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The Ultimate Guide to Customer Sentiment Analysis

In today’s increasingly competitive world, where consumers have endless options at their fingertips and the ability to try out new products and brands, understanding how your customers feel about your brand is critical for success.

Businesses need to keep a pulse on where their customers are hitting roadblocks, frustrations they have with the brand, and – of course – the things that customers love that can set your brand apart from the competition.

That’s where customer sentiment analysis comes in.

In this guide, we’ll walk you through each part of customer sentiment analysis – from what is it to why it matters to how to start doing it for your brand today – to help you build a comprehensive view of customer sentiment and start doing more with customer feedback.

What is Customer Sentiment Analysis?

Customer sentiment analysis is the practice of evaluating customer feedback to pinpoint trends, areas of improvement, and potential opportunities for growth in your customer experience.

Typically focused on written feedback, sentiment analysis allows brands to take their feedback strategy a step further to understand the tone and intent behind a review a customer has left.

positive, negative, and neutral sentiment from text analytics

By tapping into customer sentiment analysis, brands are able to highlight emerging themes within customer comments to anticipate – and respond – to customer pain points proactively.

Why Does Customer Sentiment Matter?

When you think about customer satisfaction, what metrics come to mind? 

Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), Customer Effort Score (CES), and more are probably at the top of your list. And for good reason – these customer satisfaction metrics are the best way to understand how your customers are feeling.

In truth, your customer feedback comments are a treasure trove of insights about your team, your products, and your brand directly from the people who matter most.

But simply reading customer comments on a one-off basis, without digging into the meaning or the intention behind that feedback, means that you’re missing out on a wealth of insights.

This becomes especially important when thinking about positive and negative feedback.

If you receive a 4-star review from a customer, for example, you would count that as a win for your team for a job well done. But, if that 4-star review includes feedback that explains why the experience wasn’t worth a full 5 stars – and thus, highlights the negative sentiment the customer might be feeling as a result – how does that feedback get categorized?

When we know that 53% of consumers are likely to stop buying from a brand after a poor customer service experience, it becomes more important than ever for brands to keep a pulse on what customers are thinking and feeling, and address them head on.

With customer sentiment analysis, you’re able to find those moments you might otherwise overlook to get at the heart of each customer issue.

And as a result, you become better equipped to cultivate a customer-centric approach for both your team and your overall business.

How to Analyze Customer Sentiment

For most businesses, customer sentiment analysis is a manual process.

It often involves collating pages upon pages of customer reviews and doing manual searches for core keywords, whether they are positive or negative, and then hacking together reporting based on those findings.

The problem with a manual process like this is that you more likely than not are only skimming the surface of what your customers are actually saying. 

That’s where tools like Stella Connect and Medallia Text Analytics come in.

Rather than going through each customer feedback comment one-by-one, our bundled solution enables you to process (and interpret) feedback as positive, neutral, or negative as it comes in. From there, organizations can use out-of-the-box reporting charts to quickly view trends across customer survey comments, uncover blind spots, and prioritize the most pressing issues.

This not only drives operational efficiencies by helping you save time on manual data analysis via automatically aggregating insights across the front-line, but also helps reduce call volume. 

The Ultimate Guide to Customer Sentiment Analysis

 

When you’re able to uncover blindspots and improve your customer experience before small issues become large ones, you’re understanding the “why” behind customer interactions and surfacing issues, themes, and trends at scale.

With this bundled solution, macro-level themes and key learnings from all Stella Connect customer feedback comments can automatically be detected so teams can quickly identify opportunities to make changes that matter and share them with the entire front-line team and beyond.

Doing Customer Sentiment Analysis at Scale

As your business grows, so too does the need for solutions that were built to scale with your growth and empower your team to deliver exceptional customer experiences.

With Stella Connect and Medallia Text Analytics, you can expedite your front-line training programs by sharing aggregated learnings across the customer service team, ramping new agents more quickly and helping seasoned staff stay on top of the most pressing customer issues.

Plus, our bundled solution allows you to identify improvement opportunities to share across the broader organization and executive team to prioritize investments across the business and inform broader company strategy.

Leave manual data analysis in 2020 and leverage the power of AI to automatically surface insights from customer feedback. Discover how Stella Connect and Medallia Text Analytics is helping front-line teams like yours uncover the truth behind survey feedback and increase customer satisfaction.