Now, more than ever, businesses need to make sense of online reviews and analyze what customers are trying to tell them. And, they can simply do this by using AI-powered text analytics and sentiment analysis.

2. How Is Sentiment
Analysis On Reviews
Done

3. Overview
Now, more than ever, businesses need to make sense of online reviews
and analyze what customers are trying to tell them. And, they can
simply do this by using AI-powered text analytics and sentiment
analysis.
Companies need to understand that success lies in the hands of their
customers. Understanding how your customer feels about your
product or service is imperative to financial survival and prosperity.
Here, we’ll understand the process of sentiment analysis on reviews
and how it helps businesses improve their products and services.

4. Why Do You Need Product Review
Sentiment Analysis?
When brands or businesses have voluminous reviews across multiple sites,
extracting and analyzing them for sentiment becomes daunting and time-
consuming. Businesses for utter efficiency need to look to AI-powered review
sentiment analysis to retrieve insights from reviews quickly and precisely.
How is Review Sentiment Analysis Done?
A reliable sentiment analysis API is used to find insights and relationships within
the textual data. The three-step process is simple:

5. Step 1: Data Gathering
Collect and prepare the data that you want to analyze whether it’s internal
(customer feedback) or external data (feedback from review sites). To prepare the
data from text analysis, all you need to do is put it into a CSV or XLS document
format.
Step 2: Integrate Review Sentiment Analysis API
Next, run your input data through your sentiment analytics API. It’ll quickly return
sentiment scores for each relevant review topic, aspect, or entity ranging from -1
for negative emotions, 0 for neutral, and +1 for positive emotions.

6. Step 3: Sentiment Analysis Dashboard
Once you receive the sentiment scoring, you can easily receive different
visualization tools like Tableau, Power BI, Repustate to quickly turn your data into
visual reports. These reports are made from charts, graphs and tables to identify
trends, patterns and actionable insights in your data.
An aspect is a specific element or feature of business, for instance, customer
service, that further can be classified under. Customer service can be classified
into various topics like wait staff, line ups, reservations, etc. A topic or subject is
the matter or subject dealt with in the review.

7. Lastly, the Benefits of Sentiment Analysis on Reviews
There are myriad benefits of sentiment analysis on reviews, but here, I’ve
pocketed the mains.
● Accurately target operational improvements at pain points
● Identify and extract how your customer feels about your business
● Easy to visualize customer insights for fast analysis
● Classify feelings according to different parts of your business
● Develop baseline sentiment metrics to measure the change in progress

8. Conclusion:
Once the data starts flowing in, you will realize your business has a goldmine
of review insights that you can draw from. This trick works wonders to
embrace good with the bad. Rather than considering negative reviews as a
damper, use them to bring the ball in your court. Not only do you get better
profitability, but better brand perception as the customer gets the satisfaction
of being heard.

9. Thank you!
Understand your data,
customers, & employees with
12X the speed and accuracy.
Visit: www.repustate.com to
learn more