By Jennifer Bi
Natural language processing, big data, machine learning — these are all big topics. Seriously, Google it or listen to a Ted talk, it’s everywhere.
But let’s break it down, because these buzzwords are often thrown around and rarely explained at the fundamental level. What exactly is natural language processing (NLP) and why is it relevant to you and your business?
I spoke with our resident linguist Ascander Dost here at SalesforceIQ to get down to the basics. Here’s what I learned about the term “NLP,” how it can benefit your workflow, and how to leverage textual data to strengthen relationships with customers.
What is Natural Language Processing (NLP)?
It’s a term we can break up into three criteria: Natural, Language, and Processing. It seems self-explanatory, but having three broad terms summed together is intimidating at first, so let’s break it down.
At the “big picture” level, natural language processing is about mimicking the way humans understand language. “Natural language” is nuanced and rife with meaning. Take for instance when people browse news articles, in the matter of seconds, your brain recognizes the tone of the article and the author’s perspective on the subject matter.
The “processing” part of NLP means imitating a human level of understanding language with machines. Tackling language nuances such as metaphor and sarcasm in a programmatic way can be a lofty challenge, and that’s the challenge met by linguists and data scientists today.
What are the applications of NLP?
Practical applications can range from sentiment analysis of social media conversations to search auto-completion on your favorite search engine. These applications of NLP stem from large volumes of text that can be mined for trends and richer insights into your business, such as your twitter feed, Google search results, or reviews in the Apple app store.
That’s natural language processing doing its work.
You can quickly see the importance of NLP for the applications you use on a daily basis: email, social media, CRM, and the list goes on.
Your business communication runs on the movement and organization of textual data.
How NLP Can Change Your Work Productivity
Let’s talk specifically about NLP and email. You get emails every day — maybe even hundreds per day, and often the communication can be segmented out into various “buckets,” depending on your occupation: emails to prospective clients, email updates to your manager, email replies to your team members.
Improving work-flow by automating repetitive processes
When you apply natural language processing to email, you start to recognize patterns to accelerate your workflow and implement features that save you time.
We see this in Gmail’s split between primary, promotional and social emails. Gmail quickly assesses every incoming email’s content and splits them amongst the different categories, so you no longer have to mentally sift through Gap 50% off sales emails and your weekly subscription to Wall Street Journal to get through personal messages from friends and coworkers.
NLP also gives you the power to move through text more intelligently, and manipulate text with smart features. My personal favorite is SalesforceIQ’s Templates, stored email messages that can be called on with keyboard shortcuts. Especially for sales reps who handle communication with hundreds of accounts, Templates can seriously cut down on email time and increase productivity.
As NLP becomes more advanced, you unlock a whole new level of automation and predictive analytics to your inbox. Your inbox will be able to detect what to send and when, based on your writing habits, sending history, and other email data.
Consider the future of email: Your inbox will get good enough to identify where a prospective customer is in the sales lifecycle, predict when they’re ready for the next stage, and suggest the right email to get you there.
Slowly, your email will learn to work for you.
Digging Deeper Into Rich Data Insights
NLP doesn’t just autocomplete your sentences; it can also process text on the semantic level.
Think of language as a data hierarchy: You can analyze text on a letter to letter basis, word by word basis, or at a higher level: What does this paragraph of text mean? What new perspective did you gain from an English essay? How do you feel after reading the latest article from Huffington Post?
When you apply NLP to this higher level of analysis, you can derive advanced insights into:
- How your business is doing
- What customers are saying about your business
- What business relationships need more nurturing
Sentiment Analysis, Customer Feedback, and More
For example, using sentiment analysis you can evaluate how customers are feeling — are they happy with your product? Do they feel strongly about your brand?
Who are your unhappy customers and what are the ways to prevent their accounts from falling through?
These are the big questions that richer language processing can answer, or at at least endeavor to answer as technology advances. Over time, NLP will help monitor your business’s health and business problems that don’t fit easily into a numerical model.
Why is NLP relevant for your business?
Working people work and interact with large amounts of text all the time; all of us are constantly checking email, scrolling through blogs, and sending documents. If we can extract intelligence from text, we’ll get smarter about our business, build better products, and provide a better experience for our customers.
This post is a part of our Future of Work series, where we describe how the way we work is evolving. Read the first in the series: Is Your Sales Strategy Outdated?
Originally published at www.salesforceiq.com.