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Webinar from BrightFunnel Ties Marketing to Revenue

June 30, 2015

The webinar on BrightFunnel Blog titled Campaign Attribution: Start Measuring True Marketing Impact (How-To Video) adds value to marketing efforts. BrightFunnel defines itself as platform for marketing analytics that works to join marketing more closely to revenue. The webinar is focused on the attribution application. The video poses three major questions that the application can answer about how pipeline and revenue are affected by marketing channels and specific campaigns, as well as how to gain better insight on the customer. The article overviews the webinar,

“Marketers care. We care a lot about what happens to all those leads we generate for sales. It can be hard to get a complete view of marketing impact when you’re limited to trusting that the right contacts, if any, are being added to opportunities! In this recording from our recent webinar, see how BrightFunnel solves key attribution problems by providing seamless visibility into multi-touch campaign attribution so you can accurately measure the impact you have on pipeline and revenue.”

BrightFunnel believes in an intuitive approach, claiming that three to four weeks has been plenty of time for their users to get set up and get to work with their product. They host a series of webinars that allows interested parties to ask direct questions and be answered live.

Chelsea Kerwin, June 30, 2014

Sponsored by, publisher of the CyberOSINT monograph


Watson Gets Ink in the Bezos Newspaper

June 29, 2015

I read “The Human Upgrade: Watson’s Next Feat? Taking on Cancer.” The write up, which reminded me of an inclusion or sponsored content, states:

IBM’s computer brain is training alongside doctors to do what they can’t.

I am not exactly sure what this “do what they can’t” means, but the suggestion is that IBM Watson, which cannot generate significant revenue, can do something to ameliorate cancer.

Watson can put information together. Watson has written a cookbook. Then the write up startles with this statement:

But these feats were essentially gimmicks.

Gimmicks. No.

But now IBM Watson is not doing a gimmick:

The IBM program is one of several new aggressive health-care projects that aim to sift through the huge pools of data created by people’s records and daily routines and then identify patterns and connections to predict needs. It is a revolutionary approach to medicine and health care that is likely to have significant social, economic and political consequences.

Consequences like generating confusing or just plain wrong outputs? No way. This is IBM, the company which has declined in revenues for the last 36 months. IBM which spawns the often downright nasty commentary on Alliance@IBM. Impossible.

The write up summarizes some of the history of Watson. Omitted is the use of open source software to reduce certain costs. Left out is the mish mash of components which comprise Watson. Ignored are the human massage therapists essential to get information into Watson digestible form. Sidestepped are the computational requirements to build the index and then the tough problem of processing new or changed data in a timely manner so the outputs are not stale or outdated.

But Watson is evolving. Okay.

Like the Forrester professional who tosses around the word “revolution,” the write grabs this overinflated football.

Watson is a search and retrieval system. Watson adds layers upon layers of wrappers to impart value to outputs. IBM does not have a lock on smart software. What IBM does have is an ability to push the Watson story far and wide.

Does PR make a successful product? IBM obviously believes that marketing is the key to reversing Big Blue’s revenue challenges. IBM stakeholders may want to see some big contracts and zooming revenues. I know I do, and I am just a bystander deflecting PR flack in Harrod’s Creek.

Stephen E Arnold, June 29, 2015

Traditional Publishers, What Is Your Digital Media State?

June 28, 2015

I read “An Investment Bank Made This Epic Presentation on the Future of Digital Media.” “Epic” invokes memories of a required class in which we had to read The Iliad, Paradise Lost, Gilgamesh, and – my favorite – Beowulf. Go, Grendel.

This “epic” appears to tell the tale of the destruction of printed-on-paper outfits. I am not sure that the PowerPoint deck of Terence Kawaja will displace the yucks in the Divine Comedy, but who knows?

The basic idea is that digital media is entangled with marketing. Marketing means money. Money leads back to the focus of Luma. If you are interested in digital media and money, you will, of course, want to work with Luna, but that is another thread in the epic.

Several points warranted a pale blue highlight:

  • Facebook and Google are the big boys
  • Demand means “imbalance”
  • Opportunities for M&A folks
  • Five trends which require about half of the slides in the deck. Spoiler: “new” TV is a big deal

If you are into epics which thrill the MBAs, check out the deck. If you are happy to be a displaced worker, why not go fishing?

And for traditional media types? You did not make the cut.

Stephen E Arnold, June 28, 3025

Story Telling and Search: Smartlogic Fiction

June 25, 2015

One of my two or three readers sent me a link to an article appearing in the Smartlogic Web log. I found the write up unusual. You may want to check it out: Surviving without Content Intelligence? There’s an Elephant in the Room. The first chapter is here.

The approach is to tell a story which explains the value of Smartlogic’s content intelligence approach. I circled this passage in pale blue:

The OLAP cube and MDM solution he’s spent the first half of the year implementing [you can read about it here] is not going to help him with the emails, call records and file system data that he is being asked to include. He’d always known that 80% of an organization’s data was unstructured – he had hoped that they could get away with the 20% that was structured and easily managed. Now he’s got four times more data to work with, and he can’t just shovel it into the CRM system and hope they can deal with it.

The “read about it here” does not link to anything.

If the story resonates with you, Smartlogic may be exactly what you require.

The subhead “Next Week” includes this passage:

The Smartlogic Semaphore Search Application Framework is a tool for rapidly developing search applications that uniquely combine a Semantic Model with commodity tools such as SOLR and the Google Search Appliance, so users are not restricted to keywords, but can search by meaning as well which dramatically improves the user experience. Last, but not least, the Semaphore Classification Server would have allowed Archie to reliably link structured data and unstructured content without being dependent on existing structures and metadata; but that’s a story for next week.

I found one word fascinating, “commodity.” I think of the Google Search Appliance as an expensive way to process large volumes of content. The GSA no longer takes a one size fits all approach, but it is expensive to set up with fail over and customized functions. Solr is an open source solution perched on top of Lucene. A number of companies offer implementations of these open source products. The current stallion winning races is Elastic, but that is not a commodity like diapers.

The “story” is not complete. Part three will become available soon. Stay tuned.

Stephen E Arnold, June 25, 2015

Watson and Coffee Shops. Smart Software Needs k\More Than a Latte

June 19, 2015

I read “IBM Watson Analytics Helps Grind Big Data in Unmanned Coffee Shops.” I promised myself I would not call attention to the wild and wonderful Watson public relations efforts. But coffee shops?

The main idea is that:

IBM has worked with Revive Vending to create systems for unmanned coffee shops that tap into the cognitive computing technology of Watson Analytics for data analysis.

Note the verb: past tense. I would have preferred “is working” but presumably Watson is not longer sipping its latte at Revive.

According to the article:

IBM’s cloud-powered analytics service is used to crunch the vending machine data and form a picture of customers. Summerill [a Revive executive] explained that Watson Analytics allows Honest Café to understand which customers sit and have a drink with friends, and which ones dash in to grab a quick coffee while on the move. Transactional data is analyzed to see how people pay for their food and drinks at certain times of the day so that Honest Café can automatically offer relevant promotions and products to individual customers.

The write up also includes a balling statement from my pals at IDC, the outfit which sold my content without my permission on Amazon courtesy of the wizard Dave Schubmehl:

Miya Knights, senior research analyst at IDC, said that the mass of data generated by retailers through networked systems that cover retail activity can be used to support increasingly complex and sophisticated customer interactions.

Okay, but don’t point of sale systems (whether manual or automated) track these data? With a small operation, why not use what’s provided by the POS vendor?

The answer to the question is that IBM is chasing demo customers even to small coffee shops. IDC, ever quick to offer obvious comments without facts to substantiate the assertion, is right there. Why? Maybe IDC sells professional services to IBM?

Where are the revenue reports which substantiate Watson’s market success? Where are substantive case examples from major firms? Where is a public demonstration of Watson using Wikipedia information?

Think about these questions as you sip your cheap 7-11 coffee, gentle reader.

Ponder that there may be nothing substantive to report, so I learn about unmanned coffee shops unable to figure out who bought what without IBM Watson. Overkill? Yep.

Stephen E Arnold, June 19, 2015

Predictive Analytics Applied to Marketing As a Service

June 17, 2015

In the good old days, content processing provided outputs to those who knew how to ask quite specific questions. Today analytics are predictive and the outputs are packaged to beckon to marketers who are struggling to generate leads and sales.

I read “The Story Behind Syntasa: A Rising Data Analytics Startup With DoD Contractor Roots.” The article is a success story with a dash of emotion and gloss of cheerleading. The company profiled is “a new species of data analytics company, combining national defense expertise with big data marketing technology.” That is an interesting combination.

According to the write up:

The digital marketing and data analytics tech startup offers the “very latest predictive behavioral analytics technology to help enterprises use their large amounts of data and identify actions and outcomes,” said Marwaha, “We do that by providing software that goes through mountains of consumer data gathered by each brand and analyzing click strokes to understand and predict online consumer behavior while they peruse the sites of particular brands.” Syntasa’s CEO added,”[the company] has taken off as more and more enterprises are moving to open source tools like Hadoop and Apache Spark, which can handle large amounts of data. We’ve brought the expertise once used in the federal government’s efforts to fight national security threats through intelligence gathering online, and unleashed it at the enterprise level.”

I noted this passage as well:

When I [author of the article] asked Syntasa’s CEO whether he believes we will begin to see other cyber security companies and intelligence experts expand and/or pivot into marketing/advertising ventures, he offered an interesting counter response: “The converse is more likely. There is a sense of behavioral analytics taking shape in the cyber security market in order to proactively predict where an attack may occur. Which comes first isn’t really the point. The two markets are BOTH now leveraging the power of big data and machine learning to predict events — whether it is leading to a potential threat or a potential customer.”

If you are looking for an outfit with predictive marketing analytics, perhaps Syntasa’s capabilities are spot on for you.

Stephen E Arnold, June 17, 2015

Upgraded Version of Kofax Kapow Released

June 11, 2015

The article on KapowTech titled Kofax Kapow 9.5 Adds Analytics and Simulation Capabilities discusses Kofax’s recent upgrade. The new version includes more graphic support, speedier robot design and testing, and the ability to easily share and synchronize projects. The article says,

“As a global leader in commercial intelligence for the energy, chemicals, metals and mining industries, we provide objective analysis and advice on assets, companies and markets, giving clients the insight they need to make better strategic decisions,” said Matthew Jennings, a Director Operations for Research at Wood Mackenzie. “The new analytics capabilities built into Kofax Kapow 9.5 will give our business analysts detailed, up-to-the-minute insight into how our web data integration processes are running.”

Dave Caldeira, Senior Vice President of Product and Solutions Marketing for Kofax speaks to the importance of real-time management in order for users to keep on top of their projects. The article reports that the Kofax Kapow platform is the quickest way to work with enterprise applications that also routes the need for any coding. Most importantly, it provides the ability to use information that was previously useless. Kofax has more than 20,000 users that rely on the company for its aid in customer engagement.

With Lexmark in Kentucky, the crowd in Harrod’s Creek wishes the company success as it adjusts to its new owner.

Chelsea Kerwin, June 11,  2015

Sponsored by, publisher of the CyberOSINT monograph

Online Shopping Is Too Hard

June 10, 2015

Online shopping is supposed to drive physical stores out of business, but that might not be the case if online shopping is too difficult.  The Ragtrader article, “Why They Abandon” explains that 45 percent of Australian consumers will not make an online purchase if they experience Web site difficulties.  The consumers, instead, are returning to physical stores to make the purchase.  The article mentions that 44 percent believe that traditional shopping is quicker if they know what to look for and 43 percent as prefer in-store service.

The research comes from a Rackspace survey to determine shopping habits in New Zealand and Australia.  The survey also asked participants what other problems they experienced shopping online:

“42 percent said that there were too many pop-up advertisements, 34 percent said that online service is not the same as in-store and 28 percent said it was too time consuming to narrow down options available.”

These are understandable issues.  People don’t want to be hounded to purchase other products when they have a specific item in mind and thousands of options are overwhelming to search through.  Then a digital wall is often daunting if people prefer interpersonal relationships when they shop.  The survey may pinpoint online shopping weaknesses, but it also helps online stores determine the best ways for improvement.

“ ‘This survey shows that not enough retailers are leveraging powerful and available site search and navigation solutions that give consumers a rewarding shopping experience.’ ”

People shop online for convenience, variety, lower prices, and deals.  Search is vital for consumers to narrow down their needs, but if they can’t navigate a Web site then search proves as useless as an expired coupon.


Whitney Grace, June 10, 2015
Sponsored by, publisher of the CyberOSINT monograph

Sentiment Analysis: The Progeny of Big Data?

June 9, 2015

I read “Text Analytics: The Next Generation of Big Data.” The article provides a straightforward explanation of Big Data, embraces unstructured information like blog posts in various languages, email, and similar types of content, and then leaps to the notion of text analytics. The conclusion to the article is that we are experiencing “The Coming of Age of Text Analytics—The Next Generation of Big Data.”

The idea is good news for the vendors of text analytics aimed squarely at commercial enterprises, advertisers, and marketers. I am not sure the future will match up to the needs of the folks at the law enforcement and intelligence conference I had just left.

There are three reasons:

First, text analytics are not new, and the various systems and methods have been in use for decades. One notable example is BAE Systems use of its home brew tools and Autonomy’s technology in the 1990s and i2 (pre IBM) and its efforts even earlier.

Second, the challenges of figuring out what structured and unstructured data mean require more than determining if a statement is positive or negative. Text analytics is, based on my experience, blind to such useful data as real time geospatial inputs and video streamed from mobile devices and surveillance devices. Text analytics, like key word search, makes a contribution, but it is in a supporting role, not the Beyoncé of content processing.

Third, the future points to the use of technologies like predictive analytics. Text analytics are components in these more robust systems whose outputs are designed to provide probability-based outputs from a range of input sources.

There was considerable consternation a year or so ago. I spoke with a team involved with text analytics at a major telecommunications company. The grousing was that the outputs of the system did not make sense and it was difficult for those reviewing the outputs to figure out what the data meant.

At the LE/intel conference, the focus was on systems which provide actionable information in real time. My point is that vendors have a tendency to see the solutions in terms of what is often a limited or supporting technology.

Sentiment analysis is a good example. Blog posts invoking readers to join ISIS are to some positive and negative. The point is that the point of view of the reader determines whether a message is positive or negative.

The only way to move beyond this type of superficial and often misleading analysis is to deal with context, audio, video, intercept data, geolocation data, and other types of content. Text analytics is one component in a larger system, not the solution to the types of problems explored at the LE/intel conference in early June 2015. Marketing often clouds reality. In some businesses, no one knows that the outputs are not helpful. In other endeavors, the outputs have far higher import. Knowing that a recruiting video with a moving nasheed underscoring the good guys dispatching the bad guys is off kilter. Is it important to know that the video is happy or sad? In fact, it is silly to approach the content in this manner.

Stephen E Arnold, June 9, 2014

Social Media Listening on Facebook

June 9, 2015

The article on Virtual-Strategy Magazine titled NUVI and Datasift Join Forces to Offer Clients Access to Anonymized and Aggregated Facebook Topic Data explains the latest news from NUVI. NUVI is a growing platform for social media “listening”, allowing companies to combine and visualize the data from a variety of social media sites including Facebook, Twitter, Instagram, Reddit and more. NUVI is also the exclusive partner of Berkshire Hathaway subsidiary Business Wire. NUVI is now partnering with Datasift, which gives it access to collected and anonymous Facebook topic data, which includes such information as the brands being discussed and the events being held on Facebook. The article states,

“Access to this information gives marketers a deeper understanding of the topics people are engaging in on the world’s largest social platform and the ability to turn this information into actionable insights. With NUVI’s visually intuitive custom dashboards, customers will be able to see aggregate and anonymized insights such as age ranges and gender… “Our partnership with DataSift is reflective of our desire to continue to provide access to the valuable information that our customers want and need,” said CEO of NUVI.”

Tim Barker, Chief Product Officer of Datasift, also chimes in with his excitement about the partnership, while mentioning that the business value of the deal will not affect the privacy of Facebook users. At least the range of information businesses will glean from a post will not contain a specific user’s private data, just the post they probably have no clue is of value beyond the number of likes it gets.

Chelsea Kerwin, June 9, 2015

Sponsored by, publisher of the CyberOSINT monograph


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