Analysing reviews to get the most valuable insights
For businesses that want to excel, understanding customers is no longer a luxury; it’s a necessity. And while collecting reviews is step one, understanding how to analyse your customer and product reviews is key to gaining valuable insights.
While collecting data on the latest consumer trends can be a valuable tool, knowing which data to analyse from your own customer set can have the biggest impact on evolving your business.
We’ve compiled this guide to help you manually analyse your reviews or know which features and platforms are the most useful.
If you're wondering how evolved your customer insight strategy is, our business questionnaire will help you understand. The guidance we'll share after you complete the questions will help you identify how to take your strategy up a notch.
How to analyse customer reviews manually
The key to analysing your reviews manually is to know which data sets to pay attention to and which ones to ignore.
We know that businesses that base decisions on data are 19 times more likely to be profitable; but it’s not always easy to tell which data to pay attention to.
There are two types of data that businesses should be listening to: operational and experience.
Operational data is generated by your organisational processes, including sales, inventory, and customer interactions. This data allows you to track metrics like win rates, product profitability, and the sources of your sales.
Experience data captures the human element - that is your customers' opinions, beliefs, and motivations. It helps bridge the gap between your perceptions and the actual situation.
By taking a holistic approach to analysing both types of customer data, you can gain a comprehensive understanding of your business and deliver a seamless customer experience from start to finish.
Use sentiment analysis to analyse customer reviews
Smart businesses don’t just want to know what their customers are saying, they want to know what they feel about it. Verbatim comments can be useful to read on one level, giving the team insight into customer analysis, but being able to analyse the sentiment behind the comments can prove to be more valuable.
Save time with AI sentiment analysis
Feefo’s suite of analytics features includes customer sentiment analysis that uses AI to recognise patterns and trends in customer feedback. These are patterns that might otherwise be impossible for the human eye to spot, especially if there’s a large data set. It’s a great tool when analysing product reviews because it can save hours and pinpoint exactly where you may need to tweak a process or an item to improve customer satisfaction.
Highlight common themes
As well as emotive words that give you a certain sentiment from customer feedback, it’s valuable to look for common themes in review comments. For example, a company may be getting lots of negative reviews that all mention the same issue, giving you valuable insights you can turn into positive changes.
This post looks at several case studies that show how Feefo helps companies take action based on negative reviews.
Feefo worked with a holiday park company who were worried when they received a series of negative reviews about their villas. When they looked deeper, they identified that the comments had a similar theme: the shadiness of a specific villa. This told the company that some of their accommodation was in a shady spot that customers didn’t like. They could respond accordingly and fix the issue.
Looking for common themes in your customers and product reviews, whether manually or using a verified reviews platform, will give you insights that can be actioned.
How to turn customer feedback and reviews into actionable business insights
So, how can businesses that want to grow their profits find actionable insights from customer feedback?
Step one is looking for patterns in sentiment and themes.
Step two is to analyse what these common themes are saying and investigate the origins of their comments. Are many customers dissatisfied with the level of customer service around the same aspect of their buyer journey? Is there one particular range of products that gets the most negative reviews? Do people often mention delivery times?
It’s important not to look at customer feedback in isolation and instead understand which area of your service or products each review is connected to. Of course, this is easy with a verified reviews collection platform that will tag reviews automatically, rather than manually trying to categorise your comments.
Use AI technology to make analysing reviews quicker
While AI might still be a contentious issue to some, we all know it’s making many aspects of business quicker and easier than ever before. Particularly when it comes to analysing reviews.
Identifying data trends, whether manually or automatically, is a vital part of the process of analysing and making use of customer feedback data. Feefo’s Analytics hub gathers data from all channels using our advanced reporting tools. Our tools analyse customer feedback by demographic and location and help to uncover valuable insights that drive business growth and creativity. AI is a much faster way of analysing reviews than doing it yourself.
Our customer sentiment analysis features
Feefo’s Essential Analytics includes customer sentiment analysis to provide an overview of what customers think and feel about your products and services, without your team spending hours analysing the data. It can also analyse thousands of reviews on your behalf and summarises a round-up of themes and sentiments, saving you valuable time to work on the things you do well.
The benefits of using automated sentiment analysis
The benefit of automated sentiment analysis is that it’s faster than the human brain. Not only that, but the human brain often fills in the gaps with what we expect to see, not with what is there. So, it’s valuable for all staff to understand their reviews and what customers are saying. Using a tool such as automated sentiment analysis will save more resource, time and money than completing a manual analysis.
What's the best review analysis solution for your business?
Before choosing the best review analysis solution for your business, think about your review management platform. The best outcomes always come from the best-laid plans. A feedback collection platform that lets you tag and categorise the reviews and comments you’re getting before you even get to the analysis stage is highly beneficial.
A manual feedback collection process is great because it’s free, which is ideal if you’re running a small, independent business. But free doesn’t always mean better. A free tool often means it costs you time rather than money.
You might consider an open reviews platform, such as Trustpilot, that allows you to collect reviews (even potentially without you knowing as an account is automatically created on your business if a review is left), but open platforms will sacrifice quality of customer insights. A typical issue businesses find with open review platforms, like Trustpilot, is that they can leave businesses open to fake or false reviews as there is no purchase verification required to leave a review. This can not only cause inaccuracies in data analysis but also risk reputational damage.
So, what’s the solution? A verified-only reviews platform – one that authenticates that people are not only human but also genuine customers through purchaser verification – will give you richer insights that can be turned into true, business-enhancing actions. It can also help businesses stretched for resources as it’s already set up to collect reviews into categories and uses supporting technology and tools to make analysis quicker than any other method.
From just £99 businesses of any size can set up a verified reviews collection process that will give them the gold standard of actionable insights and a respected, third-party feedback platform that is great for building customer loyalty.
