Harnessing the power of augmented intelligence to understand the drivers of online review ratings
One of the biggest challenges facing marketers in all sectors is how to improve their products’ online review ratings. Numerous studies have shown a strong correlation between high ratings/satisfaction levels and sales. Understanding what drives positive reviews and ratings is therefore paramount.
In this whitepaper, we demonstrate how automated topic modeling/artificial intelligence (AI) and human analysis combined can reveal this. We refer to this powerful combination as “augmented intelligence”.
We share the findings of a client study that used this approach to assess the performance of a competitor’s activity tracker/health watch. The aim of this two-country study conducted in the US using Amazon.com and China using JD.com was to:
- Identify the topics/drivers of both positive and negative consumer appraisals
- Determine the influence of those topics on review ratings
- Establish the differences between Chinese and American consumers’ reviews of both models of fitness watch