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Improve Your Business With Google Review Analyzer Insights

A Google reviews analyzer can significantly improve your marketing effectiveness and help amplify your brand reputation. Research shows that the sales conversion ratio of people who have read positive reviews is much higher than those who don’t read reviews at all. This means that not only does a business have a chance to leverage insights from Google reviews analysis for ways to improve its products and offerings but also improve its search engine rankings to reach more customers.

Read on to know how Google reviews can help your business grow and what kind of insights you can expect from a Google reviews analyzer.

Why Are Google Reviews So Important?

Google reviews are a powerful marketing tactic to increase your business and brand visibility on Google search results, get customer and product insights, as well as for competitor analysis. Let’s understand these better.

1. Product feature analysis

A Google reviews analyzer can get you detailed, aspect-based insights about product features that work well in the market and those that need improvement. Once trained, machine learning tools can extract this information seamlessly with Google review analysis and provide insights based on specific timelines, product features, customer demographics, languages, and more.

2. Improves brand trust

People always look up customer reviews before they buy a product or service. Call it being cynical of advertising campaigns or just being overcautious, customers tend to believe peers more than the company itself. Ensuring that you encourage customers to leave Google reviews, and more importantly, acknowledge them by responding to queries and negative comments graciously can go a long way in building your brand credibility.

3. Boosts Google search visibility

Google reviews can not only help in building brand experience and give you product insights but also boost your search engine optimization (SEO). Google reviews affect local searches to a great extent due to the fact that Google algorithms can identify review signals (ratings that people provide for products or services). Therefore, the more and varied your reviews are, the more it affects your search visibility and the probability of your appearance on the Google Map Pack that shows a bunch of red dots signifying local businesses.

Google listing sentiment analyzer

4. Increases sales conversion rates

Brand trust plays a significant role in better sales conversions. As people go through your reviews, they gather more information not only about your product but also about your after-sales service and customer care efficiency. Further, when they see your interaction with customers in the reviews, they get to see your genuine commitment to your customers. All these factors help in having better sales conversions.

5. Competitor analysis

You can easily find competitor intelligence through Google review analysis with the help of a machine learning tool for customer insights. Repustate’s Google reviews analyzer is driven by AI and allows you to use keywords or hashtags, and even alter entities in the customer experience dashboard, all without coding, so you get the insights that you need as your business grows and demands change.

6. Customer intelligence

You can leverage the intelligence you have gathered from your Google reviews and find out what motivates your customers into buying your products and services. Through an AI-enabled Google reviews analyzer, you can discover how you can improve your overall customer experience, enhance customer engagement, better customer service, and much more.

How Do You Analyze Reviews On Google?

Google reviews can be processed with high precision automatically with the help of AI-driven algorithms in a Google reviews analyzer. The machine learning platform for customer experience (CX) analytics applies natural language processing (NLP), semantic clustering, text analytics, and ultimately, sentiment analysis, along with several other ML tasks to give you in-depth business insights. A look at the main steps involved.

Step 1: Data collection

You can enter the URL of the Google reviews. Or, you can upload the data via an excel file.

Step 2: Data preparation

The model now prepares the text from your reviews for voice of the customer analysis of your Google reviews. This includes emojis. The model uses different capabilities for different data sources. For example, it would use YouTube comments analysis for YouTube content and Instagram social listening if you wanted to analyze comments and videos on Instagram.

Step 3: Analyzing the data

The Google reviews analyzer now processes this cleaned and prepped data. It is important to note that the model is trained with training data based on the industry you are in. For example, the model will be trained separately for hospitality, banking, healthcare, automotive, government services, etc. This helps get accurate data as the ML model is able to correctly categorize the aspects and topics in the data.

There are other important aspects in this stage, which include:

  • Multilingual data analysis - Algorithms analyze the reviews in the language they are written using the ML model specific to the language. This improves the accuracy of the insights.
  • Topic classification - The topic classifier tags themes in the data such as “customer service”, “parking”, “location”, etc.
  • Custom tagging - Apart from automatic topic classification, custom tags are also created for aspects such as “food” or “drink”, so that they can be analyzed for the sentiment.
  • Sentiment analysis - The Google reviews analyzer now commences sentiment analysis, which gives sentiment scores for all aspects and topics in the data, as well as the overall brand sentiment score.

Step 4: Visualizing insights

All the insights appear in the text analysis dashboard. The data is shown as graphs and charts, and can be shared amongst teams.

Benefits of Google Review Sentiment Visualization

  1. Sentiment Trend - You can view the overall sentiment trend of your business as can be seen in the screenshot below of the Google reviews analysis of the Disney World Resort in Florida.

Google review sentiment trend

  1. Overall Sentiment and Distribution Trend - A Google reviews analyzer can tell you the overall sentiment that customers have about your business. As the example below shows, you can see positive, negative, and neutral sentiment clearly in percentages and color codes.

Google reviews sentiment trend

  1. Multilingual Data Analysis - The CX analytics platform can give you sentiment details regardless of the different languages it finds in the data. It gives you a breakdown of the total number of languages as well as the sentiment scores in each. This gives you an idea of your business sentiment based on demographics.

Multilingual Google review analysis

  1. Time-based Sentiment Scores - You can leverage Google reviews analysis by monitoring customer sentiment based on timelines of events, new product releases, seasons, and any other factor.

Google Review Analyzer Sentiment Change Over Time

  1. Common Words & Phrases - Repustate’s Google reviews analyzer for customer experience analysis recognizes and extracts all keywords and phrases that have occurred in your Google reviews. This gives you a clear indication of what’s on your customers’ minds.

Common Entities & Phrases in Google Review Analyzer

  1. Aspects Trends - You can monitor and measure aspects trends in your Google reviews analysis data. As the example of the Disney Resort in Florida shows, there are many aspects that are important to customers including price, cleanliness, service, quality, and others.

Google Review Analyzer with Sentiment Trends

  1. Aspect by Sentiment - Google review analysis can give you a clear measure of aspects by sentiment so you can gather product, service, and customer intelligence on different aspects of your business.

Google Review Analyzer with Sentiment by Aspect

  1. Aspect co-occurrence - Aspect co-occurrence shows you what aspects are mentioned often together, giving an indication of their relationship and importance to customers.

Aspect Co-occurance with Google Review Analyzer

  1. Emotion Aspect co-occurrence - The Google reviews analyzer extracts the sentiment related to each aspect so that you know exactly what aspect represents what kind of sentiment and to what extent, in customers.

Emotion-aspect co-occurance with Google Review Analyzer

  1. Word Cloud - Apart from charts, you can also get a bird’s eye view of what customers mention the most in your reviews through a word cloud.

Word cloud from Google Review Analyzer


Repustate’s feature-rich Google reviews analyzer allows you to extract hidden customer, product, and business insights in Google reviews.

Repustate’s proven AI capability for sentiment analysis is available in 23 languages, both for text, and video content analysis. This means you have high-precision insights at speed and scale from any data source including review websites, Reddit, blogs, news articles, surveys, emails, or any other data, as well as insights from video-centric social channels, for example, TikTok insights.

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