Customer voice is one of the biggest perks digitization has afforded businesses over traditional media. That said, apart from managing online reputation and weeding out fake reviews, marketplaces need a deeper level of customer cognizance to stay above the curve. Why is a particular brand in a category performing better than others? What features are most-talked-about in a sub-category, and are we infusing it rightly in our product content? Is there a reigning customer sentiment towards a particular product line that we are missing and could use to our marketing advantage?
Answers to these and many more related factors can be gleaned through a robust and customizable review analytics. By processing user-generated reviews through certain predefined algorithms, combined with text mining, marketplaces can derive actionable content insights at scale. Let’s see how:
Capturing sentiment towards a product-specific feature
Even as online shopping continues to grow amid the pandemic, shoppers have become increasingly discerning about their purchases. They are looking beyond price and weighing the pros and cons in terms of usability, trustworthiness, and long-term value of each product. This trend has been driving marketplaces to conduct not just a quantitative product review analysis based on sales shares and customer ratings, but also dig deeper into the qualitative side.
Measuring sentiment that’s feature-driven is quickly gaining importance. Why? Because it uncovers the good, the bad, and the ugly of each product. For instance, if a review for a trouser reads, “The fit is great but the material is not breathable,” the analytical results will identify the sentiment for the fit being positive while for the material being negative.
It doesn’t end here. Netscribes’ review analytics tool comes built-in with a few cognitive layers as well – grammar being one of them. For instance, if “cheap” is mentioned in relation to price, it captures that as a positive sentiment, but if it’s mentioned in the context of the material used for manufacturing, it concludes it as negative. Being captured as individual feature-based sentiments, these inputs help marketplaces gain an overall perspective into competing brands along with their strengths and weaknesses. It also gives brands and sellers insights on their choice of words while crafting customer-centric product content.
Understanding the buying context
Very often customers tend to write reviews in a hurry, peppered with multiple spelling errors and using messaging lingo. It’s manually unfeasible to scour through such reviews to derive the right context. Here’s where a review analytics tool employing fuzzy logic with optimum tuning makes certain spell-corrections. In some give-and-take scenarios, it applies common sense to make certain spell changes. In this manner, marketplaces can stay assured that every review is gleaned for accurate insights to help set the right context in their product descriptions.
Also, as customer circumstances evolve, the way they engage with a product tends to change. Developing content aligned with these changing needs requires context-driven positioning strategies. For instance, the pandemic-induced stockpiling is driving shoppers to look for consumables with longer shelf-life. The beach umbrella has turned into the backyard picnic umbrella. The robustness of a camping tent is now appreciated for doubling up as a playhouse for kids in the attic. Listening in closely to these contexts reflected through reviews and infusing them into product descriptions can help marketplaces stay notches about their competitors.
Catalyzing product development for brands
Apart from offering category-based brand filters, marketplaces like Amazon provide popular brands exclusive e-stores on their platform. These enable brands to leverage a form of DTC experience giving them a chance to garner brand-exclusive insights. In both scenarios, by plugging in review analytics, marketplaces can cull out which specific features and attributes dominate a category.
For instance, within mobiles, the camera quality and battery life are the most sought-after features. Or among air conditioners, which is the most-talked-about feature after cooling capacity and power saving? Is it no-noise or installation convenience? Review analytics makes drilling down to such granular levels of data at scale possible. Backed with such analytics brands can steer their R&D to better fine-tune their product development and make confident positioning tweaks to their product content.
Netscribes’ review analytics solution is built to fit scale. You can employ it on a host of categories — from apparel to electronics, personal care, and beyond. It comes with a highly-visual, interactive dashboard helping multiple marketplace stakeholders pull out their function based insights – be it feature extraction, regaining topics and tags, customer ratings, and trend lines over time.
For about two decades, global marketplace players have relied on Netscribes for its end-to-end e-commerce solutions. From developing research-driven rich product content to performing product review analytics and beyond, connect with us to know how you can take your product content from good to great.
