Search Wizards Speak: Oleg Rogynskyy, Semantria
Semantria focuses on a class of problems that a few years ago would have been outside the reach of many firms. He said:
We make it simple for our clients to solve the following problems: First, some organizations have too much text to read. For example, a Twitter stream or surveys with many responses. Also, there is the need to move quickly and reduce the time to get to market. Many survey results come with an expiry date before they’re irrelevant. Then there is reporting the information. Anyone can use their Excel smarts to build simple/interesting reports and visuals out of unstructured data. But that can take some time, and Semantria accelerates this step. Finally, users need to analyze text with the same impartiality each time. A human might see a glass as half full or half empty, but Semantria will always see a glass with water.
Changing the Approach to Enterprise Search: Horse First
The greatest issue is when there is a growing crevasse between the wealth of information and findability.
Amazon and Its Money Losing Model
The former employee then offers this observation or is it a threat?
If I were an Amazon competitor, I’d actually regard Amazon’s current run of quarterly losses as a terrifying signal. It means Amazon is arming itself to take the contest to higher ground. The retail game is about to become more, not less, punishing.
All three articles in full text with links below the line.
Search Wizards Speak: Oleg Rogynskyy, Semantria
Semantria is a company focused on providing text and sentiment analysis to anyone. The company’s approach is to streamline the analysis of content to that in less than three minutes and for a nominal $1,000, the power of content processing can help answer tough business questions.
The firm’s founder is Oleg Rogynskyy, who has worked at Nstein (now part of Open Text) and Lexalytics. The idea for Semantria blossomed from Mr. Rogynskyy’s insight that text analytics technology was sufficiently mature so that it could be useful to almost any organization or business professionals.
I interviewed Mr. Rogynskyy on October 24, 2013. He told me:
At Semantria, we want to simplify and democratize access to text analytics technology. We want people to be able to get up and running in no time, with a small budget, and actually derive value from our technology. The classic story is you buy a system worth $100k and don’t deploy it.
Semantria focuses on a class of problems that a few years ago would have been outside the reach of many firms. He said:
We make it simple for our clients to solve the following problems: First, some organizations have too much text to read. For example, a Twitter stream or surveys with many responses. Also, there is the need to move quickly and reduce the time to get to market. Many survey results come with an expiry date before they’re irrelevant. Then there is reporting the information. Anyone can use their Excel smarts to build simple/interesting reports and visuals out of unstructured data. But that can take some time, and Semantria accelerates this step. Finally, users need to analyze text with the same impartiality each time. A human might see a glass as half full or half empty, but Semantria will always see a glass with water.
One of the most interesting aspects of Semantria is that the company delivers its solution as a cloud service. Mr. Rogynskyy observed:
We are happily in the cloud, and in the cloud we trust. We have android and iOS software development kits in the works, so whoever wants to talk to our API from mobile devices will be doing it with ease very soon.
You can get more information about Semantria at https://semantria.com.
This interview is one or more than 60 full-text interviews with individuals who are deeply involved in search, content processing, and analytics. You can find the full series at www.arnoldit.com/search-wizards-speak.
Stephen E Arnold, October 28, 2013
Changing the Approach to Enterprise Search: Horse First
Pebble Road’s article analyzing search is titled The Curse of Enterprise Search and How to Break It. The curse referred to is created by the misconception that once an enterprise search software has been purchased it will do all the work and the business it is being used for is already handled. The article argues against this lackadaisical approach to search, explaining that search needs to be implemented and designed for a given business with the business’s users in mind. It argues that “search is a negotiation” which is not simply a means to an end but a way to figure out the right question. The article explains with a comparison to camera shopping,
“When you’re searching for a camera, and if you don’t know exactly which one you want, you’re going to start on a search journey, or the negotiation. The journey may take you from locating the right type of cameras ? to comparing them ? to verifying their details. These three modes are not the same. You are seeking different outcomes in each mode. The modes are like layers of meaning. Meaning that will eventually lead you to make a decision.”
Metadata and appropriate interfaces are the answer proposed by the article to designing support search modes that will be useful and productive. The greatest issue is when there is a growing crevasse between the wealth of information and findability. To simplify, don’t put the cart before the horse. Design search for your business and then put in place.
Chelsea Kerwin, October 28, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
Amazon and Its Money Losing Model
I read “Amazon and the Profitless Business Model Fallacy.” The article was the work of a person who once worked at Amazon, departing in 2004. I assume that some of Amazon’s processes are unchanged, but nine years is a long time, even for an addled 70-year-old goose like me.
The main point of the write up is that many people assume that Amazon is a charity. Amazon, the article points out, is “a classic fixed cost business model.” The company uses the Internet:
to get maximum leverage out of its fixed assets, and once it achieves enough volume of sales, the sum total of profits from all those sales exceed its fixed cost base, and it turns a profit. It already has exceeded this hurdle in its past.
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The article asks:
Does Amazon lose money on sales of some individual items? For sure. The first Kindle ebooks that were priced at $9.99 when Amazon had to pay more than that per copy to publisher were one example. Giant, heavy electronics items that Amazon sometimes ships for free when the shipping cost is clearly non-trivial and cost more than the usual thin margins on such goods are another.
The Bezos brilliance takes this approach:
Amazon has decided to continue to invest to arm itself for a much larger scale of business. If it were purely a software business, its fixed cost investments for this journey would be lower, but the amount of capital required to grow a business that has to ship millions of packages to customers all over the world quickly is something only a handful of companies in the world could even afford.
On the subject of Amazon’s interesting financial report, the article states what is obvious to most analysts who have tried to figure out where the money comes from and where the money goes:
The irony of all this is that while Amazon’s public financial statements make it extremely difficult to parse out its various businesses, it is extremely forthright and honest about its business plans and strategy. It’s the reason Jeff continues to reprint its first ever letter to shareholders from 1997 in its annual report every year. The plan is right there before our eyes, but so many continue to refuse to take it at face value. As a reporter, it must be so boring to parrot the same thing from Jeff and his team year after year, so different narratives must be spun when the overall plan has not changed.
The former employee then offers this observation or is it a threat?
If I were an Amazon competitor, I’d actually regard Amazon’s current run of quarterly losses as a terrifying signal. It means Amazon is arming itself to take the contest to higher ground. The retail game is about to become more, not less, punishing.
Several observations:
Amazon is a giant company with customers, cash, and clout. Those who try to get in its way find out that the Amazon business model is not much less forgiving than Google’s. Google has made little headway in online shopping and that suggests some bright folks have bumped into one or two of Amazon’s pointy parts.
Second, price cutting is a great business tactic. Once the competition is gone, then it is pretty easy to move forward. A number of moguls figured this out decades ago. In today’s regulation-soft environment, commercial enterprisers are functioning more or less like nation states. Different economic rules apply to nation states. Individuals who shop at the company store have fewer options.
Third, Amazon is one of the firms developing a monoculture for its customers. Once one gets into the Prime, one-click, personalization approach to online activities, an old adage kicks in:
Like a soft bed, a bad habit is easy to get into and hard to get out of.
Now my interest—now a hobby, not a job—is search and retrieval. How does the Amazon approach work in search. Amazon offers what I call “corset search.” If you want to get into the darned thing, be prepared to experience some push and pull. If you want a cloud based search system, Amazon is, as I wrote in one of my for-fee columns, a “search lazy Susan.” Just dial up an alternative running on the Amazon system.
Easy. Cheap at least at the outset. Mostly reliable. What more could a vendor want? What more would a user want?
That in my view is the problem with the WalMart approach to technology. Amazon is one of the manifestations of the deep divides that continue to fracture behaviors. I am okay with making my way through an increasingly medieval landscape.
I suppose Wall Street is learning that what look like losses may be something else. We have entered the Dimonization Era. Money is not what it seems perhaps?
Stephen E Arnold, October 27, 2013
