5 Platforms Using AI to Analyze Customer Reviews

This post is the latest in our “Word of Mouth” series. It’s our editorial focus for the month of February, including topics like reputation management, and reviews optimization. See the rest of the series here. 

Display advertising and social media campaigns can drive website traffic, but when it comes to converting shoppers and driving actual sales online, it’s all about the reviews.

Online reviews have a major impact on whether shoppers decide to pull the trigger and purchase products from brands or retailers they have not purchased from before. They also convey sentiment about products or services to which brands may not otherwise have access, which is why brands that disregard the online reviews posted by their customers are making a major mistake.

Beyond the star ratings lies a wealth of information. Sentiment and opinions can be used to shape the way brands develop their highest-selling products. Given the volume of reviews posted each day, however, it would be impossible for most major brands to analyze every customer reaction individually. Instead, a growing number of brands are utilizing artificial intelligence (AI) technology to extract and analyze the sentiment from product reviews. (Street Fight’s parent company, Brandify, offers a similar AI-powered review analysis tool in partnership with IBM Watson. Brandify’s tool is focused on reviews of local businesses.)

Here are five examples of platforms that offer this type of AI technology for analyzing customer feedback posted online.

1. Lexalytics: Understanding how customers feel, and why they feel that way
Rather than manually analyzing comments and reviews, Lexalytics encourages retail marketers to use its natural language solutions to automate the process. Lexalytics’ sentiment and intent analysis is available through the company’s multi-lingual text analysis engine. Brands can quickly analyze thousands of tweets, reviews, and online comments, using algorithms to identify recurring themes and topics. (For example, poor fit or excellent customer service.) Out-of-the-box scoring helps retailers understand how customers feel and why they feel that way, without having to read every review individually.

2. SentiGeek: Using feedback to help brands enhance the customer experience
SentiGeek uses advanced algorithms to analyze customer reviews and comments. Using dependency relations, proprietary industry-specific tagging, complex grammar and syntactic rules, cognitive/pragmatic rules, and other resources, SentiGeek analyzes reviews and identifies feelings and opinions. The company’s technology can also classify reviewers, as it processes shoppers’ reviews taking into account “context particularities.” The resulting information is presented in the form of reports and analysis, including current trends based on shifting sentiment in online reviews, as well as customer profiles and industry-specific customer personas.

3. Revuze: Spotting shifts in consumer interests
Global brands like Neutrogena, KitchenAid, and Gillette use Revuze to better understand the sentiment being expressed in consumer product reviews. Revuze’s algorithm spots shifts in interest in products or features, as well as emerging trends—for example, if people shopping for beauty products are suddenly interested in a new ingredient. The company’s AI-powered text interpretation engine constantly scans its clients’ online and offline data sources and then creates reports that executives can use to drill down into any element of any product. In addition to analyzing the reviews being posted on a brand’s own website, Revuze also tracks Facebook, Twitter, call centers, chat logs, and in-store data.

4. BirdEye: Turning trending text into actionable insights
BirdEye’s customer experience software is typically used to help brands manage online reviews, social media postings, and surveys. However, since early 2018, BirdEye has also been giving its clients a way to look at insights with an AI tool enhancement. The tool, dubbed the Annotation feature, gives businesses a way to look at insights generated by natural language processing. BirdEye identifies snippets of text that appear frequently in the feedback posted about brands—in reviews, social media replies, news articles, and discussions in online forums—and converts it into actionable insights.

5. Aspectiva: Understanding how shoppers feel about specific product attributes
Aspectiva is using AI to automatically surface what people are saying about products online. Retailers with e-commerce websites can integrate the technology into their own product pages to give shoppers more confidence about what they can expect from the items they’re about to buy. Aspectiva automatically surfaces product attributes from reviews, which means shoppers can filter products by attributes, like softness or durability. In the event a certain product doesn’t rate highly, Aspectiva’s technology shifts and displays dynamic product suggestions that are personalized based on the shopper’s intent.

Stephanie Miles is a senior editor at Street Fight.