Survey results, customer reviews, social media mentions, oh my. It’s a feedback-driven world, and our brands are just living in it.

The days of relying on a great product or service to do your branding are behind us, which is why acquiring all types of feedback is important.

Quantitative feedback like net promoter scores can provide a general pulse of your brand performance, but qualitative feedback in the form of text can provide insight into how people actually “feel” about your brand.

Sifting through textual data, however, can be impossibly time-consuming for some brands. Doing so manually just isn’t feasible and the nuances of brand sentiment could be difficult to capture.

One solution to this problem? Sentiment analysis.

Let’s look at the importance of sentiment analysis and how it can be used to improve customer experience through direct and indirect interactions with your brand.

What is sentiment analysis?

Before we can dive into the nitty-gritty of customer experience, we first need to understand the basics of sentiment analysis.

Sentiment analysis is part of the greater umbrella of text mining, also known as text analysis. This type of analysis extracts meaning from many sources of text, like surveys, reviews, public social media, and even articles on the Web. A score is then applied based on the sentiment of the text. For example, -1 for negative sentiment and +1 for positive sentiment. This is done using natural language processing (NLP).

“sentiment

Sentiment scores help businesses understand what sort of emotions their brand evokes in a group of people. These emotions can be happiness, sadness, anger, or simply impartialness. From there, it’s up to the business to determine how they’ll put that sentiment into action. One way is to let sentiment inform how customers are currently experiencing your brand.

3 ways to analyze customer sentiment

In a world of endless opinions on the Web, how people “feel” about your brand can be important for measuring the customer experience.

Consumers desire likable brands that understand them; brands that provide memorable on-and-offline experiences. The more in-tune a consumer feels with your brand, the more likely they’ll share their emotions in written text (through surveys, reviews, social media, and more).

But the opposite is true as well. As a matter of fact, 71 percent of Twitter users will take to the social media platform to voice their frustrations with a brand. Those users also expect brands to respond to queries within an hour of tweeting, but we’ll save that for another day.

These conversations, both positive and negative, should be captured and analyzed to improve the customer experience. Sentiment analysis can help.

Let’s first look at how more direct interactions with brands can be analyzed.

1. Text analysis for surveys

Surveys are a great way to connect with customers directly, but they’re also ripe with constructive feedback. The feedback within your survey responses can be quickly analyzed for sentiment scores.

For the survey itself, consider questions that will generate qualitative customer experience metrics, some examples include:

  • What was your most recent experience like?
  • How much better (or worse) was your experience compared to your expectations?
  • What is something you would have changed about your experience?

Remember, the goal here is to acquire honest textual responses from your customers so the sentiment within them can be analyzed. Another tip is to avoid close-ended questions that only generate “yes” or “no” responses. These types of questions won’t serve your analysis well.

Next, use a text analysis tool to break down the nuances of the responses. TextiQ is an example of a tool that will not only provide sentiment scores but extract key themes from the responses.

After the sentiment is scored from survey responses, you’ll be able to address some of the more immediate concerns your customers have during their experiences.

Another great way to acquire sentiment is through customer reviews. This method is a bit more indirect compared to surveys.

2. Text analysis for customer reviews

Did you know that 72 percent of customers will not take action until they’ve read reviews on a product or service? An astonishing 95 percent of customers read reviews prior to making a purchase. In today’s feedback-driven world, the power of customer reviews and peer insight is undeniable.

Review sites like G2 are common first-stops for customers looking for honest feedback on products and services. This feedback, like that in surveys, can be analyzed for emotional responses.

The benefit of customers providing reviews compared to responding to surveys is that it’s more indirect, which could lead to more honest and in-depth feedback. This isn’t a rule-of-thumb, but analyzing customer reviews has its clear upsides.

To improve the customer experience, you can take the sentiment scores from customer reviews – positive, negative, and neutral – and identify gaps and pain-points that may have not been addressed in the surveys. Remember, negative feedback is just as (if not more) beneficial to your business than positive feedback.

3. Text analysis for social media

One of the most indirect ways to acquire textual data is through social media mining. This is made possible using social media management software with monitoring capabilities.

Monitoring tools essentially scrape public social media like Twitter and Facebook for brand mentions and assign sentiment scores accordingly. This has its upsides as well, considering users are highly likely to take their uninhibited feedback to social media.

One downside to text analysis for social media is character limitations. Whereas in surveys and review sites there is a set of contexts, social media is more free reign. This could create some noise within the data, but this isn’t a huge concern.

Regardless, a staggering 70 percent of brands don’t bother with feedback on social media. Because social media is an ocean of big data just waiting to be analyzed, brands could be missing out on some important sentiment.

Analyzing customer sentiment, creating better experiences

Whether you’re using a text analysis tool for survey responses or a social media management tool for mining purposes, the key here is to be on the lookout for customer feedback.

Acquiring feedback and analyzing its sentiment can provide businesses with a deep pulse on how customers truly “feel” about their brand. When you’re able to understand your customers emotionally, you’re able to provide a more robust customer experience.

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Author Bio: Devin Pickell
Devin is a Content Marketing Specialist at G2 writing about data, analytics, and digital marketing. Prior to G2, he helped scale early-stage startups out of Chicago’s booming tech scene. Outside of work, he enjoys watching his beloved Cubs, playing baseball, and gaming.