When it comes to text analyzers, there’s a good bit for businesses to know. In this piece, we’ll peel back the layers to reveal what you should know and why you need to add a text analyzer to your company’s toolkit!
First, here are some stats and facts to keep in mind:
- 80-90% of text data is unstructured, and the ability to capture and organize it quickly is key.
- About 90% of all the data in the world we have created in the last 24 months — averaging 2.5 quintillion bytes per day.
- Keeping pace with all of this manually is impossible. And this is where a text analyzer comes in.
What is a Text Analyzer?
Although you probably think of basic things like tracking word count and characters when we talk about text attributes, text analyzers take the enterprise well beyond those basic stats. Text analyzers perform a wide range of functions. At its most basic, text analyzers derive meaning from text. And at its most sophisticated, it uses advanced artificial intelligence to aggregate, organize and cluster conversations based on semantic connections to create interactive data visualizations for a faster path to insight.
And the attraction to text analyzers is not only found in the technology realm. We see a variety of industries exploring the potential this visualized insight offers.
And, as we mentioned previously, there are best practices to keep in mind. So, we have tips for using a text analyzer. You’ll want to make sure you’re well versed in these capabilities – and that the tool you’re using has each of these options available (and be sure to click over to explore each in-depth):
- Keyword spotting
- Manual rules
- Text categorization
- Topic modeling
- Thematic analysis
Why are Text Analyzers Important?
So, why are text analyzers important to brands? Right now, the amount of data flowing online is almost immeasurable, averaging 2.5 quintillion bytes per day. The amount of data available has moved well beyond anything the human mind can comfortably quantify, that’s for sure.
And every day, this unreasonably massive amount of structured and unstructured data finds its way online. This is both exciting and anxiety-producing for brands hoping to get a jump on the competition – or even to just have a good sense of what their potential clients want. And they can even have trouble keeping up with who those potential clients are! We’ll get to some more specific examples in just a moment, but for now it’s important to understand how this data can look online – and why text analyzers are important when it comes time to make sense of it all.
Text analyzers are kept busy parsing text-based language – and this takes us well beyond words. Text analyzers capture sarcasm, emojis and even implied language, which makes up the basis of sentiment analysis. And then 80-90% of data that finds its way online is unstructured, adding to the complexity of analyzing it.
This is a large part of what’s done behind the scenes, as processing unstructured, raw data that isn’t easily searchable otherwise is the lifeblood of brand marketing. Pretty much every consumer post is unstructured. That’s huge.
And then top text analyzers combine it with other data sets to create an holistic view of your business and the competitive landscape:
To clarify, unstructured data is everything that is not organized neatly in an organized, predefined manner that makes it easy to search and understand. It’s most things we see online, in fact. “Structured data is highly-organized and formatted so that it’s easily searchable in relational databases. Unstructured data has no predefined format or organization, making it much more difficult to collect, process, and analyze.”
Text analyzers combine all of this structured and unstructured data in one dashboard and create order out of that chaos. It creates a way to understand and find your way through a cacophony of noises and zero in on relevant, game-changing insight and apply it to an amazing array of use cases to maximize your brand’s impact.
Ways Text Analyzers Maximize a Brand’s Consumer Impact
Text analyzers maximize a brand’s consumer and market impact by helping them understand the overarching category conversation, as well as the more dialed in brand-specific conversations. And our proprietary NLP technologies read millions of documents simultaneously and offer immediate AI-driven insights, turning text into context.
NetBase Quid extracts sentiment by analyzing insights, such as emotions, behaviors, likes, or dislikes, expressed in a sound bite. For any given topic, some mentions contain sentiment and others do not. When NetBase finds sentiment, it classifies it as one positive, negative, mixed or neutral.
Even though both sentences include the word “good,” it is clear to a human reader that the first sentence expresses a negative opinion about the iPhone while the other expresses a positive opinion. Natural Language Processing automatically understands the difference between sentences like these and uses it to accurately classify and extract insights from conversations.
Businesses depend on NLP-powered text analyzers to cut through the noise in some very specific ways. It allows them to:
- Interpret the meaning of consumers’ social media opinions with a high level of accuracy.
- Analyze not only the most basic of sentence structures, but also data based on all of the variations that may occur in over forty different languages.
- Capture consumer intent even when they are hidden behind misspellings, abbreviations, slang, sarcasm, and emojis
And because of this, businesses can rely on that accuracy when strategizing around product launches, influencer identification for collaborative partnerships, campaign planning, innovations, and even to evaluate potential mergers or head off a crisis. They know where conversations are happening, who is leading them and how to best respond. It not only saves them time, it saves them millions.
There are options out there for text analysis, and we may be a bit biased here, but NetBase Quid is honestly the best tool text analyzer you’ll find, hands down. Time and again we’ve had our natural language processing (NLP) go up against competing products, and we’ve had consumer reviews that all say the same thing: When it comes to capturing and analyzing the sentiment behind unstructured data, NetBase Quid’s next generation AI captures nuances that others miss.
We’d love to take you for a tour of the platforms to show you our text analyzer in action, so be sure to reach out for a personalized demo!