Do you know what your customers say about your business or how they feel about their experience with your brand? Customer review analysis can get you insightful feedback to help guide your business decisions, increase customer satisfaction, and increase revenues.
Without customer feedback, you’re guessing what your customers need and how satisfied they are with your offerings, business processes, and brand. Companies who listen to their customers often see customer complaints decrease, customer satisfaction increase, and customer retention skyrocket.
In this article, we’ll discuss the value of doing an ongoing customer review analysis, how to collect relevant feedback, and how to analyze it to pull the actionable insights necessary to inform more effective business and marketing strategies.
- What is a customer review analysis?
- What’s the importance of customer review analysis?
- What sources are used to analyze customer reviews?
- Step-by-Step: How do you analyze customer reviews?
- Helpful tools to collect customer feedback
- How is customer review sentiment analysis done?
- The best tool to analyze customer review feedback
What is a customer review analysis?
A customer review analysis is how you gather, analyze, and interpret customer review feedback to learn more about your customer’s needs and how you can optimize the customer journey. The goal is to generate actionable, data-based insights that you can use to make changes to increase customer loyalty, and boost your revenue.
Your customer review analysis results may provide insights to improve your offerings, optimize customer service and support, or identify processes or areas of your business that aren’t meeting customer needs or could be improved to increase satisfaction.
What’s the importance of customer review analysis?
Collecting customer feedback isn’t helpful unless it can be analyzed and insights can be actioned on. Here are a few benefits and areas of your business you can improve through insights from customer review data:
Product and service development
The key to selling more products or services is solving a customer’s problem or making their lives easier. Analyzing customer reviews and feedback is the best way to know if you’ve accomplished this. You can use customer feedback insights to see if your product or service changes are having the desired effect.
Customer experience enhancement
Customers expect a certain standard of service and experience when using your offerings or interacting with your team (helpdesk, sales, tech support etc.). If you’re not providing the level of quality they expect, you’ll notice a decrease in sales, and they’ll tell you in feedback surveys.
As a bonus, you can often charge more if you’re known for excellent customer experience. Up to 86% of buyers will pay more if you provide a better customer experience than your competitors.
Include your competitors’ reviews in your customer review analysis to see how you rank against them in your customer’s opinion. This is helpful for identifying which areas you need to improve to beat the competition.
You can make better-informed marketing decisions by listening to your customers’ words. Insights from their feedback will help you better position and market your products to address any concerns customers have about your product. You can address or fix these concerns before they buy, ensuring that your product is presented to attract more of the customers.
What sources are used to analyze customer reviews?
The best sources of customer experience information are those received directly from the customer. Trustpilot estimates that 89% of consumers will check your reviews online before making their buying decision. The customer review sources you use for your customer review analysis may vary depending on your business niche and what forms of customer feedback you actively solicit.
There are both direct and indirect sources of customer feedback and reviews:
Direct feedback includes any feedback your company asks for. This may include Customer Satisfaction (CSAT) Surveys, Net Promoter Score (NPS) surveys, Customer Effort Score (CES) surveys, website visitor surveys, and any other customer surveys your business collects. You may also collect their feedback directly through conversations over email or phone.
A benefit of soliciting feedback is that you can ask very targeted questions to get granular feedback on particular aspects you want to analyze. For example, you can ask about your customer’s experience with a newly launched software feature or their satisfaction with their help desk conversation. You can also ask less specific questions, such as asking an NPS survey question like, “How likely are you to recommend [company name] to a friend.”
When collecting direct feedback, you can do it yourself (such as asking customers to rate their experience with a live chat rep after a conversation) or through a third-party feedback collection company you hire to collect feedback from customers on your behalf.
Indirect feedback sources are the reviews you don’t ask for but are posted online on a review site or digital platform. Some examples include:
- Google Business Profile reviews: Customers can leave reviews on your company’s profile page if your company has a published Google Business Profile. These reviews are a score (1 through 5) and are often accompanied by written feedback from the customer.
- Trustpilot reviews: Trustpilot is a 3rd party website where customers can submit reviews on companies for others to read. Trustpilot reviews are not moderated or reviewed, so they’re pretty honest. This is valuable customer data because the feedback includes a star rating, written feedback, and a mention of the date the “experience” occurred. This is helpful when you must focus on data collection related to events in a specific date range. It helps you know if you are reading a current and relevant review or an old and potentially no longer relevant review because the “issue” has since been resolved.
- Social media: People love to complain or praise businesses on social media. You can search publicly available social media posts that mention your company name or a branded name and collect those posts to analyze.
Diversify your customer feedback sources, and avoid relying on just one or two channels. For example, people are likely to post negative reviews and comments on public forums like social media but may be less honest about their struggles when speaking to a representative of your business directly. Include online reviews and customer feedback from various direct and indirect sources to get a more accurate picture.
Step-by-Step: How do you analyze customer reviews?
Doing customer feedback analysis is easy when you follow these four steps:
Step 1: Collect feedback
Look at your current sources of customer-supplied feedback and data. Depending on your goals, you may need to start collecting additional sources of information to get more targeted feedback to answer a specific question. For more accurate results, look for a mix of direct and indirect review sources.
Step 2: Combine and categorize
Once you’ve collected your data, combine all your data sources and look for trends and patterns. This can be done manually or through an AI platform like Idiomatic (more on this below).
When analyzing star ratings, calculate your averages and trends over time, and calculate your average score for numerical customer feedback data (like NPS surveys).
When analyzing written feedback sources, a little more work is often involved if you’re doing it manually. You’ll want to categorize feedback to assign a ranking or understand which aspects of your organization people are providing feedback on and whether that aspect is positive or negative.
Processing and analyzing this large amount of data can be done manually but requires a significant investment in time to review and discover the insights. Human analysis of customer feedback is often unreliable and prone to human error and misinterpretation. A more reliable solution is to use an AI-driven feedback analysis tool like Idiomatic to categorize and analyze your data.
Idiomatic can help you categorize and analyze your data with machine learning models. This makes generating actionable insights faster and more reliable than human analysis, which increases potential for human error and misinterpretation.
Step 3: Dig deeper to uncover the “why” or source of customer feedback
Once you’ve collected and categorized your online reviews and customer feedback, it’s time to do a deep dive analysis to discover the root cause or the “why” behind their feedback. This involves looking at the data and looking for commonalities and trends. From this analysis, you can develop actionable insights to know which areas of your business need to be changed to increase customer satisfaction.
👉 Read more about how Idiomatic can increase product satisfaction by as much as 250% through AI-powered customer feedback analysis.
Step 4: Make changes and repeat
If you don’t act on the insights you get from customer feedback analysis, collecting the feedback in the first place becomes redundant. Make the changes and give the market time to notice before you re-survey your customers to see if your scores and customer sentiment have changed.
Helpful tools to collect customer feedback
In the past, businesses could only collect customer feedback by talking to customers (literally talking) when they came into their business. Then, they would record that feedback and do manual review and analysis to look for trends and commonalities in their customer’s reviews.
Today, there are many online tools to help you collect and analyze customer feedback, including:
- Survey software: You can create digital surveys to distribute via email, social media, and email marketing. Programs like Survey Monkey, Google Forms, and Jotform work well for collecting customer feedback.
- Google Maps profile: Make sure your company has a Google Business Profile listing so that if someone is looking to submit your review there, you already have the account set up for feedback collection and monitoring.
- Chatbots: A chatbot on your website can help you collect customer feedback through the recorded conversation between the customer and the chatbot AI or a live human agent. Data collected from these conversations can be used to understand customer struggles and is customer feedback you can use in your analysis. Examples of chatbot tools include Ada, Tidio, ProProfs Chat, and Freshchat.
- Feedback analysis tool: To analyze your customer feedback quickly and accurately, use a powerful customer feedback analysis tool like Idiomatic to take your customer feedback sources, categorize them, and present actionable insights and trends.
👉 Learn more about the benefits of Idiomatic as your customer feedback analytics software.
How is customer review sentiment analysis done?
A customer sentiment analysis summarizes how people feel about a specific aspect you’re polling. Most sentiment analysis will include 3 categories (positive, negative, and neutral) or may consist of more specific degrees of positive and negative scores for more granular analysis.
For qualitative customer feedback, the best way to begin categorizing this information is by issue or feature. For example, separate feedback mentions relating to product pricing from problems relating to app user experience.
Once you understand the sentiment behind the specific aspect, you can use customer feedback analysis tools to dig deeper into the feedback to uncover the particular reason for the sentiment score. Idiomatic is one customer feedback analytics software that helps you categorize your data based on unique business issues and process a large amount of this feedback data at scale.
👉 Learn more about conducting an effective sentiment analysis with customer feedback data.
The best tool to analyze customer review feedback
Using tools to collect and analyze customer reviews will help you get actionable insights faster and with less human error that often comes with manual data collection and analysis. Idiomatic will process customer feedback from multiple sources (both direct and indirect), so you can learn the root cause behind your scores. It helps you better understand why customers feel the way they do about your offerings and brand.
Idiomatic is the industry’s most detailed and accurate machine learning model, categorizing customer feedback based on your unique business issues and goals. It provides data-driven insights into the “why” behind customer sentiment and feedback. You can use this information to execute the right business decisions faster and see positive business growth.
As a customer sentiment analysis tool, Idiomatic finds trends you may not have seen before. This alerts you to potential problems before they cause significant business disruption.
Ready to learn more about how Idiomatic can make customer feedback analysis easier, more accurate, and more actionable?