Every day, companies of all sizes in the telemarketing and communications industries are flooded with data from customers, clients and stakeholders.
That data holds valuable insights you can leverage to reduce average handling time, make better strategic decisions and increase profits. But before that can happen, you need to process, analyze and present the data in a way that makes sense to decision makers.
That's where Natural Language Processing comes in.
Natural Language Processing is a field of Artificial Intelligence that gives machines the ability to read, understand and derive meaning from human languages.
With NLP, we can use computers to do things like:
- Find and separate types of feedback (positive and negative, mentions of distinctive features such as colour)
- Analyze text documents
- Identify different groups of customers or users (this helps us learn which products they may prefer, the lifetime value of those products and churn rate)
- Categorize text according to questions asked (for example, are customers contacting your company looking for the answer to a question, hoping to schedule an appointment or expecting you to help solve a problem)
- Translate text from one language into another
- Build personal assistant applications and voice recognition software that respond to users' voices
- Run chat bots that greet visitors to your website, which can help connect people with the information they need more effectively in some circumstances
Natural Language Processing plays a critical role in interactions between humans and machines. It often overlaps with machine learning. Recent progress in Natural Language Processing, machine learning and data science means we can write programs to translate, analyze and summarize text.
Natural Language Processing automates parts of tedious, time-consuming, "behind-the-scenes" tasks like data processing, completing them with great accuracy.
It can help you learn what's driving inbound calls so you can dedicate resources to reduce average handling time, serve your customers more efficiently, and run a more cost-effective business.
One specific application is that it can allow you to improve information retrieval workflows. For example, you may want to search through your internal documents to match phrases. If you searched for the phrase "one day before", you might seek matches for "yesterday", "the previous day", etc. Finally, you and your employees will be able to focus on tasks that demand complex skills or bring in more revenue.
You probably collect data from different sources, like phone trees, recordings of customer calls, surveys, sales staff and more. It can feel overwhelming and even scary to think about how you'll make sense of it all, and you don't have the in-house time or talent to dedicate to this critical (and monumental) task.
That's where we can help. Combining our highly specialized skills in Natural Language Processing with our understanding of many cornerstone algorithms used in this area, we custom develop the right approach to solve the right problem, then implement the solution flawlessly.