Business review websites, such as Trustpilot and Amazon, can be the boon or the bane of your organisation. The make or break. The best and worst. You get the picture…
Customers will take to review sites to share their experiences or thoughts on your products/services. This can be advantageous in many ways and is a free marketing tool that does, frankly, a lot of work for you. A five-star review can encourage x amount of purchases when potential buyers spot somebody else singing your praises.
However, an unhappy customer leaving a scathing review could also discourage x amount of purchases. Once a bad review is submitted, it acts like an infection, leaving people steering clear of your offerings.
Having said that, any company worth its salt knows that customer feedback is of paramount importance. In particular, you can use customer reviews to your advantage to listen to what needs improving and what is working well for you. Yes, it’s invaluable in itself, but what if you could really bolster this to your advantage?
Sentiment analytics takes centre stage
Today, organisations have sentiment analytics at their disposal to help them make the most of customer reviews. Sentiment analytics enables ‘opinion mining’, which in turn enables you to dig deeper into their thoughts on your business. This is not restricted to feedback on review sites; it also includes other mediums such as social media.
Sentiment analytics uses machine learning and natural language processing to scratch beneath the surface of given text. It can extract subjective information from it and present the reviewer’s thoughts and judgement in a way that’s more meaningful and useful to you. In particular, natural language planning is the main tool in the kit that extracts opinions and differentiates between the words.
Rather than having an employee sift through Twitter/Amazon etc themselves, you can use sentiment analytics to analyse a huge amount of text from a number of content sources. Solutions today often offer real time insights too, meaning you can get a general feel of campaign responses with immediate effect. In the long term, it enables you to track your business performance by building reports over time.
It’s funny to think that a machine learning-enabled tool can analyse text and harvest human opinions better than, well, a human can. However, much of this is due to the fact that sentiment analytics can do the dot-to-dot for you much quicker (and perhaps more accurately) than a human can. For example, you/your team may acknowledge a comment regarding the ‘prolonged delivery time’. Sentiment analytics can dig deeper to see if this is a trend, encouraging you to work on it if so.
There are many use cases for sentiment analytics, from driving marketing to measuring performance in politics. In the enterprise arena, it can provide a strong competitive edge if you can better listen to your reviews. Happy customers, happy company.
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