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Google Review Analysis: Strategies for Extracting Customer Insights

Tobias Roelen-Blasberg
Tobias Roelen-Blasberg
Co-Founder & Head of Product
Learn how analyzing Google Reviews can unlock actionable customer insights for business success.
Google Review Analysis: Strategies for Extracting Customer Insights

Google Reviews remains one of the most prominent online review platforms, with 81% of internet users checking Google Reviews before making a purchase. Considering this, Google Reviews are truly a pivotal source of feedback for businesses. Understanding the significance of analyzing Google Reviews can be a game-changer for any business striving for success.

Why is analyzing Google reviews important in business?

It's no surprise that an increasing number of businesses are dedicating substantial resources to enhance their visibility on Google. However, note that Google optimization isn't just about collecting Google Reviews, but also extracting actionable insights for your operations.

a. Learning from negative Google Reviews

Here's how you can mitigate the impact and pivot negative reviews as a positive force in your business:

1. Identifying areas for improvement

Negative reviews provide valuable insights into areas of your business that may require attention or enhancement. Carefully analyzing the feedback provided in these reviews can help businesses identify specific aspects of their products, services, or customer experience that need improvement.

2. Addressing customer concerns and issues

Responding to negative reviews demonstrates a commitment to customer satisfaction and allows businesses to directly engage with dissatisfied customers. Through addressing their concerns and issues promptly and professionally, businesses can mitigate the impact of negative feedback and potentially turn unhappy customers into loyal advocates.

3. Preventing negative trends from recurring

Analyzing patterns and trends in negative reviews can help businesses identify recurring issues or pain points. By understanding the root causes of these problems, businesses can implement corrective measures to prevent similar issues from arising in the future, thus improving overall customer satisfaction and retention.

screenshot negative google review hotel
A complex, negative review from Google.

To learn more about effectively handling Google Reviews, read our article Negative Review Response Examples: Don't Let Bad Reviews Ruin Your Business


b. Maximizing positive Google Reviews

Positive Google Reviews won't just enable you to boost your visibility on Google but also attract new customers. Here's how you can make the most out of your 4-star or 5-star Google Reviews:

1. Leveraging positive feedback for marketing

Transform positive reviews into compelling marketing content, such as social media posts, website testimonials, or promotional materials. Showcasing real-life experiences of satisfied customers allows you to effectively demonstrate the value and quality of your products or services to a wider audience, ultimately driving more sales and conversions.

2. Building brand reputation and credibility

Positive Google Reviews serve as valuable endorsements that bolster your brand's reputation and credibility in the eyes of potential customers. When prospective clients see positive feedback from satisfied customers, they are more likely to trust your business and choose your offerings over competitors. Consistently accumulating positive reviews over time reinforces your brand's reliability and excellence, further solidifying your position as a trusted industry leader.

3. Encouraging customer loyalty and retention

Expressing gratitude and engaging with customers who leave positive reviews fosters a sense of appreciation and loyalty among your clientele. By acknowledging their feedback and demonstrating genuine interest in their satisfaction, you strengthen the emotional connection between your brand and its supporters. Satisfied customers who feel valued are more inclined to remain loyal to your business, becoming repeat purchasers and advocates who enthusiastically recommend your products or services to others.

positive google review screenshot
A short but insightful positive review from Google.

Want to learn more about how you can make the most out of your positive online reviews? Read our article: How to Respond to a Positive Review With Examples

How to Analyze Google Reviews – Top Techniques to Use

Analyzing Google Reviews can present challenges, but with the right approach, it's entirely manageable. Here are some effective techniques to employ when delving into your Google Reviews:

a. Numeric Data Analysis

Numeric data analysis involves examining numerical information or data to derive insights and make informed decisions. In the context of analyzing Google Reviews, numeric data analysis typically involves examining metrics such as review ratings, response rates, and the total number of reviews received.

1. Google Reviews’ Star Rating

The Google star rating system has evolved over time to become a crucial component of online visibility and reputation management for businesses. Initially based on a scale of 1 to 5 stars, it now factors in several key elements to determine the overall rating. These factors include the number of reviews, the sentiment expressed in those reviews, and the relevance of the reviews to the business. Additionally, the algorithm considers the authority of the reviewer and the quality of the review itself.

Reviews are mostly collected from Google My Business listings. Google aggregates these reviews and uses artificial intelligence and machine learning algorithms to filter out fake reviews and spam, ensuring the integrity of the rating system.

The Google star rating system plays a pivotal role for businesses, significantly influencing their online visibility. For instance, businesses with ratings above 4 are prominently featured in more searches (in conjunction with the number of reviews) and are included in the local 3-pack search results, enhancing their visibility based on a user's geolocation.

Aman's 4.4-star rating ranks higher than Mandarin Oriental's 4.6-star rating due to its higher number of ratings. Additionally, it also receives a special tag of "Excellent Location" because of the significant number of reviews related to this service feature.

screenshot aman and mandarin oriental google search
Aman and Mandarin Oriental’s rating on a Google Search.

Conversely, listings with a 3-star rating or lower may experience reduced visibility across all Google platforms, making it challenging to compete with higher-rated businesses in search results. Thus, maintaining a high star rating is imperative for businesses to attract potential customers and drive revenue.

The Plaza, regardless of its undeniable popularity, falls short in matching the online ratings of other New York hotel.

the plaza google search screenshot
The Plaza ranks sixth in the "best New York hotel" Google search.

2. Response Rate

Monitoring the response rate to reviews is crucial for understanding engagement levels. A high response rate indicates active interaction with customers, while a low response rate may signify areas for improvement in customer service. This is especially true today, as 53% of consumers expect a reply to their review within a week.

screenshot response rate google listing
A Google listing’s response rate could be accessed by the admin through their Google Business dashboard. Source: Google Help

Moreover, a 2018 study conducted by the Harvard Business Review uncovered that responding to customer reviews leads to improved ratings. The research revealed that hotels experienced a 12% increase in reviews and a corresponding average rating boost of 0.12 stars upon implementing review responses. Although these improvements may appear modest, online review platforms typically round average ratings to the nearest half star. For example, a hotel with a rating of 4.26 stars will be rounded up to 4.5, while one with 4.24 stars will be rounded down to 4.

MARA’s own research found that the average response rate of hotels across all types and regions was only around 40% overall. However, in our 2024 research, hotels are now targeting a 82% response rate towards negative reviews and a 75% response rate towards positive reviews. Certainly, businesses within the hospitality industry have realized the importance of responding to online reviews.

3. Number of Reviews

Tracking the volume of reviews over time offers insights into customer engagement and satisfaction trends. A steady increase in the number of reviews may indicate growing brand awareness and customer loyalty.

screenshot google reviews park view hotel
Quick snapshot of a Google Reviews account with number of reviews.

Receiving 1 to 2 reviews per day is a reasonable target for most businesses, as it can lead to approximately 30 to 60 reviews per month. For Google Business listings, businesses need about 30 to 40 positive reviews to move their rating up by one star. To learn more about this, read our article "How Many Google Reviews Are Necessary for Your Business?"

b. Sentiment Analysis

54% of companies say they use sentiment analysis to examine reviews and social media posts to extract customer insights. Sentiment analysis involves evaluating the emotional tone expressed in Google Reviews, focusing on predefined topics such as breakfast, housekeeping, rooms, and location. For each review, algorithms first identify if these topics are mentioned and then assess whether the sentiment expressed is positive or negative.

Google Reviews have built-in sentiment analysis for Google Business listings, accessible to everyone, including your audience.

screenshot of sentiment analysis on google
Sample of a sentiment analysis ran by Google directly from a Google Business listing.

Business owners can also opt for a third-party tool for sentiment analysis of Google Reviews. However, it's important to note that sentiment analysis algorithms are limited to a set of predefined topics that can be identified. While the accuracy of topic detection and sentiment analysis can be high, many providers still use outdated AI technology, leading to inaccuracies in both topic and sentiment detection. This can result in erroneous business decisions.

sentiment analysis sample screenshot
Sample of a third-party tool running a sentiment analysis. Source: Repustate

For example, consider a hotel analyzing its Google Reviews using sentiment analysis. The algorithm may accurately detect mentions of topics like cleanliness, staff friendliness, and location convenience. However, if the sentiment analysis tool is outdated and fails to accurately assess the sentiment expressed in reviews, the hotel may overlook negative feedback about cleanliness issues or unfriendly staff interactions, leading to missed opportunities for improvement and potential loss of business.

c. Advanced AI Analytics

Traditional sentiment analysis has its limitations, often missing valuable insights due to its reliance on predefined topics. However, with MARA's Advanced AI Analytics, businesses can unlock a new level of understanding from their Google Reviews.

screenshot MARA AI Analytics
MARA’s advanced AI analytics for Google Reviews and other online listings.

Unlike traditional methods, MARA's intelligent algorithms analyze every aspect of reviews, providing insights that are as unique as each business. For example, if guests complain about noise from birds in the lobby, MARA can pinpoint this issue specifically. In contrast, traditional sentiment analysis might overlook such nuanced feedback or lump it into a broad category.

By harnessing the power of MARA, businesses can access tailored and actionable insights without the need for extensive manual review. This advanced approach ensures that no valuable feedback goes unnoticed, empowering businesses to make informed decisions and drive meaningful improvements.

Traditional Sentiment Analysis vs MARA AI Advanced Analytics

Recent surveys indicate that nearly 63% of companies are integrating AI into their operations, with a predominant emphasis on marketing strategies. However, despite the widespread adoption of AI tools, many still rely on conventional sentiment analysis methods.

Traditional sentiment analysis provides a high-level overview of sentiment expressed in reviews, such as identifying that there are 50 negative reviews related to the topic of "breakfast." However, it falls short of providing detailed insights into the specific issues mentioned within those reviews.

In contrast, MARA's Advanced AI Analytics offers a more comprehensive approach. Rather than just highlighting the overall sentiment, it provides a detailed breakdown of specific complaints from guests.

video MARA advanced AI analytics
Going beyond sentiment analysis with MARA AI.

For example, it may identify that out of the 50 negative reviews about breakfast, 12 customers complained about the freshness of scrambled eggs, 8 customers reported issues with a broken coffee machine, and 5 customers expressed frustration about long waiting times to get seated. This level of granularity makes it much easier and faster for businesses to identify actionable insights from guest feedback, enabling them to address specific issues and improve the overall customer experience more effectively.

Most importantly, MARA's Review Analytics helps you understand and analyze the multitude of reviews and lays them out in a straightforward and easy-to-understand manner. With MARA, you can quickly grasp the essence of all your reviews without needing to read each one individually. The analysis is so detailed that you can discover specific issues such as "water in the pool is too cold" or "lack of vegan breakfast options." These insights aid in optimizing the guest experience without requiring you to be a data expert.

Analyze Google Reviews effective with MARA

MARA goes beyond advanced analytics by offering numerous features that facilitate the deployment of effective and efficient online reputation management strategies rooted in customer insights.

Responding to online reviews can be a daunting task, but it doesn't have to be with our AI Review Assistant of MARA. This intuitive tool is designed to ease your Online Reputation Management process, making it more efficient, personalized, and time-saving. It offers the best and most personalized AI for responding to and analyzing your guest reviews.

Group Analytics for multiple listings

Additionally, our group analytics overview can provide a quick evaluation of the performance of each location. Other than key metrics such as response rates, ratings, and the number of reviews, MARA also offers category scores based on advanced AI analytics. In the screenshot below, you can find an analysis of hotels with category scores for areas like Food & Beverage, Front Office, and Housekeeping. This analysis aids in swiftly identifying potential weaknesses, with a preview of detailed topics appearing when you hover over a category.

screenshot MARA group analytics
Group analytics for various review platforms.

Google Business-ready Review Inbox

One of the key features of this tool is the Review Inbox. Your review inbox makes responding to reviews as simple as hitting "Generate reply" and clicking "Send". The Review Inbox connects to multiple review sources, including Google,, and Tripadvisor, giving you a panoramic view of all your reviews. You can even configure review response automation: Why not allow MARA to automatically respond to simple reviews, like 5-star Google reviews with no text, ensuring you never miss a review? Daily notifications about new reviews keep you updated and in control.

screenshot mara review inbox
Streamlined review inbox.

The most personal response AI

MARA's AI isn't just about efficiency; it's about personalization too. The Brand Voice feature allows the AI to adapt to your tone, making sure your responses sound authentically you. Plus, with Smart Snippets, you can "teach" the AI how to respond to recurring praises or complaints. Your AI then incorporates this information into its responses, but always with different words, providing more personalized, relevant replies.

This review response assistant has quickly become a game-changer for over 2000 customers. Its promising capacity to elevate your overall rating, amplify response rates, glean insights from customer feedback, and economize both time and money, is the reason behind its growing popularity.

Final Thought

Google Reviews serves as a crucial feedback mechanism for businesses in today's digital era. Understanding and analyzing these reviews are paramount, given that the majority of consumers rely on them for making purchasing decisions. By effectively managing both negative and positive reviews, businesses can bolster their reputation, attract new customers, and foster loyalty.

Leveraging advanced analytics tools like MARA further enhances this process by providing detailed insights and actionable recommendations to improve the overall customer experience. With the right strategies and tools in place, businesses can capitalize on the power of Google Reviews to achieve sustained success in their industries. So, why hesitate? Give our AI Review Assistant, MARA, a try today. It's free for testing, doesn't require a credit card, and can be fully operational in less than five minutes.

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Frequently Asked Questions:

What is sentiment analysis for Google reviews?

Sentiment analysis for Google reviews involves evaluating the emotional tone expressed in reviews to determine whether the sentiment is positive, negative, or neutral.

How effective are Google reviews?

Google reviews can be highly effective for businesses, as they provide valuable feedback from customers that can influence purchasing decisions and impact reputation.

How do I get data from Google reviews?

You can get data from Google reviews by accessing the Google My Business dashboard or using third-party tools such as MARA AI to extract and analyze review data.

How AI can analyze customer reviews?

AI can analyze customer reviews by using natural language processing algorithms to understand the context, sentiment, and key topics mentioned in the reviews.

Can Google detect AI?

Google can detect AI-generated content through various methods, including pattern recognition algorithms and human review processes, to ensure the authenticity of reviews and prevent spam or fraudulent activity.

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