Archive for the ‘Industry Analysis’ Category

The Social Graph Must Die

Wednesday, May 3rd, 2017

Have we reached the breaking point? Has our collective exhaustion with social media — the incessant notifications, the oppressive filter bubbles, the outright denial of our individuality — finally exhausted the excuses, apologies, and band-aid fixes?

Here’s the #ElephantInTheRoom: The social graph is a terrible basis for matching people to information. This is probably not a message that will be welcomed by the corporate giants and countless ventures that are banking on the social graph, but it’s an argument that’s long overdue. The social graph must die.

To be clear, the social graph is not social media. The former is the model or representation of the relationships between people. It’s the foundation upon which social media services match people to information. And in this capacity, the social graph is irredeemable.

Read the full post on Medium

Are Machines Stealing Your Job?

Saturday, October 8th, 2016

Three myths about artificial intelligence and its impact on content creators.

Industrialization is transforming our information economy, destroying old business models and creating new opportunities. The impact it will have on content professionals will make social media seem tame in comparison. To understand this transformation and leverage it to your advantage, you need to parse the myths from reality.

Read the full post on Medium

The Industrialization of the Internet

Sunday, September 18th, 2016

The industrialization of the internet is driven by the relentless pursuit of productivity advantages, not quality improvements.

“The digital revolution is probably going to be as important and transformative as the industrial revolution.” — Ryan Avent, The Economist columnist, author of The Wealth of Humans (via The Atlantic).

Web 2.0 was a social revolution: many hands make light work. In stark contrast, the current revolution, powered by artificial intelligence and machine learning, is industrial: the automation of tasks displaces human work. But trite definitions don’t prepare us for change. Whatever you call it, our digital economy is in the midst of profound changes. By placing these changes within the frame of industrial manufacturing, the true values and motivations that underlie them than are illuminated.

Read the full post on Medium

The History of the Semantic Web is the Future of Intelligent Assistants

Friday, August 19th, 2016

The Semantic Web provides an enticing vision of our online future. This next-generation Web will enable intelligent computer assistants to work autonomously on our behalf: scheduling our appointments, doing our shopping, finding the information we need, and connecting us with like-minded individuals.

Unfortunately, the Semantic Web is also a vision that, to some, seems very distant, perhaps even outdated. It has been over a decade since it was popularized in a May 2001 article in Scientific American. Semantic Web researchers and engineers have been toiling even longer on the monumental technical and sociological challenges inherent in creating a global Semantic Web.

The good news is that we are seeing evidence today of its accelerating emergence.

Read the full post on Medium

Goodbye .@, Hello Messaging?

Tuesday, May 31st, 2016

A single-character change in how tweets are distributed highlights a massive strategic decision for Twitter.

When I first started using Twitter, I’d start my tweets with the names of other users. I wanted to give them credit for their ideas. I later discovered very few people even saw my tweets because of how they were composed. It was frustrating (and a little embarrassing) to learn I didn’t know how to use the service.

Read the full post on Medium

The Surprising Potential of a De-Smooshed Twitter

Tuesday, January 19th, 2016

A unique real-world experiment, powered by an AI, that highlights the rewards and challenges of treating people on Twitter like individuals.

Read the full report on Primal for Twitter, a personal intelligent assistant for content discovery.

The Surprising Potential of a De-Smooshed Twitter

Content curation is disrupting content creation. Are content marketers moving fast enough?

Wednesday, October 8th, 2014

First published on LinkedIn.

A few weeks ago, I made the trip down to Content Marketing World, “the largest content marketing event on the planet” with over 2600 delegates representing 50 countries.

I wanted to explore how the activity of content curation—the process of collecting, organizing and displaying information relevant to a particular area of interest—was impacting this massive content marketing industry.

Content curation may be one of the most disruptive forces in marketing, with an impact crater particularly devastating to activities directly and indirectly linked to content creation.

Based on a review of the activities at Content Marketing World and a supporting data analysis of thousands of articles in the media, content marketers appear slow to respond to this change.

The activity of curation is perceived as subordinate to content creation, complementary but not disruptive. Content curation is a new engine of content marketing, but the industry is tightly coupling it to the old activity of content creation.

The response from marketers? “It’s not creation or curation, it’s both!” Yes, it’s both. I would have had a tremendously difficult time making the arguments in this post without creating the content for it.

However, to say it’s both misses the point of a disruptive change and raises your risks of ending up under that crater. (more…)

A Visual History of The Next Big Thing (and how to see The Next One coming)

Saturday, December 14th, 2013

First published on

In business, vision isn’t some mythical ability to see the future. It’s about being able to recognize a pattern and apply it to something new, before others see it coming.

In this post, we’ll introduce you to one such pattern, the gestation of new media within old media. We’ll then review some examples of how the pattern has repeated itself over the past 30-years, from one Big Thing to the Next.

We’ll then apply the pattern in the here-and-now, to see how it points to The Next Big Things. (more…)

There’s a Graph for That!

Tuesday, December 3rd, 2013

According to Murthy Nukala, “any marketer who doesn’t have a graph within the next twelve months will be at a permanent competitive disadvantage.” That’s a pretty ominous warning, particularly when most marketers have no idea what a graph is, let alone how to use it.


Graphs are a useful way to represent relationships between things. And the World Wide Web is called a Web for a reason: it is a huge network composed of pieces of content and links among them. So it isn’t surprising that graphs are being used everywhere in IT these days to represent particular kinds of relationships among types of content living on the Web.

Since every kind of relationship among things on the Web seems to have its own graph, it can get a little confusing keeping them all straight. That also makes it hard to determine which of those many graphs could be important to you and your business.

You might find it all befuddling enough to develop graphophobia and just ignore them all. That would be a shame, because leveraging these mysterious graphs could truly revolutionize your business.
Here I’ll connect some of the dots and help you understand what graphs are and why they are important. (more…)

Big data’s creative and empathetic sibling (and why they struggle to get along)

Wednesday, November 13th, 2013

Joyce Hostyn argues that Better Human Understanding, Not Big Data, Is the Future of Business. Some excerpts (with my emphasis):

Despite the best of intentions, we’re not data driven, we’re hypothesis driven. Our stories (our mental models) are merely hypotheses of how the world works. But we see them as reality and they influence what data we collect, how we collect it and the meaning we glean from it…

In a quest to become data driven, are marketers trapping themselves with outdated mental models of data and analytics? “Big data is being wasted on marketing. The true power of analytics is in revealing cultural dynamics.”

Many echo these concerns about data-driven marketing, and the need to be skeptical and hypothesis-driven. (1) (2) (3)

Hostyn concludes her thoughtful article with a number of questions, including:

  • Can we leverage big data to zoom out and understand patterns and trends, then zoom back in for a dive deep into the hearts and minds of individuals?
  • Are we willing to develop hypotheses with the potential to disrupt our old mental models? Create experiments to test those hypotheses. Prototype to think. Collect feedback. Iterate.

At Primal, we’ve invested years exploring this mode of hypothesis-setting as a lens into big data. It involves a collaboration between humans and machines across the full spectrum of analytical and synthetical thinking.

What follows is a summary of that exploration and what we’ve learned to this point.


Human-Guided Sentiment Analysis: Beyond the Cold Hard Stats

Monday, November 4th, 2013

Call me sentimental, but perhaps some of you, too, are starting to miss the human side of sentiment analysis.

Machine-based statistical analysis is not the entirety of sentiment analysis – or at least it shouldn’t be. There is still an important role for humans to play in that process. In addition there are opportunities for other tools to assist humans in the process, working in complementary ways with statistical-based sentiment analysis tools. (more…)

Confessions of a Twitter Bot

Wednesday, July 24th, 2013
Source Talking Politics

Bots have a bad reputation. Whether they’re sinister botnets, carrying out coordinated attacks, or annoying spambots, polluting our digital universe with crappy auto-generated content, bots are a much maligned bunch.

You might ask, if bots are bad and a huge portion of Twitter activity is already generated by bots, Why is Primal creating another one?

We believe that intelligent, well-intentioned bots can add a lot of value.

If we build a bot that truly understands you as an individual and can do useful work on your behalf, it might be a welcome addition to the social scene.

In this post, we’ll share some observations and insights into the question, Can a Twitter bot do good?

How to Tell If Your Recommender Will Fail (Before You Spend All That Money On It)

Wednesday, July 10th, 2013

Awhile back, we started exploring how individual interest graphs, powered by Primal’s data service, can be used to improve the performance of recommendation engines.


Our surprising conclusion: Marketers and technology buyers are sold on the promise of personalized recommendations. Unfortunately, they don’t know how to tell recommenders apart, even when they’re built on radically different technical approaches. And the results are mixed, at best. End users are left frustrated, wondering when this promise of personalized recommendations will actually be delivered.

In this post, we’re going to show you how to ask the right questions of your technology provider, to make an informed choice based on business considerations, not technical jargon. We’ll highlight some of the common risks and pitfalls, and conclude with a statement of what to expect from your technology provider.  (more…)

The Myth Behind Big Data and Privacy

Tuesday, June 11th, 2013

We know what personalization means and the compromises it imposes on our individual privacy.

Or do we?

This is perhaps the most insidious myth among the technorati: In order for people to benefit from advanced and personalized technologies, they need to compromise their individual privacy.

This idea is remarkably pervasive and damaging, driving both consumers and businesses away from the opportunities of personalization and next-generation information services.

In this post, I’m going to introduce you to the myth and the underlying villain, Big Data. I’m also going to argue that innovation is a much better path forward than evil, or doing nothing at all.

Trixie’s Story: Virtual Assistants and Interest Graphs

Monday, May 27th, 2013

I was meeting with two guys, one a technologist, one a business advisor.

The discussion was focused on Primal’s technology: semantic user models, knowledge representation, yada, yada…

The business advisor, having listened patiently for some time, finally interjects, “Tell me what this means to Trixie!”


“Yes, the everyday person. Tell me a story of why Trixie would care about any of this?”