REVIEWS.ai CHAT offers an interactive, conversational experience while researching your review data. CHAT is found in the top navigation of your account.

NOTE: REVIEWS.ai CHAT is currently a BETA feature. That means we’re actively collecting user feedback on this new tool. CHAT references the most recent reviews with text, to provide the most current data and insights.

While using CHAT, if you have observations or suggestions, please share them with our team:

With CHAT, ask any question in the text box, get answers with context and examples informed by real customer reviews. Whether your product has 10 reviews on one retail website or 1,000 reviews across many retail websites, CHAT will reference all of these data points when responding to your inquiries.

Some of the most popular questions to ask your review data include:

Most users use CHAT as the first place to start an analysis of any product. After asking a broad question like the ones above, a follow-up question can be asked to get greater detail on a situation, all directly from the perspective of real customers through their reviews.

In this article, we’ll cover each of the below sections about REVIEWS.ai CHAT:

The LLM (Large Language Model) used by REVIEWS.ai is expertly trained for product and customer feedback and undergoes continuous refinement with new inputs and training. That means it responds very well to questions that are likely to have relevant data to reference from reviews.

It is recommended to keep questions short and focused on one topic per question. This helps CHAT better interpret the prompt and give you a more helpful answer.

For example, the question: “What are the top customer complaints about this product?” could be shortened to: “What are the main customer complaints?”

Here is another example. The question: “What are the top positive things people like about this product?” could be shortened to: “What are the most liked features?”

Now let’s look at a real example of using REVIEWS.ai CHAT to learn what customers think about a popular coffee machine starting with the question: “What are the main customer complaints?”

CHAT provided the top 7 negative trending topics about this coffee machine. After asking this initial question, asking a follow-up question about something specific in the response will give you even greater detail. For example, if you wanted to know more about the durability complaints (second mentioned negative topic) this is what to expect.

Continuing this pattern of asking questions and exploring responses can quickly lead to helpful insights.

To further enhance your research with CHAT, you’ll find Mentioned Topics in the sidebar. Each of these topics have a positive and negative percentage that can be clicked on to open additional details. For the coffee machine example, clicking on “87%” for Durability, will show more detail about this topic from customer reviews.

After clicking “87%” for Durability, the following popup will appear.

Here is a description of each section:

1. Mention highlights: This section displays the total number of mentions and the percentage of reviews (negative or positive) that include this topic.

2. Keyword timeline: This shows the frequency of keyword mentions across time, and the distribution of star ratings for reviews mentioning the keyword.

TIP: Knowing when a problem is fixed. Use this report to see if a negative keyword is now resolved. For example, if the keyword “broken” spiked two months ago, but is now not appearing in the Keyword timeline, it is likely the quality control team has resolved the issue.

3. Summary: CHAT provides a written summary of this topic here for quick reference and greater context.

4. Applicable Reviews: Here you’ll find all reviews from all applicable retailers mentioning this topic. Click the expand arrow on the right to see details of each individual review. Clicking the product name will take you to the PRODUCT DASHBOARD for this product.

Here are 6 popular use cases for using REVIEWS.ai CHAT:

#1: Ecommerce Managers

#2: Product Developers

#3: Marketers

#4: Brand Managers

#5: App Developers

#6: Leaders

Use CHAT to find ways to increase sales and ratings with a more optimized product listing. Ask questions that help you understand what customers like about your product description, images and related product info.

Here is an example. Asking CHAT what could be improved on this candle product listing produced the below response.

After looking at the product listing, the product description is implying this candle repels mosquitos.

However, the packaging very clearly states the product is NOT intended to repel mosquitos.

More clearly managing expectations of what this candle does to avoid confusion will reduce the number of negative reviews. This in turn will increase the overall star rating, sales and customer satisfaction.

Ecommerce Managers, you may even want to ask CHAT to help you write an ideal product listing description based directly from your review data.

CHAT can help you more quickly find top complaints to address in the product design and ideas for further innovation based on customer feedback.

Let’s use the coffee machine again for this example. Asking the question: “What could be improved to make the product better?” produces a list of potential product enhancements to evaluate.

This list of topics can then be researched for consideration. Take complaint #4 as an example: “Cup size accommodation”. A quick search for the word “fit” of reviews with images on Amazon shows this:

It is easy to see that even a fairly standard coffee mug doesn’t fit well with the coffee machine. Based on this finding, it may be worth making the nosel a little higher to accommodate taller mugs when releasing the next model.

Customers often share how they wish a product worked or features it would be nice to have. This data can also be useful in guiding future product models. Asking CHAT: “What features do customers wish this product had?” produces a list of specific features customers mentioned wanting in reviews.

Product Developers, remember to reference the Mentioned Topics in the side bar for additional context. Word Analytics can also be used to evaluate trending topics (both positive and negative) with custom filters by timeframe, product category, retailer and more.

As a Marketer, you want to drive traffic to your product listing. Understanding what people like best about the product can help you engineer messages and ads that appeal to the right type of shoppers and increase sales.

How can CHAT help you do this? Here’s an example of a Shower Cream Hair Remover by Nair. First, we start by asking: “What features do people like most about this product?”

These discovered phrases mentioned in positive reviews are great to repurpose in ads, on packaging and other messages:

“easy to use”

“gentle on sensitive skin”

“provides smooth finish”

“works well in a short amount of time”

“has little to no smell”

“effectively removes hair”

“quick and easy application”

Sure it is nice to have greater confidence when using phrases like these in ads, because you know they come directly from real customers who like the product.

But you can take this principle a step further for even more influence. Reviews are a form of social proof that impact consumer purchase decisions. That’s why review quotes will be more influential in ads than any message shared by a company. Consumers want to hear what other consumers think about your product more than what you have to say.

Ask CHAT for exact quotes mentioning one of the features customers love, like “gentle on sensitive skin”.

Marketers, you already know that your target audience is who all messaging should be tailored to. Use CHAT to understand your target audience better, faster. Quickly see who is using the product, how they are using it and what they like about it to design more effective marketing content.

As a Brand Manager, you want to understand the bigger picture. Who uses your product? Why do they prefer your brand? How are they using your product? Answers to these questions help you effectively tailor your branding campaigns to reach the right audience and connect in an effective way. Doing this over time creates brand loyalty and advocacy.

Customer reviews are publicly available for a faster analysis than any market research study. They can be analyzed at scale to guide your branding efforts. Let’s consider an example of Morningstar Farms from reviews of their popular Veggies Sausage Patties. Let’s start by asking CHAT: “Who eats these veggie sausages?”

This question instantly gives you a list of self-identified demographics who enjoy these veggie sausages, as mentioned in reviews. Understanding who is eating the veggie sausages can inform the type of people you feature in ads and who you target your campaigns towards.

Next we can ask CHAT: “How do customers eat these veggie sausages?”

Knowing the types of dishes your target audience enjoys with these veggie sausages further aligns your messaging to influence potential customers to buy.

Beyond enjoying a product, it is important to understand why consumers choose a specific brand among many options. To learn more about this topic, we ask CHAT: “Why do people prefer this brand?”

Branding campaigns that highlight the competitive advantages of the brand (according to real customers) and align with the right audience will have greater success growing market share and turning customers into advocates.

Brand Managers, know that traditional market research still has value, but online reviews can offer quick in-depth research on an abundance of topics. It is also important to note that internal-only research does not impact customer behaviors because they can’t see that data. Online reviews are public, constantly being added to and influence consumer behaviors. Reviews are a research data set you can not afford to neglect.

As an App Developer, you know the user experience is everything. Understanding what customers like and dislike about the app will not only help you improve experiences and sales of the app, but it can also help inform development of other new apps.

Customer reviews on both the Apple App Store and the Google Play Store can be analyzed with REVIEWS.ai CHAT. Take a look at what CHAT quickly found in reviews of the Spotify app.

To start, we asked: “What features are most requested?”

CHAT provides a list of 7 commonly mentioned feature requests for Spotify. It also notes that this feedback is reflective of only user reviews.

TIP: When interpreting results from any review-based analysis, remember that it is a minority of customers that write reviews. The larger the sample size, the more reliable your conclusions will be. Also remember that reviews are publicly available and do tend to shape consumer perceptions. So even if it is a minority sharing feedback in reviews, these comments shape beliefs of the majority.

Asking a follow-up question on any of these findings will provide additional detail. For example, we can ask about 6. (Improve the home page design and user interface) with the question: “What should be improved on the home page?”

Here’s one more example. When app reviews mention a competitor, CHAT is able to provide summary comparisons in context. Here’s an example of asking CHAT to compare Spotify with Pandora.

App Developers, take time to understand how users are responding to features and UX. Continuously testing and incorporating feedback will guide your product roadmap in the right direction over time. And remember, you can add competitor apps for even more research.

As a leader, you are focused on business operations, team management and big picture strategy. These significant responsibilities impact the bottom line. However, many operations and strategies hinge on customer preferences. Staying in touch with your customers on a tight schedule is challenging, but REVIEWS.ai CHAT makes it possible.

With a single question asked to CHAT, you can understand what is top of mind for your customers.

Here’s an example of the same Veggies Sausage Patty previously shared. Start with this single question: “Give me a short summary of how customers are reacting to this product.”

Instantly, CHAT provides a 1-paragraph summary for you to review. If you’d like to follow-up on any of these details, just ask. For example: “Tell me more about the new recipe.”

It is clear the new recipe is a significant source of negative reviews, damaging sales. If you want to explore the issue further, just click the negative “100%” next to “Recipe Change” in the sidebar.

At this point, you may likely want to share your findings with the product development team and ask them to investigate the situation in detail.

Leaders, remember you lead by example. Taking a few minutes out of your day to quickly understand customer feedback of a top selling product will give you increased perspective for decision making. Sharing that feedback with your team also showcases a high degree of care for the customer. These types of actions over an extended period of time instill a shared value of putting the customer first among employees.

And if you want a high-value case study to share with your team, this one shares the full story of the Veggie Sausages through review data.