I am writing this post as my train pulls out of the Santa Lucia station in Venice, where I’ve had the pleasure of spending the past two days as part of the Digital Economy Forum (#DEF2012). Sponsored by the US Embassy in Italy, the DEF organized a series of events, all geared toward a more robust digital ecosystem in Italy. This evening, as Venice fades into the background, I wanted to share my thoughts on what has been an interesting couple of days and a very well organized, timely conference (a special thanks to Sandy Polu):

Italy and the digital world, part 1: Despite what people may believe, Italy is home to a large pool of quality software engineers and entrepreneurs. While the program was filled with interesting new companies who have worked hard to raise capital in hopes of becoming the next Glancee (an Italian company bought by Facebook), I expected to see a greater representation of the programmers and hackers among the “entrepreneurs to be.” At similar events, this group usually outweighs the MBA types, and, as a former programmer-turned-MBA-type, I’d like to see more Italian coders making their voices and ideas heard at these meetings.

Italy and the digital world, part 2: Despite Italy’s vibrant tech industry, I’m afraid that real understanding and support for our industry still lags behind at the government level. The speech of Minister of Economic Development (and former banker) Passera was more suitable for the general electorate (promises of solving the digital divide,open government data and updated websites), than for the crowd of Italian digital entrepreneurs who want inspiration, and concrete signs that those at the top understand our new world. While I appreciate the government’s acknowledgement, I had hoped for more signs that, like the Obama administration is constantly trying to do, our government is perceptive to the needs of this important and growing sector. For me, this was a missed opportunity.

The Speakers: Speakers included a nice mix of Italian and international companies, and the big guys were there too. Google spoke first, but instead of showing this international audience of entrepreneurs, investors and startuppers why they should see Google as a partner (which I would expect and hope to see given the discussions about privacy) and not an enemy, Google spent a lot of time explaining and promoting Google+. I know the days of “don’t be evil” are gone, and I’m not in a position to criticize their strategy, but as an old fan of the company, their transformation into the next IBM is impossible to ignore.

Instead, Facebook did a great job of showcasing companies who have made the most of the assets Facebook makes available, and called for revolutionaries (“Che Guevaras”) to join their movement. I hope this will translate to more and different applications rather than time-wasting games…

Among the most interesting companies and products who took the stage, I definitely suggest following Applix and Vertical Response. These companies offer a potential innovation boost for small- and medium-sized enterprises by providing them with innovative marketing tools and apps to help put them at par with bigger companies. My favorite presentations instead were those of Andraz Tori of Zemanta (they have a great product; try it if you’re a blogger) and Eleonora Viviani of Stereomood. As a music fan, I’ve spent years creating the perfect mixtape for every situation, so I understand the solution they’re striving for. From now on, their “Sunday morning” selection will be at the top of my weekend rotation.

But until then, I’ll go with this for the next two hours.

While other kids probably dreamed about having superpowers, my dreams were about a future that was more grounded in possibility than fantasy, about inventions that, with the right combination of genius and determination, were possible. Having my own personal television, one small enough to take anywhere and where I could watch anything I wanted, anytime, was something I knew would come eventually. And while the mini TV (remember this, or this?) was an encouraging sign, the technology was still many years away.

Fast forward to today…  I’m watching Mad Men on my iPad and in my still pragmatic dreams, it’s not a leap to think that twenty years from now, we will be living in a very self-curated world. I imagine a world customized for me, my every activity synched and automated based on my personal calendar and a pre-defined set of parameters. A lunch meeting would automatically trigger a series of actions based on the meeting attendees, our location and our preferences. Reservations would be made, train tickets or flights purchased automatically and without any additional input from me.

I see hints of this “reality” today, just as I could imagine that one day, I’d be watching Serie A on the train ride home. While there are many technological and behavioral (not to mention security and privacy-related) boundaries to be crossed in the meantime, semantic technology is an important piece of this puzzle.

Data/information does not exist in a vacuum, and it is becoming easier to interconnect it with systems and technologies to design products that define a user experience increasingly similar to my idea of a “realistic future”.

Semantic technology excels in areas that present the biggest challenges for our information and data driven society by resolving context and connection within and between information. Semantics is increasingly being used to connect information silos and resolve disparities in data (particularly useful in the cases of acquisitions or consolidations), resulting in greater visibility of information assets and intelligence that can be translated to product innovation.

In this way, semantics will bridge gaps, contributing to the more connected, accessible and intuitive world that I imagine.

Understanding how to best leverage the fruits of their consolidations—data—is where many are now focusing their attentions and IT budgets. An event I attended last month, “Demystifying Financial Services Semantics: The Business Value of Data and Semantics” hit the point home: Big Data has arrived, and while not without challenges, it presents a world of opportunity.

Financial institutions are looking to linguistics and semantics as the best option for managing and taking advantage of their unstructured data, using it to better understand customers and competitors, to identify impactful market trends or simply to automate the process of answering common customer questions.

As one Chief Data Officer put it:“We are the stewards of one of our firms’ most important assets, data, and we have been charged with bringing meaning to the data. I believe semantics offers a consistent, long-term capability and change in how data will be managed.”

The ability to understand words in context is where semantics has proven to excel above all other technologies—here’s how:

• It allows organizations to better leverage the variety of data typical of financial institutions: risk analysis, transaction data, customer service feedback and socially generated content is a mix of structured and unstructured information that any financial institution can leverage for corporate and market intelligence.
• It breaks down the data silos acquired and built over time.
• It supports a unified view of information for competitive advantage. In a highly competitive environment, using linguistics and semantics can help companies learn more about customers based on their activities and preferences, noticing even the weakest signals and patterns in information. This new-found insight benefits many day-to-day areas of operations including: marketing, sales and product development efforts.

We are seeing customers take advantage of semantic technology by not only analyzing customer data to understand and benefit from customer feedback, but also through automated, virtual assistance.

Big Data presents a challenge for many industries and financial institutions are stepping up to that challenge, whether through the development of the Financial Industry Business Ontology (FIBO), or through Big Data projects geared toward implementing a framework to support the Dodd-Frank Act and data transparency.

Big Data is here to stay, and it is clear that having the ability to understand words in context using a semantic intelligence platform is critical for driving the new revolution.

]]> http://www.expertsystem.net/blog/?feed=rss2&p=207 http://www.expertsystem.net/blog/?p=206 http://www.expertsystem.net/blog/?p=206#comments Wed, 21 Mar 2012 16:25:24 +0000 L.Scagliarini http://www.expertsystem.net/blog/?p=206

Google’s interview in The Wall Street Journal last week stirred up lots of discussion, and one of Italy’s main dailies called us up that afternoon to get our take on what Google’s overhaul of search will really mean.

First, it’s a question of content. The proclamation that Google is working on a next-generation search engine that incorporates semantic search is more of a shortcut than a solution. What Google is still missing, at least as far as we know, is the ability to extract all data and information from any web page (and not just the data taken from a reference database like FreeBase, a company acquired by Google who created a database of all the data/entities in Wikipedia). Implementing a semantic search engine requires additional steps. For example, semantic search should understand the multiple meanings a word can have (which depends largely on context), not to mention the need to adapt to different languages and cultures. In addition it should also be improved to address the “doubts” — testing the system with real and simulated questions to identify its weaknesses. This is only the beginning—real semantic search technology must address all of these areas.

And finally, it’s the how of the announcement, really, that is interesting. This is the first time I remember Google ‘announcing’ something in advance, rather than on the heels of something it’s already done. Maybe it’s just a change in PR strategy, or does it signal a bigger internal (and more corporate) shift away from its roots?

Today, I’d like to share some real-world examples of customers who are using semantic technology and robust tools for natural language understanding to derive real business intelligence (and not just sentiment) from unstructured information.

Knowing your ‘friends’. Every company with a Facebook page and thousands of ‘friends’ to match has a wealth of market research at its fingertips—whether they actually convert to customers or not, knowing more about your ‘friends’ can only help your business and product strategy.

Information shared on social networks—preferences, tastes, desires—can be translated into valuable business intelligence when integrated into your existing data—demographics, sales data and other statistics—adding great depth and insight to your customer model. As one of our customers is currently experiencing, implementing a good semantic product can help you not only understand your customers, but also how the values you are trying to communicate through your brand are perceived, and what customers think of you vs. the competition. The advantages are significant: up-to-the-minute insight that is significantly less expensive compared to traditional BI or market research.

From questions to answers. When companies implement self help solutions, their main focus is on the savings achieved by deflecting calls from their customer service center. We calculated a $2 million/month savings for one customer—a major manufacturer of handhelds—simply by implementing a self help application on its devices. What the numbers don’t tell us—and semantic technology does—is that the ROI goes much deeper.

Using semantic technology to analyze the inquiries customers made through the self help application gave us valuable insight that allowed our customer to:

• Improve the knowledge base to make sure it contained all the information customers were requesting.
• Link or cluster the information with that available on the CRM system to produce a demographic representation of customers and create customer profiles or types.
• Understand which customers were asking questions most often, which were interested in information outside their normal scope of products and services, and who responded positively to campaigns, etc.

This information—all from existing data—adds more dimension to customer information, and provides not just savings, but intelligence that can impact every area, from sales and marketing to product development and more.

1. Experiment. In “Moneyball,” all the data they needed was right in front of them —they just needed to look at it differently.  While statistics had been part of baseball for many years, some stats were ignored, even if they had a high correlation and impact with important data, like number of runs scored. For small businesses, analyzing social media and web statistics are a good place to start, but don’t stop there. Don’t be afraid to experiment with different representations and mixes of data.
2. Then, be disciplined. Number crunching is not easy. Combining data from different sources in unique ways makes understanding it even more challenging, and certain skills are obviously required (see the school curriculum of the fictional A’s numbers guy, Peter Brand or the real Peter DePodesta)  But discipline, and the willingness to accept a certain degree of failure as you experiment, can lead to interesting, and valuable results.
3. Embrace the big picture. Small organizations often suffer from being too focused on the day to day activities, but every organization needs leadership—their own Billy Bean—who can set priorities and implement the strategy while embracing the big picture benefits that can be achieved through data analysis.

As with baseball before Billy Bean,  there is a lot of information available right now that could bring value to companies in any sector and of any size. Technologies that help you analyze unstructured data are affordable, and companies are increasingly adding functionalities that are applicable to specific fields and industries. The stage is set for any Oakland A‘s like organization to exploit this information to gain a competitive advantage even against richer, more established organizations. If you don’t do it someone else will hire a Peter Brand and change the rules of the game.  Better to get in the game now.

How was it that, some 25 years later, friends who were once passionate about music—both as listeners and musicians—could not reference a single group they liked from the past 5 years (or ten)? Was modern music really that bad, or had they all just tuned out?

I found myself feeling like the teenage son and talking about bands they’d never heard of (thanks to my own nephew and sites like Rhapsody and Spotify) like Arcade Fire, Beirut, Momford & Son and Fanfarlo, who I think are just as good and innovative as their fathers’ (and perhaps grandfathers’) bands were in the 70s.

To be fair, I don’t think my friends are no longer able to appreciate good music (I hope!). I admit that I’m also at fault for losing touch with modernity in other areas. Instead, I think it has more to do with having devoted less time to keeping up with a former passion over the years. Because they lost touch with today’s music, unfamiliarity automatically turned to criticism, and the past was assigned a mythical superiority that the future cannot match.

I’ve noticed this same phenomena in other areas of life, particularly in the business world. In many cases, you have people who have climbed the corporate ladder into management roles and, for various reasons (too many responsibilities, too little time, investment in company politics) become out of touch with the innovations and technological developments of their industry. As with my friends and music, this dynamic has anchored them to approaches, solutions and technologies that may not be modern, but in their eyes, are known, safe, superior.

Awareness of new technologies and innovations is relatively easy today compared to years past. Today, we aren’t left to wait outside the neighbourhood record store for the new Radiohead CD or for our issue of Rolling Stone (or Mucchio Selvaggio for Italians) to arrive in the mail. As with Rhapsody for music, there are many applications and outlets available that even the passive user can keep up with. Any number of options can keep us plugged in to our every area of interest.

Of course, having time to devote to what’s new or on the horizon is certainly a factor, but in my opinion, the benefits far outweigh the alternative, and it can have a lasting impact on almost every area of our lives, from business, right down to your individual CV.

What started many years ago as a driver for a new generation of storage devices, the topic of Big Data is turning mainstream, having made nearly every list of “trends for 2012.” Continued media attention and buzz is making what Big Data actually is more clear. The challenge is how get value from it.

Compared with other trends that fizzled out over time or remained more academic phenomena than anything else (i.e. the Semantic Web), I believe that Big Data is for real: it really can give companies a tremendous opportunity to leverage their data for better business insight through analytics. The catch is knowing how to use it.

More than structured information stored neatly in rows and columns, Big Data actually comes in complex, unstructured formats, everything from web sites, social media and email, to videos, presentations, etc. This is a critical distinction, because, in order to extract valuable business intelligence from Big Data, any organization will need to rely on technologies that enable a scalable, accurate, and powerful analysis of these formats.

On this point, the learning curve for most organizations is quite steep. Not only do they have to start considering unstructured information as part of their business intelligence process, but they also have to learn that extracting insight from unstructured data is a much more complex and qualitative process than traditional business intelligence.

While I think all enterprises can agree that unstructured information is important, when it comes down to the practical application of Big Data, everyone seems to revert to social media sentiment analysis. Certainly this approach has value in an overall business intelligence strategy, but I believe it’s overrated compared to other areas that can provide more strategic, big picture value. For example:

• Predictive Analytics: Using social media data, but more importantly, open source information, to go beyond sentiment analysis and identify patterns in customer behaviors, detect early product feedback and identify indicators to drive innovation.

• Brand Management: Being able to track trends between brands in similar sectors, or completely unrelated markets, in real time, is an extremely powerful tool to drive brand strategy and measure its effectiveness. At the same time, measuring how different brands relate to the intentions and feelings of its target customers is important information for designing a winning marketing strategy.

Integrating unstructured information in the business intelligence process cannot happen without a strong semantic technology, but here, the role of analysts is even more important than in traditional BI. To take advantage of Big Data, analysts have to use the elements and connections that emerge from analysis of millions of documents and be able to interpret them to distill what really matters for the enterprise.

Unstructured information is thus a significant part of the Big Data phenomena but automatic sentiment analysis is less than the tip of the iceberg on how, if effectively handled, this information can be strategic. In upcoming posts, I’ll present some real-world, concrete examples of what ‘effectively handling’, beyond sentiment, could mean for business intelligence in different sectors.

Not that customer service was ever a 40-hour, M-F job, but today, anything less than 24/7 is simply not possible for most. The issues that many organizations are trying to manage today are related to the challenges of keeping ahead of a customer base and global supply chain that are always on, and more connected, than ever before.

We’re working with many organizations on strengthening their customer service operations and while the applications are often different, the needs, the goals, are the same:

• Open and optimize communication channels with customers: Be able to hear them, communicate with them 24/7, learn from them.
• Improve the company’s offering of online resources and access to them.
• Improve efficiencies, reduce costs and improve customer satisfaction.

Today, we’re proud to announce our work with Vodafone, one of the world’s largest mobile communications groups. Working with technology partner Assist, we’re using our Cogito Answers semantic platform to provide SMS based customer service that is now successfully handling more that 500,000 SMS requests each month. When a user sends an SMS to the system—“how much will I pay for calls to London?”—Cogito Answers interprets and categorizes the request and quickly retrieves the answer from the internal knowledge base.

We’re seeing similar adoptions of our technology in public administration, and especially in the financial sector. In our last webinar, “Using Semantic Technology to Transform Customer Support,” we heard from attendees across several industries who are interested in semantic technology, but they ask: Who hosts the solution? How long does it take to integrate new content? What happens if the answer provided needs to be changed? Can we track the questions and answers to proactively identify new trends in questions? What if our industry uses words in a different way form the general public?

Customer service is a natural application for semantic technology because it excels at the point where customers and technology converge. The critical areas where semantics can make a difference in customer service are:

• Customer call centers. With greater access to support resources and information, representatives are able to anticipate and quickly resolve customer issues, resulting in significant cost savings and increased productivity.
• Online and mobile self-help. Customers send emails or text messages any time in natural language and receive immediate, accurate responses from internal knowledge bases, 24/7.
• Voice of the customer. Learn what customers are saying about your brand, products or competitors by analyzing social media conversations in discussion forums, Twitter, Facebook and more. Leveraging Sentiment Analysis helps to more accurately measure customer churn and responses to marketing campaigns, new products or special offers.
• Market and sales cycle intelligence. Data collected from real-time intelligence reporting, combined with customer experience data such as preferences, opinions and sales tracking enables greater insight into sales drivers, or important early warning signals to product development. Proactively monitor intelligence for sentiment to understand peaks in traffic or conversations to better prepare customer service, sales and manufacturing.

To learn more about our Vodafone announcement, click here to read the press release.

To access the recording of our recent customer service webinar, visit our archives.

We thought it would be interesting to take a sample of the tweets over a 12-day period and use our semantic software, in this case, the Cogito Search Explore Engine, to further explore and filter the tweets and see what patterns, people and trends emerged in the data. The benefit of Cogito SEE is that applies semantic technology to the data for automatic text comprehension, and it is able to attack data from different angles, not just quantitatively.

(A significant number of tweets related to Steve Jobs centered around his creations and related brands.)

Using filters and different visualization features, we were able to look at the material through various lenses. Filtering the tweets by Places, People and Organizations and using a subject-action-object (SAO) analysis to better understand the roles of words used to form the tweets gave us different levels of detail about the tweets.

Using the Conceptual Maps feature allowed exploration of these categories, and provided a unique view into all of the people, places, organizations and concepts being discussed.

(The concept map for Silicon Valley highlights concepts, people, organizations and places for further exploration.)

On a personal note, I never met Steve Jobs, but his products are what piqued my interest in computers when I was about 12 years old, and you could say that I indirectly followed him throughout my adult life. It is strange, but I, and many from my generation, are missing him already.

“Here’s to the crazy ones.”

To see our full analysis of the Steve Jobs tweets, click here to access our report.