Customer reviews are the leading driver of purchasing decisions, influencing sales and product iterations. Amazon has expanded these capabilities by launching AI-generated review summaries. These tools collect and summarize the most relevant and frequent product feedback. The initial tests focused exclusively on electronics and small appliances before evolving to include hundreds of products across various categories.

As Amazon breaks into the AI space, how can you leverage and optimize these review summaries to enhance the shopping experience and guide crucial business decisions?

How Amazon’s AI Review Summaries Impact the Shopping Experience

Reviews and ratings provide consumers with feedback and measurements of a product’s value. However, traditional reviews are limited since they emphasize quantitative rather than qualitative value. With review summaries, consumers gain insight into the reasons behind ratings and the products’ positive and negative qualities, allowing them to compare similar items. By sorting through relevant product attributes, these AI summaries compile buyer guides to present shoppers with quality options, personalizing and streamlining their experiences.

Predicting Amazon Review Summaries To Identify Key Product Themes

While Amazon’s AI-powered review summaries have gained traction in the market, only about 30% of brands have activated the tool. Consequently, many are unsure of how to analyze and predict summary trends. These review assessments have a broad and consistent structure and pattern beginning with the most common positive attribute. This is followed by a secondary favorable quality appearing in a list or sentence form. The final portion of review summaries consists of a key negative element and impartial sentiments. How can you segment these details to identify core product themes?

According to Spencer Kelty, the Head of Marketing at Yogi, conducting a thorough review analysis requires “sorting through your reviews by most recent, pulling out the attributes or themes that are mentioned, and recording the frequency of the mentions and whether they’re positive or negative.” This allows you to rank the most positive and negative features by percentage. Review summaries contain approximately 7-10 elements, so by categorizing them, you can correlate the percentages with your star ratings.

Strategies for Leveraging Review Summaries To Drive Business Decisions

Once you’ve evaluated and structured your review summaries, you must apply the data to your business. Reviews are the most accessible form of consumer and competitor data, creating a feedback loop between your brand, the market, and the shopper. You can leverage an AI analysis tool to benchmark your review summaries against competitors and gauge consumer responses and behavior attributed to these aggregations. Then, use the data and insights to iterate products, update PDPs, refocus your marketing messages and claims, and replenish gaps in the market with innovations.

Yogi’s Co-founder and CEO, Gautam Kanumuru, shares a tip for brands to consider when applying review data, stating, “What you emphasize in your PDPs ends up in reviews. Because review summaries are based on what people are writing about, especially in the most recent reviews, it will show up in your review summaries.” This provides the opportunity to govern the narrative of your feedback notes. Ultimately, improving products with AI-powered review data boosts star ratings, sales, and growth.

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?

Optimizing Product Strategies Through Ratings and Reviews

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%.

Assessing Competitor Reviews To Develop Product Marketing and Launch Strategies

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.

Best Practices for Conducting Review Analytics

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.

Gautum Kanumuru

Gautam Kanumuru is the Co-founder and CEO of Yogi, a product sentiment analysis platform that enables brands to gain deeper visibility into customer feedback and voice-of-customer. With a background in AI and natural language processing, he played a crucial role in developing Microsoft products, including Cortana and Xbox. Before co-founding Yogi, Gautam was the Vice President of Engineering at Clarke.ai and a Program Manager at Microsoft.

 

 

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Here’s a glimpse of what you’ll learn:

In this episode…

As the digital space becomes increasingly competitive, brands are harnessing customer-centric, data-driven growth strategies. Reviews and ratings have unexplored potential to implement rich feedback from shoppers, but this data source is underutilized as most brands emphasize insights from potential purchasers rather than existing customers. How are leading brands capitalizing on customer sentiment analysis to optimize products and drive sales?

According to product sentiment specialist Gautam Kanumuru, reviews and ratings are more than a measurement of volume. Rather, these data sets provide insight into your products, enabling you to develop and improve PDPs, reframe product messaging based on majority feedback, and create ad campaigns for new product launches. A robust customer sentiment analysis approach involves utilizing automated platforms like Yogi to aggregate, prioritize, and disseminate data to meet customer expectations effectively.

Join Aaron Conant in this episode of The Digital Deep Dive as he hosts Gautam Kanumuru, Yogi’s Co-founder and CEO, to address the value of reviews and ratings for product innovations and brand growth. Gautam shares best practices for evaluating reviews and ratings, how to experiment with AI for review analytics, and how data aggregation facilitates business growth.

Resources mentioned in this episode:

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When it comes to assessing the shopper journey, customer sentiment is a valuable KPI that measures consumers’ experiences with a brand throughout every touchpoint in their journey. While it may sound like just another feedback metric, the unique advantages of the KPI make it worth considering. As it gains popularity, here are some of the aspects you should know.

What Makes Customer Sentiment a Worthwhile KPI?

Traditional market research methods such as NPS are less effective in capturing nuances in the customer’s response. This metric uses a single survey question that only represents a positive and negative binary. Conversely, consumer sentiment models can express more detailed customer feedback, providing brands with actionable data.

For CPG (consumer packaged goods) brands, customer sentiment is particularly valuable. The high turnover rate of the products allows for quick adaptations and opinion changes. Customers often have more options and an easier time switching between brands. Since these products are often necessities rather than luxuries, it’s crucial to understand the consumer’s voice.

When analyzing customer sentiment, it’s important to have the right questions in mind. After all, the data isn’t beneficial unless it answers pertinent questions. For instance, brands should measure performance rates, understand the impact of customer sentiment on business processes, and assess influential market trends.

Mistakes Brands Make When Reviewing Customer Sentiment

Since customer sentiment is a nuanced measurement, it’s easy for brands to misunderstand the data.

One example of this is failing to identify analytical criteria. Gautam Kanumuru talks about the practices of Yogi’s best clients, saying, “they always, always have a benchmark, whether it's certain competitors, or the market. But taking things in context is extremely important.” Without knowing what is expected of your field or what is actually relevant to your product’s success, brands can be too quick to make misguided decisions.

Another key mistake is drawing from only one source. Using small focus groups or specific demographics can fail to explain the bigger picture. Customers are varied and unpredictable, so the best customer sentiment data comes from an array of sources on a consistent basis. This way, your practices are up-to-date and more inclusive of your entire audience.

Discussing Customer Sentiment With Corporate Leadership

Any implementation of customer sentiment services will always come down to the executive team. This means that all analytics need to support the highest goals of the business. Haithem Elembaby says that “you can take a look at your to-do list or take a look at your KPIs for that quarter or that year and figure out if this new solution can connect to something that you’re already working on.” Implementing customer sentiment into your business processes streamlines the buy-in process.

Most brands recognize the value of customer sentiment services, but it can be much harder to promote the concept to cautious budget-holders. Aside from investments, it’s beneficial to make long-term connections with the vendors themselves. This leads to better utilization of the service and access to knowledgeable people who can answer difficult questions.

Lastly, Haithem encourages companies to push for what they believe in. Hundreds of brands have seen tangible improvements by acting on customer sentiment insights that were previously unattainable. Focusing on the small wins early on can be enough to demonstrate the value. He says, “They don't even have to...blow the socks off the organization and create millions of dollars of revenue, but you want to almost guarantee that they will actually happen, right? Because…data is great, but…it's nothing if you can't do anything with it.”

The actions informed by customer sentiment data are what ultimately separates successful companies from the rest.

The rise in omnichannel marketing strategies has generated a new shopping paradigm where consumers have unlimited access to products and drive brand profitability based on their purchasing decisions. With customers impacting brand value and success, it’s crucial to develop business models that connect directly to the customer and shape their purchasing decisions and experiences.

One way to accomplish this is through consumer sentiment and VoC (voice of the customer) — two interrelated concepts indicating customers’ shopping habits, preferences, expectations, and feedback and experiences with your brand.

So, how can you leverage these areas to drive sales, maximize ROI, and regain control over your brand?

Analyzing Key Metrics to Measure Consumer Sentiment and VoC

Before implementing customer-centric practices into your business model, you must evaluate and measure consumer sentiment and VoC. This requires aggregating data points to maximize precision and generate measurable results. But, with many data collection methods and sources and multiple factors influencing these metrics, it’s often challenging to focus on a specific strategy.

According to Gautam Kanumuru, Co-founder and CEO of Yogi, and Haithem Elembaby, Yogi’s Head of Sales, data collection depends largely on factors such as a brand’s size, sector, and selling model. For instance, social media is a viable method for CPG brands to capitalize on consumer and industry trends. Similarly, focus groups and surveys allow brands to raise awareness and obtain feedback on new product launches, much like reviews and ratings provide DTC brands with valuable insights into shopper experiences and expectations.

As Haithem says, by having “the right technology that allows you to get a granular view [of the data], you can expose a lot of hidden issues, opportunities, and trends that can help with decision-making across the organization.” Experimenting with various data analytics and collection methods allows you to determine the best path forward for product positioning, messaging, and innovation.

Trends in Consumer Behavior

Creating a business approach that is both shopper-centric and profitable entails assessing behavioral trends related to consumer sentiment and VoC. One prevalent trend brands should consider is price and value sentiment. With inflation and price increases, consumers want more value for their dollar, and products that meet their specific demands have a higher sales rate.

Another key consumer purchasing trend is the effect of negative feedback on brand performance. According to Gautam, “reviews and ratings are read by anywhere between 80 and 90% of shoppers before they make a purchase.” This means that even a few negative reviews can impact conversion rates and sales.

Staying on top of trends allows you to regulate your brand’s performance and determine its success.

Curating Products for the Customer

Once you’ve established the exact data points influencing customers’ purchasing decisions, you can hone your products to meet their demands. Shoppers have access to a myriad of product information regarding pricing, availability, usage, and ratings, making them selective of the products they decide to purchase.

When considering the scope of customer knowledge, not every product or brand is the right fit for each person. So, it’s essential to utilize your data points to identify your ideal customers and customize your product messaging to solve personal use cases and create favorable purchase and post-purchase experiences that meet their expectations and preferences.

By leveraging these fundamental customer personalization strategies and assessing trends and data points, you can optimize conversion rates and generate sales and ROI.

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