Discover How OPINATOR Can Help You Generate Value from Unstructured Data to Boost Your Business Through Text Analytics
Did you know that more than 8 years ago OPINATOR started as a Text Analytics project? For it to get started, several Ph.D. professionals on Analytics and Computing had to adapt the latest tech innovations and algorithms (to date), in order to bring a unique solution to the market.
At that moment, the team reached a new milestone: a multilingual, text-oriented and digital-centered platform, focused on short and not-always-well-written texts. Because of that, it was essential to keep in mind that smart algorithms were always to be implemented and specialized, as well as constantly updated and managed by professionals. The OPINATOR team counts with linguistic experts who are dedicated to nurturing the platform (machine learning), according to any special needs or requests made by clients.
OPINATOR’s Intelligent Text Analytics (OITA) service, stands out as a leader in its niche. It’s a consolidated service, implemented by corporations in over 15 countries. The platform allows combining in real-time Text Analytics service with a full suite of digital interactions with customers such as Close The Loop modules, alert generations, message submissions, experience management, sales opportunities and churns preventions among others.
The team works constantly to bring you a window to the future. This is why we interview Inés Calvo today, an expert from the OPINATOR’s Intelligent Text Analytics (OITA) team. She unveils how the system works and how far this specialized technology goes.
Getting to Know Text Analytics
Good Morning, Inés! How are you today? Could you please tell us a little bit about what’s Text Analytics and how could it be used?
Good Morning, I’m good, thanks for asking! Sure thing, the so-called OPINATOR Intelligent Text Analytics is a categorization service mainly based on Artificial Intelligence. It processes and analyzes textual material such as real opinions from free-text qualifiers, transcriptions from phone calls or audio recordings and information from Facebook and Twitter users. Its main goal is to obtain certain behavioral patterns that will help transform that relevant information into real analytics.
Interesting, and how does the OPINATOR Intelligent Text Analytics core work?
The engine of our service is a mechanism specially optimized for short texts in online environments. Its methodology is based on the breakdown of textual material. This way, the analysis is much more practical, productive and proactive, because dividing the material into smaller blocks ensures a better focus and identification of concepts, as well as an excellent semantic-syntactic assessment and an exhaustive morphologic analysis.
Sounds complicated!
It seems like it, but it’s not! [Laughs] It is a bit like a puzzle. Once you’ve figured out the mainframe shape it’s just a matter of joining the pieces together.
And, as for the main features, could you mention anything about the most used or demanded on the market?
Our textual analysis service offers plenty of distinctive functionalities. Alongside with diverse specialized support systems and developments, it ensures an excellent fulfillment of our customer’s needs.
If I had to mention just some of them, I guess I would say:
–Sentiment Analysis, a metric closely related to Natural Language Processing (NLP). It identifies if a text is considered positive, neutral or negative.
–Multichannel Categorization of texts, complete or by semantic units.
– Effort Analysis recognizes what processes should be implemented. This will depend on the level of effort expressed by the customer. It’s also a tool for NPS.
– Emotion Analysis, which helps to identify the average emotion on a group but also on every individual category.
– Topic Extractor, a tool that easily recognizes main topics, personalities, locations, specific dates, names of enterprises, among other facts.
– Speech Analytics, a system that enables the extraction of qualitative information out of transcripted verbatims. These could be language, accent, location, but also gender, age and emotional state of the speakers.
Amazing, Inés! Thank you so much for sharing your knowledge and experience with us!
You’re very welcome, glad to help!
From Theory to Practice
In an attempt to get a closer look into the OPINATOR’s Intelligent Text Analytics world, let’s try to understand a frequent case within the financial sector:
Every day, hundreds of banks collect comments on surveys and classify them manually. This means that every single day, someone is in charge of reading and organizing those surveys. After carefully categorizing them manually they have to (also manually) create statistical reports.
Within the daily tasks of this labor, the person determines several aspects such as: “what is the main topic the customers are talking about?”, “which is the loose end?”, “which is the preferred topic?” and “which is the least favorite one?” Right after, a relevant team manages opinions sent to them. This task, as you can imagine, requires long hours of exhaustive and rigorous work.
The OPINATOR solution eases and boosts this process.
How?
- Categorization and creation of interactive dashboards
- Incident and requests management
- Case Management integration
Why?
Save time when categorizing, generating statistics and solving red-flag issues while generating value from unstructured data and boosting your potential as a leading company in the business world!
“Knowledge is power”.
F. Bacon