IHS Enterprise Search: Semantic Concept Lenses Are Here
July 29, 2014
I pointed out in http://bit.ly/X9d219 that IDC, a mid tier consulting firm that has marketed my information without permission on Amazon of all places, has rolled out a new report about content processing. The academic sounding title is “The Knowledge Quotient: Unlocking the Hidden Value of Information.” Conflating knowledge and information is not logically satisfying to me. But you may find the two words dusted with “value” just the ticket to career success.
I have not read the report, but I did see a list of the “sponsors” of the study. The list, as I pointed out, was an eclectic group, including huge firms struggling for credibility (HP and IBM) down to consulting firms offering push ups for indexers.
One company on my list caused me to go back through my archive of search information. The firm that sparked my interest is Information Handling Services or IHS or Information Handling Service. The company is publicly traded and turning a decent profit. The revenue of IHS has moved toward $2 billion. If the global economy perks up and the defense sector is funded at pre-drawdown levels, IHS could become a $2 billion company.
IHS is a company with an interesting history and extensive experience with structured and unstructured search. Few of those with whom I interacted when I was working full time considered IHS a competitor to the likes of Autonomy, Endeca, and Funnelback.
In the 2013 10-K on page 20, IHS presents its “cumulative total return” in this way:
The green line looks like money. Another slant on the company’s performance can be seen in a chart available from Google Finance.
The Google chart shows that revenue is moving upwards, but operating margins are drifting downward and operating income is suppressed. Like Amazon, the costs for operating and information centric company are difficult to control. Amazon seems to have thrown in the towel. IHS is managing like the Dickens to maintain a profit for its stakeholders. For stakeholders, is the hope is that hefty profits will be forthcoming?
Source: Google Finance
My initial reaction was, “Is IHS trying to find new ways to generate higher margin revenue?”
Like Thomson Reuters and Reed Elsevier, IHS required different types of content processing plumbing to deliver its commercial databases. Technical librarians and the competitive intelligence professionals monitoring the defense sector are likely to know about IHS different products. The company provides access to standards documents, regulatory information, and Jane’s military hardware information services. (Yep, Jane’s still has access to retired naval officers with mutton chop whiskers and interesting tweed outfits. I observed these experts when I visited the company in England prior to IHS’s purchase of the outfit.)
The standard descriptions of IHS peg the company’s roots with a trade magazine outfit called Rogers Publishing. My former boss at Booz, Allen & Hamilton loved some of the IHS technical services. He was, prior to joining Booz, Allen the head of research at Martin Marietta, an IHS customer in the 1970s. Few remember that IHS was once tied in with Thyssen Bornemisza. (For those with an interest in history, there are some reports about the Baron that are difficult to believe. See http://bit.ly/1qIylne.)
Large professional publishing companies were early, if somewhat reluctant, supporters of SGML and XML. Running a query against a large collection of structured textual information could be painfully slow when one relied on traditional relational database management systems in the late 1980s. Without SGML/XML, repurposing content required humans. With scripts hammering on SGML/XML, creating new information products like directories and reports eliminated the expensive humans for the most part. Fewer expensive humans in the professional publishing business reduces costs…for a while at least.
IHS climbed on the SGML/XML diesel engine and began working to deliver snappy online search results. As profit margins for professional publishers were pressured by increasing marketing and technology costs, IHS followed the path of other information centric companies. IHS began buying content and services companies that, in theory, would give the professional publishing company a way to roll out new, higher margin products. Even secondary players in the professional publishing sector like Ebsco Electronic Publishing wanted to become billion dollar operations and then get even bigger. Rah, rah.
These growth dreams electrify many information company’s executives. The thought that every professional publishing company and every search vendor are chasing finite or constrained markets does not get much attention. Moving from dreams to dollars is getting more difficult, particularly in professional publishing and content processing businesses.
My view is that packaging up IHS content and content processing technology got a boost when IHS purchased the Invention Machine in mid 2012.
Years ago I attended a briefing by the founders of the Invention Machine. The company demonstrated that an engineer looking for a way to solve a problem could use the Invention Machine search system to identify candidate systems and methods from the processed content. I recall that the original demonstration data set was US patents and patent applications. My thought was that an engineer looking for a way to implement a particular function for a system could — if the Invention Machine system worked as presented — could present a patent result set. That result set could be scanned to eliminate any patents still in force. The resulting set of patents might yield a procedure that the person looking for a method could implement without having to worry about an infringement allegation. The original demonstration was okay, but like most “new” search technologies, Invention Machine faced funding, marketing, and performance challenges. IHS acquired Invention Machine, its technologies, its Eastern European developers, and embraced the tagging, searching, and reporting capabilities of the Invention Machine.
The Goldfire idea is that an IHS client can license certain IHS databases (called “knowledge collections”) and then use Goldfire / Invention Machine search and analytic tools to get the knowledge “nuggets” needed to procure a missile guidance component.
The jargon for this finding function is “semantic concept lenses.” If the licensee has content in a form supported by Goldfire, the licensee can search and analyze IHS information along with information the client has from its own sources. A bit more color is available at http://bit.ly/WLA2Dp.
The IHS search system is described in terms familiar to a librarian and a technical analyst; for example, here’s the attributes for Goldfire “cloud” from an IHS 2013 news release:
- “Patented semantic search technology providing precise access to answers in documents. [Note: IHS has numerous patents but it is not clear what specific inventions or assigned inventions apply directly to the search and retrieval solution(s)]
- Access to more than 90 million scientific and technical “must have” documents curated by IHS. This aggregated, pre-indexed collection spans patents, premium IHS content sources, trusted third-party content providers, and the Deep Web.
- The ability to semantically index and research across any desired web-accessible information such as competitive or supplier websites, social media platforms and RSS feeds – turning these into strategic knowledge assets.
- More than 70 concept lenses that promote rapid research, browsing and filtering of related results sets thus enabling engineers to explore a concept’s definitions, applications, advantages, disadvantages and more.
- Insights into consumer sentiment giving strategy, product management and marketing teams the ability to recognize customer opinions, perceptions, attitudes, habits and expectations – relative to their own brands and to those of their partners’ and competitors’ – as expressed in social media and on the Web.”
Most of these will resonate with those familiar with the assertions of enterprise search and content processing vendors. The spin, which I find notable, is that IHS delivers both content and information retrieval. Most enterprise search vendors provide technology for finding and analyzing data. The licensee has to provide the content unless the enterprise search vendor crawls the Web or other sources, creates an archive or a basic index, and then provides an interface that is usually positioned as indexing “all content” for the user.
According to Virtual Strategy Magazine (which presumably does not cover “real” strategy), I learned that US 8666730:
covers the semantic concept “lenses” that IHS Goldfire uses to accelerate research. The lenses correlate with the human knowledge system, organizing and presenting answers to engineers’ or scientists’ questions – even questions they did not think to ask. These lenses surface concepts in documents’ text, enabling users to rapidly explore a concept’s definitions, applications, advantages, disadvantages and more.
The key differentiator is claimed to move IHS Goldfire up a notch. The write up states:
Unlike today’s textual, question-answering technologies, which work as meta-search engines to search for text fragments by keyword and then try to extract answers similar to the text fragment, the IHS Goldfire approach is entirely unique – providing relevant answers, not lists of largely irrelevant documents. With IHS Goldfire, hundreds of different document types can be parsed by a semantic processor to extract semantic relationships like subject-action-object, cause-and-effect and dozens more. Answer-extraction patterns are then applied on top of the semantic data extracted from documents and answers are saved to a searchable database.
According to Igor Sovpel, IHS Goldfire:
“Today’s engineers and technical professionals are underserved by traditional Internet and enterprise search applications, which help them find only the documents they already know exist,” said Igor Sovpel, chief scientist for IHS Goldfire. “With this patent, only IHS Goldfire gives users the ability to quickly synthesize optimal answers to a variety of complex challenges.”
Is IHS’ new marketing push in “knowledge” and related fields likely to have an immediate and direct impact on the enterprise search market? Perhaps.
There are several observations that occurred to me as I flipped through my archive of IHS, Thyssen, and Invention Machine information.
First, IHS has strong brand recognition in what I would call the librarian and technical analyst for engineering demographic. Outside of lucrative but quite niche markets for petrochemical information or silhouettes and specifications for the SU 35, IHS suffers the same problem of Thomson Reuters and Wolters Kluwer. Most senior managers are not familiar with the company or its many brands. Positioning Goldfire as an enterprise search or enterprise technical documentation/data analysis tool will require a heck of a lot of effective marketing. Will positioning IHS cheek by jowl with IBM and a consulting firm that teaches indexing address this visibility problem? The odds could be long.
Second, search engine optimization folks can seize on the name Goldfire and create some dissonance for IHS in the public Web search indexes. I know that companies like Attivio and Microsoft use the phrase “beyond search” to attract traffic to their Web sites. I can see the same thing happening. IHS competes with other professional publishing companies looking for a way to address their own marketing problems. A good SEO name like “Goldfire” could come under attack and quickly. I can envision lesser competitors usurping IHS’ value claims which may delay some sales or further confuse an already uncertain prospect.
Third, enterprise search and enterprise content analytics is proving to be a difficult market from which to wring profitable, sustainable revenue. If IHS is successful, the third party licensees of IHS data who resell that information to their online customers might take steps to renegotiate contracts for revenue sharing. IHS will then have to ramp up its enterprise search revenues to keep or outpace revenues from third party licensees. Addressing this problem can be interesting for those managers responsible for the negotiations.
Finally, enterprise search has a lot of companies planning on generating millions or billions from search. There can be only one prom queen and a small number of “close but no cigar” runner ups. Which company will snatch the crown?
This IHS search initiative will be interesting to watch.
Stephen E Arnold, July 29, 2014
Color Changing Ice Cream: The Metaphor for Search Marketing
July 29, 2014
I read “Scientist Invents Ice Cream That Changes Colour As You Lick It.” The write up struck me as a nearly perfect metaphor for enterprise search and retrieval. First, let’s spoon the good stuff from the innovation tub:
Science might be busy working on interstellar travel and curing disease but that doesn’t mean it can’t give some time to ice cream. Specifically making it better visually.
The idea is that ice cream has an unsatisfactory user interface. (Please, do not tell that to the neighbor’s six year old.)
Spanish physicist and electronic engineer Manuel Linares has done exactly that. He’s managed to invent an ice cream that changes colour as you lick it. The secret formula is made entirely from natural ingredients…Before being served, the ice cream is a baby blue colour. The vendor serves and adds a spray of “love elixir”…Then as you lick the ice cream it will change into other colours.
My Eureka! moment took place almost instantly. As enterprise search vendors whip up ever more fantastic capabilities for key word matching and synonym expansion, basic search gets sprayed with “love elixir.” As the organization interacts with the search box, the search results are superficially changed.
The same logic that improves the user experience with ice cream has been for decades the standard method of information retrieval vendors.
But it is still ice cream, right?
Isn’t search still search with the same characteristics persistent for the last four or five decades?
Innovation defines modern life and search marketing.
Stephen E Arnold, July 29, 2014
Google and Findability without the Complexity
July 28, 2014
Shortly after writing the first draft of Google: The Digital Gutenberg, “Enterprise Findability without the Complexity” became available on the Google Web site. You can find this eight page polemic at http://bit.ly/1rKwyhd or you can search for the title on—what else?—Google.com.
Six years after the document became available, Google’s anonymous marketer/writer raised several interesting points about enterprise search. The document appeared just as the enterprise search sector was undergoing another major transformation. Fast Search & Transfer struggled to deliver robust revenues and a few months before the Google document became available, Microsoft paid $1.2 billion for what was another enterprise search flame out. As you may recall, in 2008, Convera was essentially non operational as an enterprise search vendor. In 2005, Autonomy bought the once high flying Verity and was exerting its considerable management talent to become the first enterprise search vendor to top $500 million in revenues. Endeca was flush with Intel and SAP cash, passing on other types of financial instruments due to the economic downturn. Endeca lagged behind Autonomy in revenues and there was little hope that Endeca could close the gap between it and Autonomy.
Secondary enterprise search companies were struggling to generate robust top line revenues. Enterprise search was not a popular term. Companies from Coveo to Sphinx sought to describe their information retrieval systems in terms of functions like customer support or database access to content stored in MySQL. Vivisimo donned a variety of descriptions, culminating in its “reinvention” as a Big Data tool, not a metasearch system with a nifty on the fly clustering algorithm. IBM was becoming more infatuated with open source search as a way to shift development an bug fixes to a “community” working for the benefit of other like minded developers.
Google’s depiction of the complexity of traditional enterprise search solutions. The GSA is, of course, less complex—at least on the surface exposed to an administrator.
Google’s Findability document identified a number of important problems associated with traditional enterprise search solutions. To Google’s credit, the company did not point out that the majority of enterprise search vendors (regardless of the verbal plumage used to describe information retrieval) were either losing money or engaged in a somewhat frantic quest for financing and sales).
Here are the issues Google highlighted:
- User of search systems are frustrated
- Enterprise search is complex. Google used the word “daunting”, which was and still is accurate
- Few systems handle file shares, Intranets, databases, content management systems, and real time business applications with aplomb. Of course, the Google enterprise search solution does deliver on these points, asserted Google.
Furthermore, Google provides integrated search results. The idea is that structured and unstructured information from different sources are presented in a form that Google called “integrated search results.”
Google also emphasized a personalized experience. Due to the marketing nature of the Findability document, Google did not point out that personalization was a feature of information retrieval systems lashed to an alert and work flow component. Fulcrum Technologies offered a clumsy option for personalization. iPhrase improved on the approach. Even Endeca supported roles, important for the company’s work at Fidelity Investments in the UK. But for Google, most enterprise search systems were not personalizing with Google aplomb.
Google then trotted out the old chestnuts gleaned from a lunch discussion with other Googlers and sifting competitors’ assertions, consultants’ pronouncements, and beliefs about search that seemed to be self-evident truths; for example:
- Improved customer service
- Speeding innovation
- Reducing information technology costs
- Accelerating adoption of search by employees who don’t get with the program.
Google concluded the Findability document with what has become a touchstone for the value of the Google Search Appliance. Kimberly Clark, “a global health and hygiene company,” reduced administrative costs for indexing 22 million documents. The costs of the Google Search Appliance, the consultant fees, and the extras like GSA fail over provisions were not mentioned. Hard numbers, even for Google, are not part of the important stuff about enterprise search.
One interesting semantic feature caught my attention. Google does not use the word knowledge in this 2008 document.
Several questions:
- Was Google unaware of the fusion of information retrieval and knowledge?
- Does the Google Search Appliance deliver a laundry list of results, not knowledge? (A GSA user has to scan the results, click on links, and figure out what’s important to the matter at hand, so the word “knowledge” is inappropriate.)
- Why did Google sidestep providing concrete information about costs, productivity, and the value of indexing more content that is allegedly germane to a “personalized” search experience? Are there data to support the implicit assertion “more is better.” Returning more results may mean that the poor user has to do more digging to find useful information. What about a few, on point results? Well, that’s not what today’s technology delivers. It is a fiction about which vendors and customers seem to suspend disbelief.
With a few minor edits—for example, a genuflection to “knowledge—this 2008 Findability essay is as fresh today as it was when Google output its PDF version.
Several observations:
First, the freshness of the Findability paper underscores the staleness and stasis of enterprise search in the past six years. If you scan the free search vendor profiles at www.xenky.com/vendor-profiles, explanations of the benefits and functions of search from the 1980s are also applicable today. Search, the enterprise variety, seems to be like a Grecian urn which “time cannot wither.”
Second, the assertions about the strengths and weaknesses of search were and still are presented without supporting facts. Everyone in the enterprise search business recycles the same cant. The approach reminds me of my experience questioning a member of a sect. The answer “It just is…” is simply not good enough.
Third, the Google Search Appliance has become a solution that costs as much, if not more, than other big dollar systems. Just run a query for the Google Search Appliance on www.gsaadvantage.gov and check out the options and pricing. Little wonder than low cost solutions—whether they are better or worse than expensive systems—are in vogue. Elasticsearch and Searchdaimon can be downloaded without charge. A hosted version is available from Qbox.com and is relatively free of headaches and seven figure charges.
Net net: Enterprise search is going to have to come up with some compelling arguments to gain momentum in a world of Big Data, open source, and once burned twice shy buyers. I wonder why venture / investment firms continue to pump money into what is same old search packaged with decades old lingo.
I suppose the idea that a venture funded operation like Attivio, BA Insight, Coveo, or any other company pitching information access will become the next Google is powerful. The problem is that Google does not seem capable of making its own enterprise search solution into another Google.
This is indeed interesting.
Stephen E Arnold, July 28, 2014
Pre Oracle InQuira: A Leader in Knowledge Assessment?
July 28, 2014
Oracle purchased InQuira in 2011. One of the writers for Beyond Search reminded me that Beyond Search covered the InQuira knowledge assessment marketing ploy in 2009. You can find that original article at http://bit.ly/WYYvF7.
InQuira’s technology is an option in the Oracle RightNow customer support system. RightNow was purchased by Oracle in 2001. For those who are the baseball card collectors of enterprise search, you know that RightNow purchased Q-Go technology to make its customer support system more intuitive, intelligent, and easier to use. (Information about Q-Go is at http://bit.ly/1nvyW8G.)
InQuira’s technology is not cut from a single chunk of Styrofoam. InQuira was formed in 2002 by fusing the Answerfriend, Inc. and Electric Knowledge, Inc. systems. InQuira was positioned as a question answering system. For years, Yahoo relied on InQuira to deliver answers to Yahooligans seeking help with Yahoo’s services. InQuira also provided the plumbing to www.honda.com. InQuira hopped on the natural language processing bandwagon and beat the drum until it layered on “knowledge” as a core functionality. The InQuira technology was packaged as a “semantic processing engine.”
InQuira used its somewhat ponderous technology along with AskJeeves’ type short cuts to improve the performance of its system. The company narrowed its focus from “boil the ocean search” to a niche focus. InQuira wanted to become the go to system for help desk applications.
InQuira’s approach involved vocabularies. These were similar to the “knowledge bases” included with some versions of Convera. InQuira, according to my files, used the phrase “loop of incompetence.” I think the idea was that traditional search systems did not allow a customer support professional to provide an answer that would make customers happy the majority of the time. InQuira before Oracle emphasized that its system would provide answers, not a list of Google style hits.
The InQuira system can be set up to display a page of answers in the form of sentences snipped from relevant documents. The idea is that the InQuira system eliminates the need for a user to review a laundry list of links.
The word lists and knowledge bases require maintenance. Some tasks can be turned over to scripts, but other tasks require the ministrations of a human who is a subject matter expert or a trained indexer. The InQuira concept knowledge bases also requires care and feeding to deliver on point results. I would point out that this type of knowledge care is more expensive than a nursing home for a 90 year old parent. A failure to maintain the knowledge bases usually results in indexing drift and frustrated users. In short, the systems are perceived as not working “like Google.”
Why is this nitty gritty important? InQuira shifted from fancy buzzwords as the sharp end of its marketing spear to the more fuzzy notion of knowledge. The company, beginning in late 2008, put knowledge first and the complex, somewhat baffling technology second. To generate sales leads, InQuira’s marketers hit on the idea of a “knowledge assessment.”
The outcome of the knowledge marketing effort was the sale of the company to Oracle in mid 2011. At the time of the sale, InQuira had an adaptor for Oracle Siebel. Oracle appears to have had a grand plan to acquire key customer support search and retrieval functionality. Armed with technology that was arguably better than the ageing Oracle SES system, Oracle could create a slam dunk solution for customer support applications.
Since the application, many search vendors have realized that some companies were not ready to write a Moby Dick sized check for customer support search. Search vendors adopted the lingo of InQuira and set out to make sales to organizations eager to reduce the cost of customer support and avoid the hefty license fees some vendors levied.
What I find important about InQuira are:
- It is one of the first search engines to be created by fusing two companies that were individually not able to generate sustainable revenue
- InQuira’s tactic to focus on customer support and then add other niche markets brought more discipline to the company’s message than the “one size fits all” that was popular with Autonomy and Fast Search.
- InQuira figured out that search was not a magnetic concept. The company was one of the first to explain its technology, benefits, and approach in terms of a nebulous concept; that is, knowledge. Who knows what knowledge is, but it does seem important, right?
- The outcome of InQuira’s efforts made it possible for stakeholders to sell the company to Oracle. Presumably this exist was a “success” for those who divided up Oracle’s money.
Net net: Shifting search and content processing to knowledge is a marketing tactic. Will it work in 2014 when search means Google? Some search vendors who have sold their soul to venture capitalists in exchange for millions of jump start dollars hope so.
My thought is that knowledge won’t sell information retrieval. Once a company installs a search systems, users can find what they need or not. Fuzzy does not cut it when users refuse to use a system, scream for a Google Search Appliance, or create a work around for a doggy system.
Stephen E Arnold, July 28, 2014
From Search to Sentiment
July 28, 2014
Attivio has placed itself in the news again, this time for scoring a new patent. Virtual-Strategy Magazine declares, “Attivio Awarded Breakthrough Patent for Big Data Sentiment Analysis.” I’m not sure “breakthrough” is completely accurate, but that’s the language of press releases for you. Still, any advance can provide an advantage. The write-up explains that the company:
“… announced it was awarded U.S. Patent No. 8725494 for entity-level sentiment analysis. The patent addresses the market’s need to more accurately analyze, assign and understand customer sentiment within unstructured content where multiple brands and people are referenced and discussed. Most sentiment analysis today is conducted on a broad level to determine, for example, if a review is positive, negative or neutral. The entire entry or document is assigned sentiment uniformly, regardless of whether the feedback contains multiple comments that express a combination of brand and product sentiment.”
I can see how picking up on nuances can lead to a more accurate measurement of market sentiment, though it does seem more like an incremental step than a leap forward. Still, the patent is evidence of Attivio’s continued ascent. Founded in 2007 and headquartered in Massachusetts, Attivio maintains offices around the world. The company’s award-winning Active Intelligence Engine integrates structured and unstructured data, facilitating the translation of that data into useful business insights.
Cynthia Murrell, July 28, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Searchcode Is a Valuable Resource for Developers
July 28, 2014
Here is a useful tool that developers will want to bookmark: searchcode does just what its name suggests—paste in a snippet of code, and it returns real-world examples of its use in context. Great for programming in an unfamiliar language, working to streamline code, or just seeing how other coders have approached a certain function. The site’s About page explains:
“Searchcode is a free source code and documentation search engine. API documentation, code snippets and open source (free software) repositories are indexed and searchable. Most information is presented in such a way that you shouldn’t need to click through, but can if required.”
Searchcode pulls its samples from Github, Bitbucket, Google Code, Codeplex, Sourceforge, and the Fedora Project. There is a way to search using special characters, and users can filter by programming language, repository, or source. The tool is the product of one Sydney-based developer, Ben E. Boyter, and is powered by open-source indexer Sphinx Search. Many, many more technical details about searchcode can be found at Boyter’s blog.
Cynthia Murrell, July 28, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Snowden Effect on Web Search
July 27, 2014
If you are curious about the alleged impact of intercepts and monitoring on search, you will want to read “Government Surveillance and Internet Search Behavior.” You may have to pay to access the document. Here’s a passage I noted:
In the U. S., this was the main subset of search terms that were affected. However, internationally there was also a drop in traffic for search terms that were rated as personally sensitive.
Stephen E Arnold, July 27, 2014
Sponsors of Two Content Marketing Plays
July 27, 2014
I saw some general information about allegedly objective analyses of companies in the search and content processing sector.
The first report comes from the Gartner Group. The company has released its “magic quadrant” which maps companies by various allegedly objective methods into leaders, challengers, niche players, and visionaries.
The most recent analysis includes these companies:
Attivio
BA Insight
Coveo
Dassault Exalead
Exorbyte
Expert System
HP Autonomy IDOL
IBM
HIS
Lucid Works
MarkLogic
Mindbreeze
Perceptive ISYS Search
PolySpot
Recommind
Sinequa
There are several companies in the Gartner pool whose inclusion surprises me. For example, Exorbyte is primarily an eCommerce company with a very low profile in the US compared to Endeca or New Zealand based SLI Systems. Expert System is a company based in Italy. This company provides semantic software which I associated with mobile applications. IHS (International Handling Service) provides technical information and a structured search system. MarkLogic is a company with XML data management software that has landed customers in publishing and the US government. With an equally low profile is Mindbreeze, a home brew search system funded by Microsoft-centric Fabasoft. Dassault Exalead, PolySpot, and Sinequa are French companies offering what I call “information infrastructure.” Search is available, but the approach is digital information plumbing.
The IDC report, also allegedly objective, is sponsored by nine companies. These outfits are:
Attivio
Coveo
Earley & Associates
HP Autonomy IDOL
IBM
IHS
Lexalytics
Sinequa
Smartlogic
This collection of companies is also eclectic. For example, Earley & Associates does indexing training, consulting, and does not have a deep suite of enterprise software. IHS (International Handling Services) appears in the IDC report as a knowledge centric company. I think I understand the concept. Technical information in Extensible Markup Language and a mainframe-style search system allow an engineer to locate a specification or some other technical item like the SU 25. Lexalytics is a sentiment analysis company. I do not consider figuring out if a customer email is happy or sad the same as Coveo’s customer support search system. Smartlogic is interesting because the company provides tools that permit unstructured content to be indexed. Some French vendors call this process “fertilization.” I suppose that for purists, indexing might be just as good a word.
What unifies these two lists are the companies that appear in both allegedly objective studies:
Attivio
Coveo
HP
IBM
IHS (International Handling Service)
Sinequa
My hunch is that the five companies appearing in both lists are in full bore, pedal to the metal marketing mode.
Attivio and Coveo have ingested tens of millions in venture funding. At some point, investors want a return on their money. The positioning of these two companies’ technologies as search and the somewhat unclear knowledge quotient capability suggest that implicit endorsement by mid tier consulting firms will produce sales.
The appearance of HP and IBM on each list is not much of a surprise. The fact that Oracle Endeca is not in either report suggests that Oracle has other marketing fish to fry. Also, Elasticsearch, arguably the game changer in search and content processing, is not in either pool may be evidence that Elasticsearch is too busy to pursue “expert” analysts laboring in the search vineyard. On the other hand, Elasticsearch may have its hands full dealing with demands of developers, prospects, and customers.
IHS has not had a high profile in either search or content processing. The fact that International Handling Services appears signals that the company wants to market its mainframe style and XML capable system to a broader market. Sinequa appears comfortable with putting forth its infrastructure system as both search and a knowledge engine.
I have not seen the full reports from either mid tier consulting firm. My initial impression of the companies referenced in the promotional material for these recent studies is that lead generation is the hoped for outcome of inclusion.
Other observations I noted include:
- The need to generate leads and make sales is putting multi-company reports back on the marketing agenda. The revenue from these reports will be welcomed at IDC and Gartner I expect. The vendors who are on the hook for millions in venture funding are hopeful that inclusion in these reports will shake the money trees from Boston to Paris.
- The language used to differentiate and describe the companies referenced in these two studies is unlikely to clarify the differences between similar companies or make clear the similarities. From my point of view, there are few similarities among the companies referenced in the marketing collateral for the IDC and Gartner study.
- The message of the two reports appears to be “these companies are important.” My thought is that because IDC and Gartner assume their brand conveys a halo of excellence, the companies in these reports are, therefore, excellent in some way.
Net net: Enterprise search and content processing has a hurdle to get over: Search means Google. The companies in these reports have to explain why Google is not the de facto choice for enterprise search and then explain how a particular vendor’s search system is better, faster, cheaper, etc.
For me, a marketer or search “expert” can easily stretch search to various buzzwords. For some executives, customer support is not search. Customer support uses search. Sentiment analysis is not search. Sentiment analysis is a signal for marketers or call center managers. Semantics for mobile phones, indexing for SharePoint content, and search for a technical data sheet are quite different from eCommerce, business intelligence, and business process engineering.
A fruit cake is a specific type of cake. Each search and content processing system is distinct and, in my opinion, not easily fused into the calorie rich confection. A collection of systems is a lumber room stuffed with different objects that don’t have another place in a household.
The reports seem to make clear that no one in the mid tier consulting firms or the search companies knows exactly how to position, explain, and verify that content processing is the next big thing. Is it?
Maybe a Google Search Appliance is the safe choice? IBM Watson does recipes, and HP Autonomy connotes high profile corporate disputes.
Elasticsearch, anyone?
Stephen E Arnold, July 27, 2014
Honk Tracks Search Marketing Memes
July 26, 2014
The Honk page for Beyond Search now tracks information retrieval marketing memes. The information at http://bit.ly/1uqWxfA now includes a discussion of a coinage designed to sell “search” without using the word “search.” Is the approach likely to reverse the fortunes of search vendors who face increasingly intense uphill battles to generate substantive revenue? The Honk “Meme of the Moment” updates will keep you posted.
Stephen E Arnold, July 26, 2014
PetMatch for iOS Finds Furry Friends
July 25, 2014
A new image-based search tool can take some of the research out of adopting a pet. Lifehacker turns our attention to the free iOS app in, “PetMatch Searches for an Adoptable Pet Based on Appearance.” Now, pet lovers who see their perfect pet on the street can take a picture and find local doppelgangers in need of homes. Perhaps this will help lower dog-napping rates. Reporter Dave Greenbaum notes:
“You should never adopt an animal solely based on looks, of course—you should research the personality of the breed you want—but looks are a factor. This app works great for mixed breed dogs when you aren’t sure what kind of dog you are looking at. I like the fact it will look at local adoption agencies to find a match, too. Online services like Petfinder.com help you find local pets to adopt, but you have to know which breed you are looking for first, and searching for mixed breed dogs (common at shelters) is difficult. This app makes it easy to do a reverse image search and do your research based on the results.”
Another point to note is that PetMatch includes a gallery of dog and cat breeds, so if the picture is in your head instead of your phone, you can still search for a look-alike. It’s a clever idea, and an innovative use of image search functionality.
Cynthia Murrell, July 25, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
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