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5 Ways Data Could Help Shape the Future of Online Reviews

Anyone who’s attempted to grow or market an online business in the past few years has likely experienced the power of online reviews. Over 67 percent of consumers are influenced by online reviews, and many of them claim that they trust online reviews from strangers about as much as they would trust a personal recommendation from a friend or family member. Not only do these reviews help new users form an impression of your brand, they can also earn you visibility in new places (like third-party review sites), and even generate more traffic from higher and broader search ranks.

But there’s another side to the benefits of online reviews, and data’s about to play a major role in it.

The Other Side of Online Reviews

Most people look at the benefits of online reviews in terms of direct inbound benefits; for example, a customer posts a good review, so that affects other customers by convincing them your brand is trustworthy and may encourage them to buy your product.

But you can also use reviews as a tool to gather more information. What type of user is this? What type of experience did they have with your brand? What kinds of words do they use to describe your services? What was most important to them, positive or negative? On larger scales, this information can be indispensable for learning about your demographics and improving your business. This is especially powerful for longer, more in-depth reviews, which features extensive detail and both quantitative and qualitative review points.

How Data Can Shape the Future of Online Reviews

Let’s take a look at some of the ways data could influence and increase the benefits of online reviews:

  1. Evaluating reviewer emotions. It’s usually pretty clear what a reviewer thinks of your products or services based on the rating they give you, but what are they actually feeling? Data capturing and analysis software will soon be able to gauge user emotions based on word choices, sentence length, and other linguistic and semantic factors, which can help you contextualize user reviews with greater accuracy and more depth. For example, which is more telling about the quality of your business—a one-star review from someone who’s extremely angry, or a one-star review from someone who seems calm and logical?

  2. Categorizing reviews based on peripheral factors. Your “average” rating for a given product or service doesn’t give you the full picture of your performance. How do you perform in certain areas? With certain customers? At certain times? Data analysis can help you categorize your reviews based on these kinds of factors. For example, what kinds of reviews do you get in summer instead of winter? How do middle-aged men review you differently than teenage girls?

  3. Keyword analysis. Data analysis can also help you scan reviews for certain keywords, or identify certain keyword trends as they emerge across multiple reviews for your products and services. Do your customers seem to be using the same kinds of words to describe your business? Are there certain topics that seem more important to them than others? You can use these keywords to understand more about how your demographics operate, and then use that information to shape your marketing campaigns in the future.

  4. Trend projection. Online reviews have powerful effects on future customer experiences, so understanding any trends in play could be vital in reversing the momentum of negativity or reinforcing the momentum of positivity. For example, if you’re seeing a downward trend in the average rating of a certain product, proactive trend projection can let you know it’s happening before it delves into a full-on spiral. This can draw your attention to specific areas in need of improvement, so you can fix them before the problems become any worse. Or, conversely, it can help you invest in the key areas of your business that are thriving the most.

  5. Tying effects to causes. Finally, you can use data analysis and projections to tie different trends and changes in the reviews your company receives to different causes that you’ve created on your own. For example, let’s say you made a recent change to your customer service procedures. Big data would allow you to delve into specific, possible micro-changes in average customer reviews to see if it made a difference—and what kind of difference it made. The same is true for product design changes, new marketing tactics, or any other changes or additions you can think of.

Online reviews have always, and presumably will always, be powerful sources of information and reputation improvement for b.... When powerful data-gathering and data analysis tools start taking more control over these nuggets of customer information, they’ll become even more powerful.

Keep watch for these trends as they develop, and incorporate them into your business to drive more understanding and growth. 

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