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?
The value of unstructured information to an organization’s business intelligence process goes well beyond sentiment analysis. Unstructured information, if properly utilized, can fill in the gaps between the polarity of “Like” or “Dislike” and provide the why (why you choose them), how (how you feel) and where (where you stand) that every company should want to know.
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:
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.
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:
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.
While so many of today’s technologies are new, they are being used to address some of the business world’s oldest problems, especially customer service.
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:
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:
Over the past two weeks, news around Steve Jobs—his death, his funeral, tributes—have dominated the web-sphere. Twitter was the place where many immediately went to share quotes, links to online memorials, commercials, cartoons and photos from years past, and to comment about anything and everything related to Jobs.
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.
In an original conclusion to SemTech 2011, and perhaps also to reiterate that the main objective of semantic technology is to make knowledge more accessible, the event organizers invited Laura Campbell, director of strategic initiatives at the Library of Congress, the oldest cultural institution in the United States, and one of the largest libraries in the world, to provide the closing keynote.
Campbell began her presentation by explaining that one of the most pressing problems in wanting to ensure the acquisition and preservation of the largest collection of knowledge and easy access to the best examples of American creativity (strategic objectives of the Library of Congress), is management of our changing connections to available content.
In fact, not only are our ties to content increasing, but also increasingly diverse. Audio, video and images have long since accompanied and even sometimes replaced traditional content; to be able to better manage this complexity, the Library has implemented very stringent processes for the creation of metadata and classification, using automated tools that cannot be separated from automatic text understanding. And because their mission is also to share knowledge, the Library of Congress is a major supporter of Linked Data.
The initiative, created through the movement of Tim Berners-Lee, aims to make it possible to connect unlinked data, via the Web, and to break down the barriers that make correlation of similar information so difficult. Linked Data is perhaps one of the first globally successful initiatives related to the Semantic Web. Some governments, most notably the American and British, have long made it easy to access a myriad of different data which, when enriched with meaning (through semantics), can help develop applications that make this data available for a variety of activities to benefit not only the organizations but especially the people. Italy, too, though still lagging behind other nations, is trying to gain ground in this area, and there are many initiatives that are worth following closely, including this one at Linked Open Data Italia.
Regardless of the interest in seeing a site developed on the principles of the semantic web, if you have never surfed the website of the Library of Congress, I suggest you do so. This is a unique collection of knowledge, and especially the section devoted to digital collections is impressive in terms of quality and quantity of information.
And so, with the presentation of Campbell, halfway between technology and humanities, this year’s Semantic Technology Conference was brought to a close. And like any good conference, it leaves us with much food for thought:
And with this, I close my diary of this year’s Semantic Technology Conference. Thank you for the time you spent reading my posts. Now, it’s time to leave the Hilton and take the cable car out to the Bay, where I expect a long dinner Mark Twain style with crabs and cold beer. But if semantic technology is still on your mind, you can reach me at @Scagliarini or lscagliarini at expertsystem.it.
After the shock caused by the two drops of rain that fell Monday night (in the San Francisco Bay area it almost never rains between the end of April to late October), SemTech’s nearly 1,000 participants gathered for the keynote speech that opened the conference.
As if to disprove the critics who still paint the world of semantic technologies as a very technical and niche sector, when it comes to addressing business problems, the first speech was completely dedicated to one of the most important issues for companies across all industries—customer.
Bill Guinn, of Amdocs, delivered concrete examples of how a system of customer care, where semantic technologies are fully integrated with traditional CRM solutions, can create value. It started from the three areas in which we can construct a process of interaction with customers.
1. Customer Care:
2. Revenue Generation. A second area where the intervention of semantic technologies can add value is linked to revenue generation, because it allows you to manage detailed information on customer preferences, starting from the opinions expressed on blogs, forums and social media. Understanding customer needs enables the chance to make targeted offers, and can influence ideas for promotions and product development. The analysis of customers’ links with the social network can multiply in proportion to the investment: targeted offers for a customer can also be extended to his contacts, who are likely to have similar tastes and needs.
3. Customer Churn. Another area where semantic technologies can deliver value is that of customer churn, or the process by which we choose one product over another. The real-time analysis of the reasons why, which are most often expressed in written text as part of the company’s own communications, can help enable early attempts to keep the customer relationship alive (such as through special offers , discounts, etc.).
In the second speech we heard about the application of semantic technologies in the world of online publishing, a timely topic given the continuing state of crisis in the sector. In recounting the experience carried out with the BBC, John O’Donovan’s Press Association, described why the solution that many people traditionally use to address the poor performance of a site, that is, change the Content Management System, is the most expensive mistake an online publisher can make.
The value provided by the semantic comprehension of online content, especially when it comes to articles and news, has proven its significant and measurable ROI for some time now. O’Donovan showed that a semantic system that categorizes, creates metadata and, in a nutshell, gives a little order to content is of considerable value because it can determine:
The experience of the BBC, as well as some Italian newspapers, such as Il Sole 24 Ore, shows that this is possible even with relatively small investments. It is difficult to understand because so far, only a limited number of publishers have implemented these innovative solutions and integrated semantic functionality into their systems. What is certain is that the opportunity must be seized now because tomorrow may be too late.
For me, Cogito SEE is a reflection of where we are today and where we’re headed in the world of information management/search/analytics. We are accessing and sharing information in ways we could have only imagined 20 years ago. Today, we all have more information outlets than we know what to do with, and more tools with which to share it than ever before. “The stream,” as it’s increasingly being referred to, is a living, ever changing flow, a potentially rich source of information. But it poses an even greater challenge to those who want to tap into its depth and breadth for only the things we’re looking for, when we need them.
This is particularly challenging on an enterprise level, where the need to be able to capture what’s important and meaningful from the stream—and be able to merge that with internal data—translates into better customer service, improved product development and competitive advantage—the bottom line. Capturing the information that makes this possible is about more than search, but also about being able to filter results. This is where a semantic platform excels, and particularly where Cogito SEE excels.
The new Cogito SEE meets the growing needs of enterprise search by not only enabling more effective access to internal information, but by being able to intercept and filter the most critical information from the stream, and using new features to enable complex analysis.
These features, at the heart of Cogito SEE, extend powerful semantic capabilities beyond the point of search and discovery to the visualization and navigation of results. Where traditional filtering methods limit filtering based on file attributes, Cogito SEE enables drill down into results based on comprehension of the content.
In this view, results are broken down into sub categories based on the content, and each category can be further explored.
Our new visualization features are user friendly, and offer further opportunities to filter content as well as dynamic navigation between different views of the results. New visual features offer a variety of ways to view results:
A stream focus that is dynamically updated.
Maps integration that show a geographical concentration of results.
These are just a few of the new features we’re excited about. Visit our website to learn more about the Cogito Search Explore Engine, and if you’re at SemTech today, we hope you’ll visit us in booth #306.
If not, drop us an email at firstname.lastname@example.org to request access to our online demo.
The Semantic Technology Conference begins today in San Francisco and for the next three days, it will focus on the leading providers and the companies who have chosen to implement semantic technology to solve the problems of knowledge management, customer service and monitoring the views expressed on social media (sentiment analysis).
That semantic technologies are no longer purely niche is proven not only by the increasing number of diverse companies present, and by the rich number of case studies that crowd the agenda (pharmaceutical and financial markets for now are the leadeers) but also by the fact that the San Francisco event is just one of three editions of the conference this year. The first European edition will be held in London in September, followed by the Washington D.C. event in October, focusing on applications devoted to government organizations. In particular, I believe that the London event will be an excellent opportunity to demonstrate that, at least in this sector, European software companies are also cutting edge!
Apart from the multiple global events, the rosy future of semantic technology was also confirmed by rumblings of a series of rumors, one of which could become news today. The recent news announced by three giants of the search world confirmed the rumors: The definition of a common standard that outlines the guidelines for adding structured information to web pages (the famous metadata) in an effort to improve user experience by improving search results and reducing the presence of spam and low quality links at the top of results.
The inclusion of metadata should enable search engines to automatically include the contents of a page and, therefore, to obtain useful information to best position a site in the results. Obviously, for now Yahoo, Google and Bing have limited themselves only to the definition of these standards, leaving the webmaster to the task of manually tagging information in HTML pages.
With this announcement, they have thus indirectly confirmed what all the ‘little people’ already knew, namely that the quality of search results has seriously declined in recent years, and that it was therefore necessary to do something to improve user experience. This announcement also comes at a time of enormous opportunity for companies with technologies such as automatic language comprehension, particularly for those who can offer meaning comprehension, because it is essential to automate the encoding of information.
Semantic software automatically understands the semantic meaning of content and can replace manual labor. Obviously, those who are able to offer webmasters a tool with high quality results that is at the same time scalable and easy to use, will have access to a potential gold mine. Instead, the rumors that may become news today here in San Francisco are about bringing voice recognition to the center of the new operating system iOS5 for iPhone and iPad. This feature may allow users to interact with their smartphone or tablet in ways that are even more natural and better suited to the conditions in which these tools are used. If not announced by Steve Jobs today, it’s likely that this news will only be delayed a few months, at the most. If you consider the potential adoption of a tool like this and the absolute importance of semantic technologies in transforming good speech to text in a real search engine, you can understand why the focus on semantics has grown so significantly over the last twelve months.
Turning back to the conference, I wanted to highlight three very different presentations that I think clearly identify why, regardless of the sector in which you operate, it’s important to pay attention to what will be happening in San Francisco over the next few days.
Over the next few days, I’ll let you know, in real-time updates via Twitter @scagliarini, if the event is meeting expectations, and whether it will also offer even more surprises with the launch of new products. Stay tuned!
In economic times like these, a company’s ability to identify the right areas for investment is more important than ever before. This is especially the case when it comes to software investments, which are most often used to reduce costs or to gain competitive advantage over the competition.
The use of semantic technologies for automating manual tasks, or for making previously out of reach knowledge more accessible, is (fortunately for us!) an area where companies are still making investments despite the crisis, because they understand the importance of having this strategic advantage.
Still, when I suggest an automated solution to replace a manual activity (tagging, categorization, monitoring information flows) to potential customers, I am occasionally met with some resistance. Many times, the customer is not able to properly evaluate the pros and cons, and ends up opting for a very basic solution, and in doing so, loses the opportunity for tremendous cost savings and service improvements.
In economically challenging times, the aversion to taking risks is higher than normal, and businesses are scared to take the leap, instead waiting to defer that decision to more financially secure days. The fear that an automatic solution will not be able to perform with the same accuracy as a manual one is understandable, but it’s the wrong way to look at the question. Considering all of the benefits and advantages that can be gained with a successful semantic technology deployment, in my opinion, the risks are negligible compared to the rewards you will reap in terms of overall reduced costs, competitive advantage and more efficient operations.
The costs of an automated system are much lower (typically, the investment is recovered within the first year) compared to a manual operation. Scalability is not an issue, and you can easily add or modify various aspects of the functionality, freeing people for the more complex and greater value added tasks that—no matter how sophisticated or clever technology is—cannot be replicated or automated.
Certainly the need to take risks is not for everyone, but, in the words of Don Abbondio, “se uno il coraggio non c’è l’ha, non se lo può dare:” if one doesn’t have courage, then he also has none to give!