The Key Advantages Of Mining Customer Reviews
Technology is breaking down the entry barriers for new brands especially in terms of distribution and marketing, aided by factors such as smartphone usage and internet penetration. Subsequently, the evolution of e-commerce has resulted in extreme disruption of the retail industry over the past decade. In a short span, E-commerce went from being the disruptor channel to the only available option for many product categories, due to its increased adoption. In fact, recent research from Grand View Research estimates the current E-commerce global market to be USD 9.09 trillion and expected to grow by a CAGR of 14.7% from 2020 to 2027.
The indisputable fact is that superior customer experience are the critical factors that helped sustain this tremendous growth. With mobile, internet, and other technological advances ensuring ease of purchase, both the e-commerce companies and the sellers have started focusing extensively on improving the customer experience to keep their business afloat and stay ahead of their competitors. And, customer reviews are invaluable in providing meaningful insights. In addition, customer reviews greatly impact purchase decisions, as 97% of the online customers read reviews before buying a product online. The following are the three richest public data sources for mining and analyzing customer reviews for business growth. Together, these sources can
- Identify influential factors to product satisfaction
- Isolate customer experience pain points
- Track consumer response to competition.
Mining Customer Reviews
Before identifying the source to mine the customer reviews, it’s essential to narrow down which customer review channel works best for the objective of the analysis. The raw customer reviews data can be extracted from the following sources individually or as a combination of sources based on the business goals.
Most of the e-commerce platforms, including famous ones such as Amazon, eBay & Flipkart, enable and encourage their customers to rate and post a review on the products that they have purchased. This source is the most reliable customer review data that’s mined online.
In recent years, many customers have started expressing their opinions about products and services on social media. It has also become a channel where brands are actively engaging with their customers, making it an emerging channel in mining customer reviews.
Review websites and Online Forums:
Review sites, niche blogs, and online forums can be excellent sources of reviews of a particular product segment. At times, many customers prefer voicing their concerns on review sites and forums, rather than posting on social media.
The raw textual data are mined from the above sources using distributed crawling techniques and pre-processed by using Stop words Removal and Normalization techniques before using Natural Language Processing (NLP), Machine Learning, and Sentiment Analysis Algorithms to extract meaningful insights.
Advantages Of Customer Review Mining
The insights derived by mining customer reviews assist the business growth and in improving the customer experience with the following aspects.
Identify Influential Factors:
Customer Review insights would help in understanding the factors, features, and attributes influencing the buying decision and that the customers really care. These insights assist the business in better product placement among the target segment, thus leading to better business outcomes.
Optimize Customer Experience
The customer reviews not only help us understand the sentiment of customers towards the product and services but also helps in understanding the underlying product issues and service gaps leading to those sentiments. Improving these shortfalls helps in sales growth and in generating additional positive reviews.
It’s quite usual for the customers to compare the product with its competitor in the same segment while posting reviews. Analysis of these reviews would provide the precise shortfall of the product or service respective to its close competitors. This analysis also helps in understanding the dynamics of the market segment, thus contributing to valuable insights holistically on the ecosystem for better decision making.
SetuServ’s Customer Review Insights and Signal (CRIS) platform is capable of tracking millions of data points from multiple sources, and analyzing the same using AI models with custom taxonomies based on the market segment. This analysis helps businesses in precisely understanding the market landscape and purchase drivers influencing customer decisions.