruptive Technologies I covered one of the important disruption areas to watch this year, that was General Social Media Marketing. In fact it was the number one item listed in my 2015 predictions. Specifically I was referring to making social media easier to implement, get results and be effective. The actual prediction was as follows:

“As social media marketing becomes more and more complex, new technology is required to make it easier, regardless of user experience, knowledge or skill. This is a requirement for the industry whose time has come.”

The Problem:

The social media marketing industry is incredibly complex. Marketers, brands and individuals are attending events and classes, reading articles and buying books at a massive pace, trying to understand what to do. At the same time a handful of social media speakers, authors and…

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Riding with the Stars: Passenger Privacy in the NYC Taxicab Dataset

analyticalsolution:

Hmmm, interesting -> Applying Differential Privacy
So, we’re at a point now where we can agree this data should not have been released in its current form. But this data has been collected, and there is a lot of value in it – ask any urban planner. It would be a shame if it was withheld entirely.

Originally posted on Research:

In my previous post, Differential Privacy: The Basics, I provided an introduction to differential privacy by exploring its definition and discussing its relevance in the broader context of public data release. In this post, I shall demonstrate how easily privacy can be breached and then counter this by showing how differential privacy can protect against this attack. I will also present a few other examples of differentially private queries.

The Data

There has been a lot of online comment recently about a dataset released by the New York City Taxi and Limousine Commission. It contains details about every taxi ride (yellow cabs) in New York in 2013, including the pickup and drop off times, locations, fare and tip amounts, as well as anonymized (hashed) versions of the taxi’s license and medallion numbers. It was obtained via a FOIL (Freedom of Information Law) request earlier this year and has been making waves in the…

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Hands on with Watson Analytics: Pretty useful when it’s working

analyticalsolution:

If I have one big complaint about Watson Analytics, it’s that it’s still a bit buggy — the tool to download charts as images doesn’t seem to work, for example, and I had to reload multiple pages because of server errors. I’d be pretty upset if I were using the paid version, which allows for more storage and larger files, and experienced the same issues. Adding variables to a view without starting over could be easier, too.

Originally posted on Gigaom:

Last month, [company]IBM[/company] made available the beta version of its Watson Analytics data analysis service, an offering first announced in September. It’s one of IBM’s only recent forays into anything resembling consumer software, and it’s supposed to make it easy for anyone to analyze data, relying on natural language processing (thus the Watson branding) to drive the query experience.

When the servers running Watson Analytics are working, it actually delivers on that goal.

Analytic power to the people

Because I was impressed that IBM decided to a cloud service using the freemium business model — and carrying the Watson branding, no less — I wanted to see firsthand how well Watson Analytics works. So I uploaded a CSV file including data from Crunchbase on all companies categorized as “big data,” and I got to work.

Seems like a good starting point.

watson14Choose one and get results. The little icon in…

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The Four Horsemen Of The Cyber Apocalypse

analyticalsolution:

These “Four Horsemen” point us to the components we can expect to see used by hackers in 2015: exploits in unpatchable systems; recycled malware hidden imperceptibly; and human error. Studying these harbingers could very well save us from a potential cyber catastrophe

Originally posted on TechCrunch:

Editor’s note: Shlomi Boutnaru is the CTO and co-founder of predictive cyber-security startup CyActive.

If 2014 did anything good for cybersecurity, it showed us just how exposed major corporations, governments and militaries are to cyber attacks. From vulnerabilities in our power grids to our cash registers, cyber attacks have become the$400 billion problem. And while the attacks differ in motive and method, there are four consistent perpetrators charging at us at full speed – and we need to rein them in.

These “FourHorsemen” point us to the components we can expect to see used by hackers in 2015: exploits in unpatchable systems; recycled malware hidden imperceptibly; and human error. Studying these harbingers could very well save us from a potential cyber catastrophe.

Unpatched and Unpatchable Systems

Heartbleed. What happens when you discover your safety net has gaping holes? The Heartbleed vulnerability was…

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How big data got its mojo back

analyticalsolution:

Big data never really went anywhere, but as a business, it did get a little boring over the past couple years.

Originally posted on Gigaom:

Big data never really went anywhere, but as a business, it did get a little boring over the past couple years.

Big data technologies (and not just Hadoop) proved harder to deploy, harder to use and were a lot more limited in scope than all the hype suggested. Machine learning became the new black as startups infused it into everything, but most often marketing and sales software. So much ink and breath were wasted trying to define (or disprove) the idea of data science, probably because the tools of the trade were still so foreign to most people.

But while the early days of the big data movement hinted at greatness, it’s probably fair to say they didn’t deliver — even if the resulting tools were very useful and very necessary to set the stage for things to come. And, realistically, many companies still haven’t adopted these technologies or these techniques.

sd2015

Things are changing…

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The beginning of the end for email

analyticalsolution:

Perhaps the biggest sign yet of the change at hand comes from Germany, which has called for an “anti-stress regulation” that would, among other things, ban employers from contacting employees after hours. Chancellor Angela Merkel has criticized the law and stopped it from moving forward for now, but German leaders have long been concerned about the growing tendency for technology to allow work to encroach on employees’ private lives.

Originally posted on Fortune:

Along with global warming, the Ebola virus, and gridlock politics, this year, for me at least, something far less life- and society-threatening also spiraled out of control: email.

It was long ago invented as something to make us more productive. But what productivity expert would ever say that it’s a good thing that instead of working, we now “answer email?” Or that on some days, I am wary to leave my desk to head into a meeting because it means taking my finger off the dike and knowing I will return to a flood of boldfaced new messages waiting patiently for my total attention?

Some people strive for “inbox zero.” But like many people, I now get so much spam and unsolicited pitches that if I were to adopt such a goal, I would spend the entirety of every workday doing nothing but deleting emails. To keep up with this…

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Using Gamification to Build Communities and Create Leads #SocialSelling

analyticalsolution:

But let us take a step back here. Who are we trying to sell to? Let us not forget, you know the prospects and customers in your forecast. The people you are trying to speak to, are those who are “thinking” about buying. But we can go one better than that! If we have community, we can pull in those that haven’t thought about buying. Your competitors or prospects that might not even know they have a problem OR that your solution exists.

Originally posted on Blog by @Timothy_Hughes:

Gamification is a very trendy term right now, what does it mean?

Screen Shot 2014-12-15 at 17.50.15The main purpose for employing Gamification is to incentify, engage and improve user engagement.  In devising a “game” you work out the particular behaviors you want and then give points when people exhibit those behaviors.

For example, at a recent conference I attended, an App was provided to download.  Gamification was “provided” by offering points for leaving speaker feedback, looking at the exhibitors details, etc etc.  The organisers then hoped that people’s natural competitive streak will mean they will compete (results published on a “Leaderboard”).  To get further up the Leaderboard you need to leave more speaker and session feedback, all good behaviors.

Gamification is for Trendy Marketing People it has no Place in Sales, Right?

Screen Shot 2014-12-15 at 17.56.34Recently had a demonstration from a Gamification company called Rise (previously called Leaderboard) and it got me thinking. This is all…

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Big Data and Intuition: The Future of Marketing

analyticalsolution:

Technology isn’t only getting faster, it’s getting smarter. Computers are able to recognize and learn from patterns and make changes in real-time. Their improved analytic and decision-making abilities now allow them to outperform humans in areas such as medical diagnosis and customized marketing campaigns.

Originally posted on Gigaom:

Technology isn’t only getting faster, it’s getting smarter. Computers are able to recognize and learn from patterns and make changes in real-time. Their improved analytic and decision-making abilities now allow them to outperform humans in areas such as medical diagnosis and customized marketing campaigns.

However, it’s hard for marketers to embrace data analysis when they’ve trusted their own gut to fuel decisions for so long. It’s a point of pride for many.  The problem is, the strategy frequently fails. A 20 year study of political pundits found that they were only as accurate as a coin toss, suggesting that successful “intuitive” decisions are often a lucky guess.

On the other hand, a McKinsey study found that companies who put data at the center of marketing and sales decisions improve marketing ROI by 15% – 20%. Data-driven personalization, in particular, can lift sales 10% or more. For example, Bank of America…

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Top 10 Steps to a Pragmatic Big Data Pipeline

analyticalsolution:

As you know Big Data is capturing lots of press time. Which is good, but what does it mean to the person in the trenches ? Some thoughts … as a Top 10 List :

Originally posted on My missives:

As you know Big Data is capturing lots of press time. Which is good, but what does it mean to the person in the trenches ? Some thoughts … as a Top 10 List :

[update 11/25/11 : Copy of my guest lecture for Ph.D students at the Naval Post Graduate School The Art Of Big Data is at Slideshare]

10. Think of the data pipeline in multiple dimensions than a point technology & Evolve the pipeline with focus on all the aspects of the stages

  • While technologies are interesting, they do not work in insolation and neither should you think that way
  • Dimension 1 : Big Data (I had touched upon this in my earlier blog “What is Big Data anyway“) One should not only look at the Volume-Velocity-Variety-Variability but also at the Connectedness – Context dimensions.
  • Dimension 2 : Stages – The degrees of separation as in collect…

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Millennials and Social Commerce By The Data [Infographic]

analyticalsolution:

35% of Millennials are likely to use a “buy” button on Facebook and 24% are likely to use one on Twitter, should those be provided by the platforms.

Originally posted on BundlePost:

Interest and discussions surrounding the 76 million millennials and their impact on social media, marketing and social commerce are seemingly increasing every week. Brands and marketers are seeking data to bolster their digital marketing efforts around this group, their interests and online patterns and rightly so. Millennials are unique in that they are not influenced by traditional ‘push’ marketing strategies as other population segments have been in the past and more importantly they have been raised with the digital world in place, rather than migrating to it as those before them.

Using data published in a report by UMass, we have created an easy to consume Infographic that contains the key points every brand and marketer should know. Following the infographic we break down some of the data points and include some takeaway action steps you may want to consider.

Millennial Social Commerce Infographic

The Data Highlights:

  • 35% of Millennials are likely to use a “buy” button…

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