In a post-pandemic landscape, customer acquisition costs are rising, and shoppers are more likely to adjust their preferences and brand loyalties. Consequently, conversions are a pressing concern for many brands as they look to identify new data sources to assess shopping habits and competition, make informed business decisions, and refine the customer experience.
Analyzing customer sentiment — feelings and opinions about a particular brand — through product reviews and ratings can provide valuable insights that shape brand performance. How can you leverage these rich metrics to improve the customer experience and drive conversions?
Traditionally, brands have analyzed product reviews during purchase points, aiming for high ratings to entice customers and outperform competitors. While this approach is influential, it lacks consideration for customer preferences, limiting informed decision-making. Since these ratings are unbiased and readily available, you should scrutinize them consistently to gather relevant information addressing product complaints, favorable attributes, and marketing campaign impacts.
You can leverage these insights to update PDPs (product detail pages), refine product features, and align marketing strategies with consumer priorities, ultimately improving the overall shopping experience and increasing conversions. Tylenol’s dissolve packs present a practical example of how reviews influence business performance. 90% of the product’s negative reviews resulted from misunderstanding its use. In response, Tylenol revised its packaging, messaging, and key features in its PDP to offset those reviews. Additionally, the brand utilized positive feedback mentioning a fast-acting product feature not part of the original messaging and optimized marketing to reflect the claim. As a result, Tylenol experienced a one-star increase in its organic ratings, boosting conversion rates by 9%.
When assessing the market for product launches, competitor ratings can be valuable for developing strategies. You can leverage customer sentiment feedback for identical products to determine standards to structure your release. For instance, a negative review of another brand’s packaging may shape your design decisions. This sentiment analysis method can expedite the product life cycle by two to three years.
Since most brands already obtain insights from other marketing strategies, competitive reviews can help you structure your campaigns. Spencer Kelty, Yogi’s Head of Marketing, speaks to the advantages of gauging rivals’ reviews against your messaging: “If you have a good review volume and analysis strategy, you can look at how a competitive product is positioned, look at the reviews, and then treat it as you would your own. Basically, pretend it’s your own product, and decide what changes you would make to the marketing strategy based on what you see in place for that product and what the reviews are saying.” This allows you to position your products and brand precisely in the global marketplace.
Evaluating product feedback requires taking a calculated approach to identify and achieve brand goals. There are two phased strategies brands can implement to analyze this data effectively. You can start small by selecting three to six top-performing products, collecting the 10 to 20 most recent reviews, and interpreting the findings. Sharing these ratings across internal departments allows you to obtain additional perspectives and exchange ideas to drive meaningful change.
The second approach involves addressing and resolving a specific concern through the product life cycle. For instance, if some products have lower conversion rates and reviews, you can compare your feedback with competitors and other higher-converting products to identify the problem and gauge your product roadmap to make actionable modifications.
The Value of AI-Powered Review Analytics
Although these manual review analytics strategies generate noticeable results, they are time-consuming and lack the granularity required for significant, long-term performance impacts. Conversely, AI-powered review analytics provide comprehensive insights by gathering every product review from your brand and competitors across multiple online sources. AI tools can venture even deeper to accumulate metadata, including review times and locations and demographic information like verified buyers, sponsored reviews, and other filters.
Yogi’s Co-founder and CEO, Gautam Kanumuru, shares some key considerations for choosing analytical methods, “For someone who’s doing this for the first time…if you can extract value, that’s where starting with the manual review analysis piece is a good way to go…when you truly start to understand the power of it…that’s when something like…AI-powered review analysis becomes justified.” Whichever framework you choose, it’s imperative to ensure it aligns with your objectives and drives the ideal conversions for your brand.
