Review analysis is the act of going through customer and product reviews from a number of different channels and uncovering insights. These insights can then be used to improve products and services, create new ones, or enhance the overall customer experience.
Review analysis can also help catch any bugs or customer complaints that could escalate and be damaging for your brand.
With a small number of reviews, analysis can be done using tools like Microsoft Excel.
However, when analyzing a large quantity of reviews you’ll need to perform your review analysis with AI-powered text analysis tools.
Detecting product bugs. Reviews are an essential way for your customers to tell you about any issues with your product. It’s important that you process and take these reviews on board. This means you can give your customers a product that is functioning as it should. By acting on their reviews quickly you can avoid any customer frustration and make sure your customers enjoy using your products.
Product development. Rather than creating products randomly, reviews help you steer the creation of new products in a way that makes sense for your customer. When you create products according to their needs, they’re more likely to purchase, repurchase, and recommend you to their friends.
Improve customer experience. Reviews tell you what your customers like and dislike about their overall experience with your company. They can also provide insights on a more granular level. These insights let you isolate problem areas within your customer experience journey and quickly put measures in place to improve it.
Competitive analysis. Comparing the reviews your customer gives you, and the reviews that your competitors get can help you assess how you rank in the market. It can also help you to improve by showing you what your competitors are doing well and what you need to work on.
Making informed business decisions. To gain more business you have to put your customers at the center of every business decision you make. A great way to do this is by using the insights from reviews to inform these decisions.
Prioritize product roadmap. What you think is the most pressing new product or feature might not actually be what your customers think is the most urgent. Reviews help you to make a list of priorities, or a product roadmap, according to real demand. When you prioritize according to feedback and reviews, you are more likely to sell more products.
Sentiment analysis is the process of detecting positive or negative sentiment in text.
Since customers express their thoughts and feelings more openly than ever before, sentiment analysis is becoming an essential tool to monitor and understand that sentiment.
Keyword or Aspect Analysis
A keyword or aspect analysis identifies specific ‘things’ in the text. For example, if a customer mentions the word ‘discount’ it will label or categorize the feedback as being about discounts.
A keyword analysis is very dependent on the language used by the customer, making it prone to error and inaccuracies.
Topic analysis, or classification, is a form of AI-powered analytics that reads and analyses like a human does, but considerably faster.
A topic analysis doesn’t simply see a keyword, and label the piece of feedback. It takes into account the context of that word and the meaning of the piece of text it sits within. Correct categorisation is not dependent on any specific words used, making the results much more accurate.
For example, a topic analysis tool can identify that a customer is complaining about ‘discount code not working’ even when they say something like ‘the offer didn’t apply at checkout’.