Let’s look at how business intelligence and operations are improved when incorporating natural language systems. Understanding your customers, indirectly
For SMEs, the challenge with big data isn’t so much collecting it as it is sifting through it. They simply don’t have a large enough workforce to do it by hand. Using a Natural Language Processing API
, it’s possible to hook into existing technology that parses through data and draws meaningful conclusions from it.
Developing customer models and customer personas help determine what new products will be popular. Companies refine existing products to better suit certain groups of customers. This makes companies more efficient without costly – and often ineffective – focus groups. Google search
The Google search algorithm that determines what search results are shown now examines the search queries using natural language. The search giant wants to understand the meaning behind a given search. Over 80 percent of searches received by Google every day are unique, which presents a challenge because there are too many searches to create individual results for each one at that scale.
Natural language is now powerful enough that Google can understand when one search essentially means the same as another, even though it’s been worded slightly differently. Rather than showing one search result to one searcher and a different one to the second searcher, a single search result is produced, which is identical for both searches with the same meaning.
The search engine also looks at recent searches by the same person, and other people who have matching tastes, to interpret the meaning behind each search to hopefully provide the most useful search results. The controversial chatbots
In a move that might not appeal to everyone who dislikes computerized phone systems, online chatbots
are becoming more prevalent. They learn from previous question and answer sessions. They can match the new question with a previous session and provide the same answer. When there isn’t a perfect match, natural language algorithms look for indicators to create improved understanding. Whether this is used to develop an appropriate response or simply to categorize the query,it is directed to the correct customer service operator and may cut down on response times.
There have been some developments in natural language, which have advantages. Being able to initiate a call to emergency services through your phone by speaking to it when you cannot reach it following a car accident has been useful in many recent cases. The iPhone was updated in 2016
to allow calls to emergency services, partly in response to human need.
Natural language is here to stay. Companies are using it to learn more about their customers’ interests and change their offerings accordingly. As business intelligence increases through the use of natural language interpretation, it is hoped that end customers will reap more of the benefits too.