We’ve written a lot about customer sentiment and why it matters over the past several years. Now, if you Google sentiment analysis, lots of articles come up as it’s gained more popularity and brands are better understanding its importance. But what’s rarely discussed is practical use cases and examples of how to use sentiment analysis in real business scenarios.

Before we dive in, let’s cover the basics of sentiment.

  • What is customer sentiment? Customer sentiment is the emotion behind customer engagement. When you monitor sentiment, you try to measure the tone, context, and feeling from customer actions. Whether a customer completes a purchase, leaves a review, or mentions your company socially, there is always an emotional state connected to their action.
  • What is sentiment analysis? Sentiment analysis is essentially the process of collecting, analyzing, and acting on customer feedback. This can be the analysis of freeform, unstructured text (such as a repository of your app store reviews or comments on social media) or more linear metrics (such as Fan Signals or NPS).
  • Why is customer sentiment important? In short, tracking customer sentiment helps you understand three major metrics: Overall customer satisfaction, loyalty, and engagement intent. The more you know about a customer’s current emotional state, the more you can tailor your marketing campaigns to provide an engaging, helpful experience and adjust your product roadmap to meet customer needs faster. Customer sentiment analysis gives you insight for your mobile marketing and product strategy, helping your dollars stretch further and your ROI increase.

What are some sentiment analysis use cases?

Customer sentiment data can be used to impact many different areas of business, but we see most brands using this information to inform product decisions as well as marketing campaigns.

However, it can also help with other areas of business from market research to brand reputation and more. It’s critical to measure and analyze customer sentiment because of the large-reaching impact it has across departments.

1. Identifying and utilizing your fans.

If you are able to identify people who love your brand, you can then retarget them to encourage desired behavior. An example would be sending an app store Ratings Prompt so they’ll leave you a high rating and positive review. You could also direct them to share the app with friends and family through referral links. Or perhaps you could send them to social media and encourage them to share their positive experience with their following.

2. Winning back unhappy customers.

One of the biggest struggles brands face is being able to identify customers who are about to churn or leave forever. And even once they identify them, it’s often too late. If you’re proactively and consistently tracking customer sentiment of the same customers over time, you’ll be able to see exactly when a shift in sentiment occurs. You can then quickly follow up to either ask for more information (why are they unhappy? What can be done to solve their issue) and then offer them exclusive perks to stay with you (discounts, deals, extended trial periods, etc.).

3. Creating more fans by targeting neutral customers.

It’s a struggle to convert neutral or non-engaged customers into loyal, highly engaged customers. One of the simplest ways to accomplish this is by retargeting those who do not indicate they feel particularly strong one way or the other about your brand. This historically has been a tricky task since most neutral customers also remain pretty quiet and rarely voice their opinions. We call this the “Silent majority.” But if you retarget them and offer them special discounts, experiences, or deals, you can more effectively convert them into loyal fans.

4. Quickly flagging and solving product issues.

If you’re consistently checking the pulse of your customer base through sentiment analysis, you’ll be able to quickly identify if there’s a sudden drop in sentiment. For example, if you measure sentiment before a new version of your app is launched and then check it again after, you might see some shifts in sentiment. That’s normal. But if there’s a huge shift in previously happy or neutral customers suddenly indicating they’re unhappy, you likely have an issue with your app launch. This would allow you to do a few things: Quickly follow-up with those customers to gather more information and then win them back, and also inform your product team of any bugs or issues that should be addressed immediately.

The biggest takeaway is that it’s not enough to just have the raw data of how many people love or hate your brand. You need to understand the why behind these feelings and emotions. Sentiment analysis allows you to dive deeper and find these answers.