Learn from Online Reviews About Your Business with Data Analysis

Matt Crowley - April 14, 2023

Online reviews have become a key factor in our every day decision making from direct-to-consumer products and services to B2B decisions.

  • What new TV should I buy? Let me check reviews…
  • What dentist should I see? Let me check reviews…
  • What urgent care location should I take my child to? Let me check reviews…
  • I’m not cooking tonight, let’s get takeout. Let me check reviews…
  • What software should we use? Let me check reviews…

We can’t avoid them, yet many organizations don’t regularly review them to see what customers are saying. In an ideal world, you’ll move beyond analysis and into proactive requesting and engagement with reviews. However, a valuable first step is just to listen.

Learning from Reviews with Data Analysis

As an organization that focuses on data informed strategy, data is the first place we often turn to, surprise! There is a lot that you can learn from reviews simply by reading them, but often it becomes difficult to pull out key trends when you are reading reviews one-by-one. For example, if you have 568 reviews in a single location, reading the reviews one-by-one won’t result in any over-arching insights that are an accurate representation of all reviews.

This is where data analysis comes in. There are many technologies that can help with this, but I’m going to focus more on the concept of analyzing reviews to  gain insights with a data analyst mindset, rather than the technology for today.

Let’s say you operate an urgent care network with many locations. It’s critical to understand what your patients are saying about the services they received at those locations. So, you could narrow your focus to a specific geographic area and assess the percentage of negative to positive reviews received at each location, like this:

We can clearly see that Location #1 is doing great, with 90% of all reviews being positive. However, Location #9 is really struggling with 86% of all reviews being negative.

Then, you can break down the negative reviews received at location #9 by key themes discussed in reviews, and analyze trends in the average rating by each theme. Here (below) we can see that the ratings for reviews that mention the cleanliness of the facility and the wait time to see the provider have begun to experience month-over-month declines to very low levels in June and July. This allows you to look into that location further to assess if there are any operational changes that should be made to improve.

Then, ultimately continuing to watch the review trends as changes are implemented to see if the impact is being felt by the patients themselves. This type of data analysis is critical to ensure you are reaching the insights that can have a positive impact on your business.

If you need help with data analysis challenges your facing, don’t hesitate to reach out to info@morevisibility.com and we’ll see how we can help!

Posted in: Analytics

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