Monday, June 23, 2014

A tale of two IBMs: Big Blue vs. IBM Watson.


I had an interesting experience with IBM a few weeks ago, or actually two very different IBMs. It started with attending the IBM Business Analytics Summit at the Plaza Hotel here in NYC.

I had just read the cover story in Barron’s on IBM’s CEO Ginni Rometty: Reinventing Big Blue. “A $100 billion ship that is facing declining revenues and fierce competition at every turn.” Rometty spoke about the need to focus on growing their data and analytics business to “the cloud”, where IBM is the leader in private cloud computing.

Beyond some of the obvious revenue and stock valuation problems, IBM has is another big issue - the widely held perception of the firm being a large enterprise solution-focused behemoth. None too nimble nor quick, not very interested in small start-ups, nor up and coming young web developers. They don't seem to offer well publicized developer summits like Apple's Developer Conference held recently or the Google I/O conference set for later this week.

IBM looks like a giant company, mostly interesting in doing business with other huge corporations and government agencies. It take these mega contracts to move the needle on a multimillion dollar income statement, like the massive US Defense Department Healthcare System Modernization contract that just went up for bid valued at $ 11 billion.

The Business Analytics Summit reinforced this perception for me. Compared to the downtown NYC Silicon Alley way of doing business I’ve become accustomed to – which is collaborative, friendly, hip and open in every way – IBM could not have been more different and frankly less relevant. 

The event was dominated by mostly unfriendly people in business suits, lots of PCs and Blackberry devices, with very little social media streaming of event content. Add to that way too many IBM product acronyms being served up like a fire hose - SPSS predictive analytics, the Cognos performance management platform and IBM risk management solution algorithms - my mind went numb in short order despite the luxurious event venue.

They did lots of talking at the audience, telling them how wonderful IBM data solutions are. Very little back and forth dialogue with the audience, just loads of power point presentations with well rehearsed scripts. It seemed to be the IBM-way or the highway.

To add insult to injury they did not even offer free Wi-Fi ($14.99 fee) so I did not use my laptop, and when they invited me to get more information at analyticszone.com I found a website that was not even mobile optimized. I signed up for an IBM analytics beta trial on the site – they acknowledged my registration – and I am still waiting to hear back from them. Nice.

However not all is lost for IBM. It comes down to what web developers call delivering a superior UX or user experience.

That evening I went to a downtown Meet-up at Turn to Tech – a hip IOS coding school in the Flatiron District in the heart of Silicon Alley to learn about IBM Watson.

It was sponsored by Teddy Angelus from BlueWater Labs – a NYC based data / tech consulting firm that specializes in building communities. This effort is a tangible way IBM is reinventing itself – with a cognitive technology that processes information more like a human than a computer. The IBM Watson business proposition is simple: It interacts with humans on human terms.

At the very least the young IBM Watson team at the Meet-up interacted with the attendees like real people. They engaged in a delightful conversation about the possibilities of
IBM Watson to help people work better and smarter across a wide range of applications. They explained IBM Watson runs algorithms on data – and conducts probabilistic analytics to reach conclusions.

People at the event asked hard questions, and the Watson team admitted when they did not have all the answers. They simply asked people to consider the possibilities, from mobile device programming to business and medical uses. I learned that Watson is not your average analytic tool. It can search and sift through huge amounts of data to deliver a relevant data set with simple visualizations and info-graphics in split seconds that show key data points. Wow.

IBM is putting its money behind Watson, with a massive new presence in the heart of Silicon Alley at 51 Astor Place in New York City, hiring a reported 2,000 new people and a commitment to seed venture investments to the tune of $ 100 million to use the IBM Watson Developers’ Cloud. 

Now that will get the attention of the downtown Silicone Alley Crowd for sure.

I spoke with William Sennett – one of the new faces of IBM Watson at the event. He’s been brave enough to pose a poignant question in his Linked In profile: “How can we take social technology, big data and analytics and marry them to create a scalable personalized experience?” A relatively recent graduate of Duke University with a Mechanical Engineering degree, it appears Sennett is asking the right kinds of questions, rather than preaching canned corporate solutions.

You can check out IBM for yourself at the next "Introduction to IBM Watson" Meet-up on June 25, 2014 at Turn to Tech.

I’m not sure how I will use IBM Watson in the future when it comes to marketing, but I am sure that this is the face of IBM that I will look forward to doing business with, in what ever form it comes.





Friday, June 6, 2014

The Marketing Funnel vs. “McKinsey Loop” and the role of data.


Back in 2009 McKinsey made the argument in its Quarterly journal article 
"The Consumer Decision Journey"  that the traditional “marketing funnel” had become obsolete in lieu of a “marketing loop” model.

The metaphor of a “funnel” is one where consumers start with a number of
potential brands in mind (the wide end of the funnel). Marketing programs are then directed at them as they methodically reduce that number of considered
brands as they move through the funnel. At the end they emerge with one brand they choose to purchase.

The "McKinsey Loop": An Evolution of Consumer Behavior
Being McKinsey they went out and analyzed the purchase decision process of 20,000 consumers across five industries and three continents to come up with a different model. Their research showed that the proliferation of media and products combined with the shift from one-way communication - from marketers to consumers – towards a two-way conversation sparked the need to think about new ways to look at marketing.

But I am at a loss in terms of aligning current marketing data analytics with this loop model.  I’ve talked to lots of smart marketers recently who still think generating brand awareness / consideration is important, and measure it religiously. Forbes called 2014 "The Year Digital Marketing Analytics" and the Harvard Business Review declared data scientist "The sexiest job of the century."

Marketing programs using “attraction” or an “in-bound” approach like content marketing to increase consumer engagement are growing in effectiveness and efficiency. Savvy marketers use data-based attribution to figure cost-per-inquiry, cost-per-lead and cost-per-acquisition and use this learning to optimize their marketing mix spend and ROI. So measuring the moving prospects along the "funnel" still seems to have business merit.

User ratings, social media sentiment and content sharing now also come into play – maybe as part of the new “loyalty loop” - but have more positive business building impact by increasing the number of “brand advocates” who fuel modern day word-of-mouth like support via technology based venues.

The move towards ever more engaging content is changing the modern day marketing mix as well. The VB News blog recently discuss the evolution of content marketing – from simple text and visually enhanced streamed content towards customized marketing apps.

Interactive White-Paper Marketing App Example.
According to author Scott Brinker “The fourth wave will be a proliferation of responsive web “marketing apps” — wizards, configurators, calculators, assessment tools, interactive white papers, participatory e books, games, quizzes, guided tours, contests, diagnostics, workbooks, utilities, and a wide range of entertaining and educational experiences.”

The beauty of these apps will be better user engagement and the marketing data exhaust they will surely produce. These tech-driven offerings will deliver a more tangible value exchange between the marketer and consumer, with the ability for marketers to test – learn – apply based on measurable behaviors. They will tip the art vs. science discussion about marketing towards science, for sure.