Find the best Natural Language Processing (NLP) Software
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Klangoo NLP API
SAS Visual Analytics
Veritone Automate Studio
You say, “Alexa, play some music.” and a device responds in a humanlike voice and starts a song. Amazing how the device activates when it hears your command, understands the intent, executes an action, and provides feedback, all within a few seconds. Such interactions are made possible by natural language processing (NLP), which uses technologies such as artificial intelligence (AI) and machine learning (ML) to understand human language.
The NLP technology also allows finding insights from within heaps of written unstructured data sources such as emails, call center transcripts, or social media conversations.
In this buyers guide, we’ll talk about NLP software solutions, what exactly they do, what are their features, what to consider when buying one, etc.
Here's what we'll cover:
What is natural language processing (NLP) software?
Natural language processing (NLP) software is a tool that uses AI and ML to help computers understand, interpret, and manipulate human language in the form of speech and text. The software offers features such as text analysis, sentiment analysis, part of speech tagging, and more to achieve that.
NLP software can be utilized in a variety of business areas such as customer service, customer experience, sales (in the form of chatbots), and data analysis.
Common features of NLP software
There are some features that most NLP solutions offer:
Text analysis/text mining
Analyze unstructured data in text in emails, social media conversations, chats, etc., and obtain easy-to-understand and useful information. It also includes tokenization to break down a string of words into semantically useful units called tokens.
Determine a chunk of text as positive, negative, or neutral and assign weighted sentiment scores.
Analyze a string of symbols (or tokens) and identify the syntactic structure of a text and the dependency relationships between words.
Semantic analysis/ topic clustering
Analyze sentences to identify the topic discussed in the text and the relationship between different concepts used in the text.
Derive insights in the form of summary reports and visualize them on charts or graphs.
Part of speech tagging
Identify the appropriate part of speech for the words in a sentence, depending on the definition of each word and its context.
Detect text in multiple languages and perform analysis on them. It also allows converting the text in one language into another language.
What type of buyer are you?
The right type of NLP software depends on your unique requirements as well as the expertise level of your in-house IT team. Check the buyer category you belong to before making a decision.
Small and midsize businesses: These buyers usually look for a tool to take care of immediate business requirements such as customer service conversation analysis, social media monitoring, website experience analysis, financial agreements, and contracts analysis. The suitable applications, in this case, are cloud-based NLP products that offer basic text analysis, semantic analysis, reporting, and language detection capabilities.
Large enterprises: These buyers want a feature-rich data analysis platform with advanced features such as speech-to-text analysis and predictive analytics. The platform should also offer integration with a wide range of enterprise tools and support functionalities such as the ability to analyze and derive insights from customer journeys across multiple channels such as social media or email.
Benefits of NLP software
Here are the key benefits of NLP software for your business:
Automation can save time: Manual data analysis on huge datasets can take days or weeks. Whereas NLP solutions can automate and complete the process in minutes or even seconds. This data processing can be performed on datasets from various sources such as documents, social media data, or online reviews data.
Build better strategies and improve customer service: NLP software is intended to help organizations find insights from emails, customer reviews, social media, support tickets, and other texts. The software uses features such as sentiment analysis, part of speech tagging, and tokenization to parse the intention of words, which allows building better strategies to fulfill customer needs.
Key considerations when selecting NLP software
Before investing in NLP software, businesses should carefully analyze their requirements.
Business requirements: Check which team will be using the NLP software—Is it going to be used entirely internally, such as by the finance team to consolidate financial agreements, or will it be used by a team such as the customer service department where external users will come into the picture. If you are purchasing it for an internal team, make sure it supports functions such as credit scoring and document search. If you want it for departments such as customer service, look for a solution with strong sentiment analysis capabilities.
Additional capabilities: Nowadays, there are advanced functionalities such as optical character recognition and speech-to-text conversion that are rapidly evolving into key business requirements. Check whether investing in an NLP system that offers such advanced capabilities will make any impact on your return on investment in the long term.
Open source tools: If your text analysis requirements exceed what existing tools on the market support or you have an IT team with specialized domain knowledge, you can go for open source NLP tools. You choose your own algorithms or methodology and implement components such as classification, tokenization, stemming, or parsing as you need.
Market trends to understand
Below are some of the NLP software-related trends:
NLP in automating customer service. Owing to the increase in digitalization, there is an upsurge in customer support tickets, which is increasing the need to process a high volume of tickets and provide fast responses to queries. NLP tools can be integrated with help desk software, which could help in automating tasks such as automatic tagging and routing of support tickets.
NLP in social media monitoring. Analyzing customer sentiments on social media helps businesses understand negative/positive perceptions about their brands, thus giving them the opportunity to improve their products/services. Additionally, NLP solutions help understand the impact of marketing campaigns and evaluate how customers react to different marketing initiatives.
With so many options, choosing the right NLP tool can be a tedious task. For real advice from real people, schedule a call with us. Don’t worry it’s free!
Note: The application selected in this guide is an example to show a feature in context and is not intended as an endorsement or recommendation. It has been taken from sources believed to be reliable at the time of publication.