As a rapid-developing and dramatically changing industry, e-commerce has gradually become the main battlefield of manufacturers and brands. According to the Commerce Department, e-commerce is going to grow at a rate of over 15% per year (Roepke, 2019). With such rapid growth, it also brings many complicated problems as products may be distributed on different platforms such as Amazon and Walmart. In this case, Reviewbox arose as a solution in 2016 and seized the opportunity of monitoring and managing massive information including reviews, prices, contents and ads, etc. on multiple platforms.
Initially, as an online Software as a Service (SaaS), Reviewbox focused on automatic email notifications & detailed historical reports especially for bad reviews. Accordingly, the team was formed by 12 members specializing in Product Management and Operations. However, as analytics becomes extremely popular, the company has been trying to apply more analytical techniques to help their customers achieve better performance.
Reviewbox provides fundamental analytics report that analyzes historical data to track trends and identify issues that may harm the performance of products. It also offers automated reports and personalized dashboards so that customers can utilize analytics based on their own needs.
Apart from the basic analytics service, Reviewbox has launched the ‘Brand Report Card’, which can provide a precise and quantified measurement of the ‘health’ of product listings. Scores are calculated based on service: Reviewbox for Reviewbox for ratings and review management, Pricebox for price and inventory, Copybox for content management, and Searchbox for keyword search rank data (Debi, 2020). While this kind of new service will help retain the existing customers and attract new customers, there remains some problems, for example, how is the weightage assigned? Here comes our practicum project. In the very first sub-project, we aimed to explore the relationship between reviews/content/price and search/sales. With such quantified relationship, more precise and appropriate weightages will be assigned rather than simply calculating the average.
Another potential application of analytics is our team’s main focus right now: fraudulent review detection. A few months before, one of Reviewbox’s customers reached out and claimed that their products on Amazon are facing a considerable number of fraudulent reviews and we were tasked to analyze it and try to develop a model for detection. Specifically, we looked into all the possible features that could make a review fraudulent such as phrase repetition, verified or not, incentivized reviews, as well as some attributes related to reviewer profiles such as one-hit reviewer. Ideally, the final model should not only evaluate the authenticity of reviews of one specific product, but also identify which are the suspicious fake reviews. By integrating this into Reviewbox’s platform, customers can get alert notification if their products are getting fraudulent reviews. In this case, they can immediately report to Amazon to avoid loss of revenue and brand infringement.
Online review has been considered as an important source of product assessment and there are way more analytics that can be done through mining the review data. For example, a negative review with one-star rating can either be a fraudulent review, or it might be an authentic one. By analyzing these true negative reviews, identifying key aspects that consumers are not satisfied with, Reviewbox can provide suggestions towards product improvement and quality control of their customers. Similarly, positive keywords that are frequently mentioned in reviews can also be used in ad campaigns and product description page. In this way, the search rank as well as the ‘share of voice’ of products can be elevated.
As an innovation-focused start-up, it is vitally crucial for Reviewbox to make full use of analytics and continuously provide new services and products that can help their customers perform better on various e-commerce platforms. As the research team of them, we would also try our best to apply our analytical skills.
Resources:
- Roepke, A. (2019, May 21). Understanding Your Brand’s Share of Voice. Retrieved from https://getreviewbox.com/understanding-your-brands-share-of-voice/.
- Debi, C. (2020, January 15). Brand Report Card. Retrieved from https://getreviewbox.com/brand-report-card/.
