In the highly competitive e-commerce industry, it is essential for sellers to make use of Amazon review analysis tools to select products, improve consumer experience, and ultimately obtain better market sales and an enhanced brand presence. Through sentiment analysis, voice of customer research, Amazon review analyzers, feedback analysis, product research, audience research, competitor analysis and Amazon ratings & reviews data it is possible to gain deeper insights into customer behavior and preferences. This information can then be used to craft more effective marketing strategies that directly meet customer needs and drive customer satisfaction.
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Sales, a key metric of costs and profits for any business, is the most intuitive and accessible data. With established social media platforms and advertising channels providing detailed insight in regards to website traffic, understanding consumer sentiment--i.e., volume--is one of the more challenging areas to analyze. Volume refers how people express their opinions on our brand's products/services/marketing efforts via various touchpoints; these voices come together as an aggregate that can tell us what consumers need or expect from us – why consumers make purchases with us over others.
Target your customers through customer profile
Voice of customer analysis and audience research are key elements when targeting customers through customer profile. By leveraging Amazon review analysis and other data sources, sellers can gain insights into their customers preferences and behaviors, which can be used to craft targeted solutions and develop a successful product profile. Additionally, this data can also be used to create more effective campaigns that attract the right customers and boost sales.
Ship products your customers love through sentiment analysis
Sentiment analysis can be used to uncover consumer discontent with products, automatically divide NR and PR, and present data about product quality issues, packaging recommendations, marketing flaws, and inadequate service in a digitized format. Through the issues found in VOCs with CTQs, businesses are able to initiate a closed loop from problem to action that enables constant iterations and optimization of product quality. Additionally, customer emotion data can be analyzed to facilitate predictions of upcoming trends before competitors and customize products to meet customers’ needs.
Cons | |
|---|---|
| mirror | 37.96% |
| fog badly | 16.13% |
| issue | 1.12% |
| not good quality | 0.97% |
| loose | 0.80% |
| not stay in it | 0.66% |
| light | 6.89% |
| suction cup | 4.52% |
| suction | 3.60% |
| product | 3.23% |
Pros | |
|---|---|
| mirror | 32.39% |
| good | 2.52% |
| clear | 2.48% |
| good quality | 1.93% |
| easy to install | 1.90% |
| right size | 1.64% |
| light | 7.57% |
| size | 5.89% |
| product | 4.27% |
| suction | 3.06% |
Make the smartest sales decisions through Buyers Motivation
Companies must thoroughly understand the voice of their customers in order to make smart sales decisions. This can be achieved by leveraging buyer motivation data, conducting competitor analysis, and engaging in product research. Companies should also seek out customer feedback, analyze past purchasing data, and stay updated on market trends to devise effective pricing strategies. Additionally, businesses should focus on providing value to customers with competitive prices, relevant discounts, quality products and services, and excellent customer service. By considering buyer motivation and delivering value to customers, businesses will be able to make informed decisions that will lead to profitable long-term success.
| Topic | Mentions |
|---|---|
| others | 126 |
| fogless | 20 |
| anti fog | 8 |
| fogless mirror | 5 |
| don ' t fog up | 3 |
Understand customers need for prioritizing what to build next
Companies should prioritize what to build next by understanding their customers' needs. Amazon review analysis can help businesses better understand customer sentiment, while product research and competitor analysis can give insights into current and upcoming trends in the market. Moreover, customer expectations should be taken into account when developing new products or features. Ultimately, prioritizing what to build next based on an in-depth understanding of customer needs will enable a company to develop successful products that maintain customer satisfaction and loyalty.
| Topic | Mentions | Review Snippets |
|---|---|---|
| big | 56 | big large |
| last long | 28 | last long last longer last awhile last forever last long long |
| large mirror | 22 | mirror big mirror large big mirror large mirror 2x big mirror |
| brighter light | 21 | light brighter lighting brighter brighter light more brightness |
| light | 21 | light lighting |
| large size | 16 | large big size large size size large |
| magnified mirror | 15 | magnification in mirror magnification mirror strong brighter magnification on large mirror magnified mirror magnify mirror on side |
| magnifying mirror | 15 | magnifying mirror large magnification mirror big magnification mirror magnifier mirror magnifying mirror big |
| 2 year ago | 14 | year ago |
| fog less | 14 | fog less fogless fog free fog-less last fog-free longer |
Amazon review analysis is a powerful tool for gaining customer insights that can help inform decision making and product development. Shulex VOC is an AI-powered platform that makes Amazon review analysis easier and more effective, allowing companies to leverage the data available to them. It provides companies with core capabilities such as customer profiles, sentiment analysis, buyers motivation and customer expectations. This empowers businesses to unlock the power of voice of customer, leveraging AI modeling for an in-depth look at customer experience, product research & selection as well as improving quality and reputation. These insights then can be transformed into tangible actions that promote a balanced relationship between customers and brand.
