When we think of data, we often imagine numbers and metrics that can be gleaned from financial and quantity-based statistics. If a specific vehicle model has a higher number of sales in a given year, for example, manufacturers may incorporate features of that vehicle in other models to increase sales across the board.
Although hard stats are useful, marketing directors and customer service analysts know that qualitative information like customer satisfaction represents a huge, unstructured data set that can’t easily be represented by a numerical value. It is possible to count the number of negative online reviews a business receives, but relying on such numbers does not give insight into why the review was negative, or how the business can improve to convert these experiences into positive business interactions.
When it comes to customer opinions and attitudes, a majority of valuable information lies in the language that consumers use to describe their experiences. Language, therefore, represents a huge data set that many businesses have access to through recorded phones calls and archived mentions of their brand online. The problem is that businesses often lack an effective way to extract meaning from this kind of unstructured data.
By leveraging AI equipped with natural language processing (NLP), businesses can convert thousands of phone calls and hundreds of online mentions into measurable data sets to improve their customer satisfaction and branding practices.
Processing Natural Language with AI
As IoT and Artificial Intelligence (AI) becomes integral to our processes of collecting and analyzing crucial business data, it is important to consider how to get search tools and voice assistants to understand the way we naturally use language, and convert these understandings into valuable business metrics and insights.
Natural language processing is a core response to this growing need for concise data sets derived from language. Within this domain of AI, machines are learning how to better process and respond to human speech through NLP. Speech recognition, question answering, and sentiment analysis are NLP tools that create an opportunity for AI to become adept at interpreting and responding to voice commands and typed queries.
Applying NLP to Business Operations
AI's use of NLP to recognize speech and even talk back in a natural way was evident in the 2018 I/O event where Google demonstrated its Assistant’s ability to successfully gather meaningful data and book appointments through two automated phones calls with real humans. As the machine learning capabilities of AI become more comprehensive and in-depth, brand directors, market research analysts, and digital marketing specialists can expect to gain valuable insights that are scalable and rapidly produced from these NLP advancements in AI.
Online product reviews, social media mentions, and other forms of customer feedback can be scanned using NLP algorithms in a process referred to as opinion mining, Opinion mining is used to rapidly identify which words and phrases indicate a negative response versus a positive or neutral response. The result? Unstructured, language-based data now can be turned into valuable marketing insights regarding customer experience or public opinion about a particular business brand.
NLP also can be used by businesses internally to expedite language-based operations. During the hiring process, larger companies can make use of NLP when reviewing thousands of applications submitted to a job post. NLP algorithms can conduct an initial filtering process that scans applications and resumes for keywords and phrases that are relevant to the job descriptions in order to minimize the time HR representatives must spend on selecting the top applicants to move forward with in the hiring process.
Similarly, lawyers and loan officers can save thousands of hours each year by employing AI machines equipped with NLP to take over the task of reviewing legal documents for pertinent information, allowing them to make more efficient use of their time.
Aeris: Reliable Network for All Types of Data
With advancements in NLP, AI machines are becoming more adept at turning language into measurable data sets. Whether it’s from IoT devices or advanced online technology, a reliable network is required for any business to collect and process data into meaningful interpretations. At Aeris, we provide networks that help businesses across the board securely and reliably collect and manage data.
To learn more about how Aeris can provide your operation with a reliable network, Contact Us today.