How NLP Advances Market  Research

How NLP Advances Market Research

Using NLP For Consumer Speak

Using NLP For Consumer Speak

Human language is complex. But identifying rich and relevant human insights is even more complex. Agencies have long rejected the ability of machines to correctly decode verbatims such as “I like this product, somewhat, but it needs to be sweeter”. And hence, in the past, and even today, most agencies use manual coding. However, this comes at a cost in terms of time.

Today, insight sources go beyond surveys to social media, CRM data, passive data and digital footprints. In addition, the types of data are increasingly varied, ranging from largely structured to unstructured, such as text, videos and images. As a result, it becomes increasingly necessary to process multisource data and. given the quantum of data, manual coding is often not feasible. Hence, many are increasingly using NLP or natural language processing to process textual data.

So, what is NLP? In layman’s terms, NLP is an artificial intelligence (AI) technology that allows the machine to recognise and understand the nuances of human language as it is spoken or written. It organises unstructured textual data by analysing it for relevance, spelling variations, correlation and semantic significance. It tries to understand different lexicons, grammatical syntaxes and the relation between words and phrases, just as a human does and remembers. No wonder NLP is generating a great deal of interest in intelligent content analysis in the market research industry for creating innovative and efficient marketing strategies.

At Ideal Insights Lab, NLP is being used to process qualitative, quantitative and social media data to process textual data. Let’s explore why agencies like Ideal are deploying NLP:

1) Social media sentiment analysis: NLP efficiently understands internet short forms, slang, code-switching, emoticons and emojis, and hashtags, which makes it unique and prominent in social media listening. Furthermore, sentiment analysis helps you analyse different emotions through three pre-classified groups – positive, negative, neutral – that help to drive business, deliver better customer experience and build value.

2) Text analytics: NLP converts the pile of raw data that a company derives from news, social media reviews, tweets, online surveys, voice-to-text notes or any other source into purposeful documentation that a machine learning algorithm can analyse. Adding to it, semantic search helps you understand the intent and meaning behind words. Hence, it enables businesses in intelligent decision making.

3) Topic modelling: This is a method used to classify natural topics present in textual data. It helps to extract the motivation from a large set of respondent inputs on a particular topic in qualitative analysis. These techniques do not require any human supervision. Hence, topic models are helpful in registering brand mentions in news articles or customer reviews.

With the advent of the digital era, NLP is bringing radical change and disrupting market research. Using technologies like NLP will enable you to stay afloat and at the vanguard of technological advancements and get rich & holistic consumer insights