Jun

Beware the lure of crowdsourced data

Crowdsourced data can often be inconsistent, messy or downright wrong 

We all like something for nothing, that’s why open source software is so popular. (It’s also why the Pirate  Bay exists). But sometimes things that seem too good to be true are just that. 

Repustate is in the text analytics game which means we needs lots and lots of data to model certain  characteristics of written text. We need common words, grammar constructs, human-annotated corpora  of text etc. to make our various language models work as quickly and as well as they do. 

We recently embarked on the next phase of our text analytics adventure: semantic analysis. Semantic  analysis the process of taking arbitrary text and assigning meaning to the individual, relevant components.  For example, being able to identify “apple” as a fruit in the sentence “I went apple picking yesterday” but to  identify “Apple’ the company when saying “I can’t wait for the new Apple product announcement” (note:  even though I used title case for the latter example, casing should not matter)

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The End of Digital Monitoring Paradigm

                                 

Digital industry is changing rapidly.

For the last decade analysis of social chatter and capture of consumer sentiment was considered the cutting edge of the marketing strategy.  In these early days of the new era of digital information businesses were told to listen to what market is saying about them. They were educated on the importance of media monitoring and the advantages it creates for strategic growth.

This picture has become outdated.

Listening to Big Data, in all its aspects and forms, is no longer enough. After you successfully listened and understood what customer said the next natural step would be to act, or respond. And so the digital domain is now spreading to include responses, with a host of innovative technological solutions reshaping the field rapidly.  Advances in artificial intelligence in particular create disruptive scalable opportunities in the space traditionally known for its slow manual progression.

Facebook was among the firstto enter the market, introducing bots into the process of connecting users with brands. Then there was Microsoft's turn.

Following these developments bots became the hottest trend in Silicon Valley in 2016.

nmodes fits seamlessly into this new world order. We deliver AI solutions that power business sales process. Our listening solution accurately monitors and captures real-time needs and interests of individual customers within the defined audience. And our Intelligent Assistant solution brings scalability to responses without compromising on quality.  

 

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When Big Data is not so big anymore

                                                   

We are inundated with information. There is so much information around us they coined a special term - Big Data. To emphasize the sheer size of it.

It is, of course, a problem - to deal with a large amount of data. Various solutions have been created to address it efficiently.  

At nmodes we developed a semantic technology that accurately filters relevant conversations. We applied it to social networks, particularly Twitter. Twitter is a poster child of Big Data. They have 500 million conversations every day. A staggering number. And yet, we found that for many topics, when they are narrowed down and accurately filtered, there are not that many relevant conversations after all.

No more than 5 people are looking for CRM solutions on an average day on Twitter. Even less - two per day on average - are asking for new web hosting providers explicitly, although many more are complaining about their existing providers (which might or might not suggest they are ready to switch or looking for a new option).  

We often have businesses coming to us asking to find relevant conversations and expecting a large number of results. This is what Big Data is supposed to deliver, they assume. Such expectation is likely a product of our ‘keyword search dependency’. Indeed, when we run a keyword search on Twitter, or search engines, or anywhere we get a long list of results. The fact that most of them (up to 98% in many cases) are irrelevant is often lost in the visual illusion of having this long, seemingly endless, list in front of our eyes.

With the quality solutions that accurately deliver only relevant results we experience, for the first time, a situation when there are no longer big lists of random results. Only several relevant ones.  

This is so much more efficient. It saves time, increases productivity, clarifies the picture, and makes Big Data manageable.  

Time for businesses to embrace the new approach.

 

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