Turning customer reviews into actionable data

If you run a consumer-based, retail, or hospitality business, chances are your company has customer reviews on multiple website. You can easily access the reviews and see your overall average score and that’s great, but what if your score is the same as your competitors? It’s time-consuming and a bit mind-boggling to read through 100s of reviews to determine what differentiates your businesses and take action based on the feedback.

One way you can simplify this is with Import.io. As a basic solution, you could easily pull the customer reviews into a spreadsheet and search for key words. That’s just a matter of setting up a data extractor in Import.io and in a couple of steps, you have your spreadsheet.

Take it a step further and you can use Import.io to compare your business with your competitors, based on keywords in customer reviews. As an example, let’s say you run one of the five large mid-priced hotels in downtown San Jose, CA. Competition is fierce, so you are always looking for ways to improve, but you go to Yelp and all five of you have 3.5 out of 5 stars. Not very helpful.

 

 

With Import.io, you can dig deeper. Once you have the search page shown above in Yelp, capture the URL and enter into Import.io and you can structure this data, so it’s more useful. One result could be a chart based on keywords that define a guest’s experience with your business.

The chart below compares customer reviews for each hotel and shows how many times each of the key words we chose were mentioned in those reviews. Just glancing at the chart you can see more blue and orange and less of the other colors is positive for the hotel. People seem to have strong feelings for the Fairmont, both love and hate. Hotel De Anza has the beautiful décor down, but Fairmont and Marriott may want to consider refreshing their décor. This is just one data point for a business to use, but combining this data with other metrics will tell the whole story.

 

customer sentiment data

 

Now, let me show you how I got this data. It’s easy once you see how it’s done.

First, I entered my search URL into Import.io:

 

 

I then added a column of the Hotel Name and link to the detail page and extracted that data into columns.

 

 

Then, I clicked on the detail page for one of the hotels and captured that URL and entered it into Import.io to extract that data.

 

 

 

I then created columns for the detail page including the keywords I wanted. For each keyword, I created a new column and a Regular Expression to match that keyword. Here’s what the Regular Expression looks like for the word “love”. We can show you how to create that column when you are ready.

 

 

Below is the Extractor for the key words.

 

 

Now that I have my high-level list page and my one detail page, I’m done creating extractors. Now, I just need to link them together to pull the data from all five hotels. This is called Chaining in Import.io. Basically, I click on my detail extractor, then connect it to the list page.

 

 

The result of that is a structured spreadsheet of every time the keyword is mentioned in a review for each hotel and from that Excel spreadsheet, I created two types of Excel charts to illustrate.

 

customer sentiment data

 

This is a simple example, but you can go much deeper and much wider than 5 competitors. You can also choose as many keywords as are relevant to your business.

Try getting customer reviews for yourself or contact Import.io for help!

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