Are you looking for a way to understand your customers better? Do you want to know what they think about your products and services? If so, then Review & Feedback Analysis is the perfect way to do so. In this blog post, we’ll look at what Review & Feedback Analysis is, its benefits of it, the types of Review & Feedback Analysis, and how to interpret feedback data. So, let’s get started!
What is Review & Feedback Analysis?
Review & Feedback Analysis is a process of gathering and analyzing customer feedback to gain insights into customer needs, preferences, and behavior. It is used to determine what customers think about a company’s products or services. It can help companies understand customer satisfaction, identify customer pain points, and improve customer experience. Review & Feedback Analysis can also help companies understand customer preferences, improve customer engagement, and identify potential opportunities for growth
Benefits of Review & Feedback Analysis
There are many benefits of Review & Feedback Analysis. For one, it can help companies identify customer pain points, which can help them improve their products and services. It can also help companies understand customer behavior, preferences, and satisfaction levels. This can lead to improved customer experience, better customer engagement, and higher customer retention. Additionally, Review & Feedback Analysis can help companies identify potential opportunities for growth.
- Optimize product quality
From review & feedback analysis, we can easily extract the reasons why consumers are dissatisfied with our product, such as problems, complaints, and even reason of returns and exchanges. These are collectively referred to as product quality standards. The quality standards obtained from review & feedback analysis are communicated to the product department and quality department as the task of product iteration optimization.This closed-loop process is called from review & feedback analysis to quality problem solving, that is, VOC-CTQ process.
- Improve brand experience
In review & feedback analysis, we should not only look at negative product reviews, but also at consumers' positive review on our brands, markets, marketing and services. For example, customers review on our promotional campaign and the discount rule, and their public praise of our customer service. The information obtained from review & feedback analysis, on the one hand, can help us continuously improve our operation ability; on the other hand, it can enlarge the positive consumer word-of-mouth and convert it into brand.
- Expand competitive advantage
In terms of product competitiveness or selling point (MUS), we should get more more advantages or exclusive functions. Through review & feedback analysis, we can clearly interpret consumers' purchase motivation and experience praise. For example, "the power storage capacity of this product is the best among all the products I have used, and the quality is very good without heating".From this review, we can see that customer care about the power storage capacity and safety of products. Some information obtained from review & feedback analysis is a point that needs us to enlarge infinitely in the creation of product selling points.
- Improve sales conversion
review & feedback analysis has two levels of effect on sales transformation. One is mentioned above, obtaining the competitive advantage of products through review & feedback analysis, and then enlarging infinitely. The second is to find keywords that conform to consumer context and cognition. For scientific and technological products, we often describe our products in professional terms. However, from the review analysis of Amazon, we can see that the consumers are not familiar with professional term. For example, when we mention turbo, but consumers always said Power. We use words that are easy to search, read, and understand to describe products, so as to improve the sales conversion rate.
- Mining Opportunities for new products
Mining explosive products is a deep-seated role in review & feedback analysis. We usually judge opportunities by sales, that is, the market supply. What review & feedback analysis can tell us is the consumer demand scenario and usage scenario, that is, the market demand situation. Only when the market volume and growth rate are large enough and meet the needs of consumers at the same time,Only when they can pay for it can they truly grasp the supply-demand relationship of the market and create hot money with high sales.
Types of Review & Feedback Analysis
There are several types of Review & Feedback Analysis, each with its own purpose. Survey Review & Feedback Analysis is used to gather customer feedback on products or services. Market Review & Feedback Analysis is used to identify customer preferences and trends in the market. Customer Review & Feedback Analysis is used to measure customer satisfaction and identify customer pain points. Social media Review & Feedback Analysis is used to monitor customer sentiment and engagement.
Review & Feedback Analysis Frameworks
In order to effectively analyze customer feedback, companies need to use Review & Feedback Analysis frameworks. These frameworks help to organize customer feedback and make it easier to analyze. Common Review & Feedback Analysis frameworks include the Kano Model, SERVQUAL, and the Net Promoter Score (NPS). Each of these frameworks has its own set of criteria for measuring customer satisfaction and identifying customer pain points.
Analyzing Customer Data
Once a Review & Feedback Analysis framework has been chosen, the next step is to analyze customer data. This includes gathering and organizing customer data, such as feedback from surveys, social media posts, and customer reviews. This data can then be analyzed using statistical methods such as regression analysis, clustering, and factor analysis. This analysis can help companies understand customer preferences and behavior, as well as identify customer pain points.
- Use basic tags to determine consumption scenarios
Cross-Industry basic tags, usually demographic tags and e-commerce quality tags. In Amazon review & feedback analysis, we can use these tags to clarify user portraits and basic word-of-mouth of categories.
For example, in Amazon review & feedback analysis, we can see who buys for whom, for apartments or villas, commercial or public, seasonal or holiday. The order accumulation of these information can help us to constantly identify the target user groups. For example, "I bought the latest smart sweeper as a Christmas present for my wife,This will help her clean up our public areas on the first and second floors ". Wife, Christmas gift, two floors, public area is the user portrait we obtained through Amazon review & feedback analysis.
E-Commerce quality tags, or product-level specific, can be divided into design, function, packaging, quality, promotion, technology, service, market, and brand. These nine first-level tags also constitute the nine basic factors for categories or brands in Amazon review & feedback analysis. For each factor, score 1-5 from the dimension of consumer review,It also ranks all products for the first time from the perspective of customers.
- Mining explosive demand through lean specific tags
If you need to find new products and create best seller product, basic tags are far from enough. We need to create exclusive user experience tags for a category or even a single product.
User experience tag library is a tag library designed for products from the user's perspective. It contains the user's basic data, use process, purchase process, experience and scenario.
Different from user behavior tag library and product attribute tag library, user experience tag library is a tag system that combines user attributes, user actions, product attributes and consumer emotions.
Created by whom
In general, the product manager of the company is responsible for the design of Amazon review & feedback analysis of user experience tag library for his own category.
The product manager designs the user experience tag framework and is responsible for the tag design of product attributes in the framework. Then, five organizations including quality, market, brand, sales/operation and service are invited to expand tags. Finally, the Amazon review & feedback analysis user experience tag library is formed.
The product manager will formulate tag standards, quality requirements, safety requirements, maintenance mechanisms, and manage tag library iterations.
How to Create
Step 1: Determine the basic direction:
First identify objects, identify people (consumers), things (products), and relationships (use, purchase, experience, and emotion). For example: My wife thinks the appearance of this product is very beautiful. In this sentence, we can get people (wife, woman), things (appearance, ID design), relationships (forward, design)
Step 2: establish the design idea of Amazon review & feedback analysis:
The design idea of tags, or design logic, refers to the five ways of core words, divergence, drill-down, dynamic, and abstraction to extend the first-level and second-level tags.
Core words: if the core words are brand preferences, then subordinate tags are established around brand phrases, such as brand country, brand grade and brand grade.
Relevant: for example, around physiological parameters, we distribute all relevant tags, such as height, weight, blood type and hair color.
Drill down: The parent-child structure. Drill down all attribute tags. For example, if Bluetooth is the parent, drill down to the Bluetooth version, link technology, etc.
Dynamic: tags that record the development process and behavior process, such as browsing, clicking, sliding, and jumping out.
Abstract: Unified abstract processing from the same things, such as music, movies, food, tourism
Step 3: develop Amazon review & feedback analysis tag classification (level 1 and Level 2 tags)
Around the data source, we can design a primary and secondary tag tree from seven dimensions: User attributes, platform attributes, product attributes, environment attributes, usage attributes, experience attributes, and emotion attributes.
Step 4: compile the underlying tags for Amazon review & feedback analysis
When the primary and secondary levels are clear, we begin to continuously add, delete, modify, and query the underlying tags. Among them, the update frequency of product attribute tags is the highest, and we become the neat update, which requires the product manager to constantly gain insight into new products and sub-categories in the market and optimize the update.
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Analyzing Customer Feedback
Once customer data has been analyzed, the next step is to analyze customer feedback. This involves looking for patterns in customer feedback and identifying key themes. It also involves using sentiment analysis to determine the sentiment of customer feedback. This can help companies identify customer needs and preferences, as well as customer pain points.
After marking, you need to use tools to Mark and analyze the content. From the content after marking, we use tools to conduct a comprehensive Amazon review & feedback analysis.
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Users
Based on the product usage scenario data and the usage scenario tag heat map, the distribution of product usage scenarios under different brands of different groups is analyzed.
View the emotional distribution of users and identify the satisfaction degree of product functions by analyzing the scenario data of product manipulation.
Look at the pain points, cool points and demand points of consumers through the data of user preference expectation.
Determine product quality requirements and standards through tolerance for user functional quality problems
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Look at the product: mainly from the overall product quality, scene experience, function module to identify the problem
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Look at selling points: a comparative analysis between product selling points and user sentiment
Look at competing products: compare all the above contents with competitors' advantages and disadvantages
Feedback Reporting
Once customer feedback has been analyzed, the next step is to create feedback reports. These reports can be used to communicate customer feedback to stakeholders and decision-makers. They can also be used to track customer trends and identify customer needs. Feedback reports can also be used to identify areas of improvement, as well as opportunities for growth.
Customer Feedback Analytics Solutions & Applications
In order to effectively analyze customer feedback, companies need to use customer feedback analytics solutions and applications. These solutions and applications help to automate the process of analyzing customer feedback, making it easier and faster. Popular customer feedback analytics solutions and applications include ShulexVOC, ChatGPT, and Ship. These solutions and applications can help companies quickly identify customer pain points, understand customer preferences, and improve customer experience.
Market Review & Feedback Analysis
Market Review & Feedback Analysis is used to identify customer trends and preferences in the market. This includes analyzing customer data, such as customer reviews, social media posts, and survey responses. It also involves analyzing customer feedback to identify customer needs, preferences, and behavior. This can help companies understand customer sentiment and identify potential opportunities for growth.
Customer Feedback Reports
Customer feedback reports are used to communicate customer feedback to decision-makers. They can also be used to track customer trends and identify customer pain points. These reports can be generated using customer feedback analytics solutions and applications. The reports can be used to identify areas of improvement, as well as opportunities for growth.
How to Interpret Feedback Data
Once customer feedback has been analyzed, the next step is to interpret the data. This involves looking for patterns in customer feedback and identifying key themes. It also involves using sentiment analysis to determine the sentiment of customer feedback. This can help companies identify customer needs and preferences, as well as customer pain points.
Conclusion
As you can see, Review & Feedback Analysis is a powerful tool for understanding customer needs, preferences, and behavior. It can be used to identify customer pain points, improve customer experience, and identify potential opportunities for growth. By using customer feedback analytics solutions and applications, companies can quickly and easily analyze customer feedback and generate feedback reports. With the right approach, companies can unlock the power of Review & Feedback Analysis and discover what their customers are really thinking.
So, if you’re looking to understand your customers better, don’t hesitate to use ShulexVOC to analyze feedback using ChatGPT, Ship products your customers love, 5X faster using ChatGPT Discover a wealth of insights without lifting a finger Understand customer’s needs by prioritizing what to build next. With the right Review & Feedback Analysis tools and strategies, you can gain valuable insights into your customers and unlock the power of Review & Feedback Analysis.
