Published on

November 24, 2023

Sentiment Analysis

5 easy steps to customer sentiment analysis

Customer sentiment can seem like a black-box, but understanding what customers think about your brand, products, and services is crucial to success.
Craig Wisneski
Co-Founder & Head of G&A, Akkio
Sentiment Analysis

Ever wonder what your customers are thinking?

Customer sentiment can seem like a black-box, but understanding what customers think about your brand, products, and services is crucial to success. Sentiment analysis is a way to understand customer opinion, and can help you track how your business is doing, what customers think of your products, and what they want from you. Sentiment analysis will soon be a $10 billion industry, given its use-cases for tracking and optimizing customer engagement.

In this article, we'll explore customer sentiment analysis and its benefits.

What is customer sentiment analysis?

Customer sentiment analysis is a method of evaluating the attitudes and opinions of customers towards a product, brand, or company. It is used by businesses to understand how customers feel about their products and services. 

Customer sentiment can be positive, negative, or neutral. Sentiment analysis can be used to track how customers feel over time, and to understand what factors influence their opinions. Tracking customer sentiment can be done from chatbots to the call center, and can be used to improve customer satisfaction and loyalty.

What are the benefits of customer sentiment analysis?

In today's business world, data is king. And one of the most valuable data sets you can have at your disposal is sentiment data.

Understanding Your Target Market

After all, if you know how your target market feels about something, you can make better decisions about your business strategy and marketing campaigns. You can tailor your messaging to resonate with them more effectively. You can even anticipate and head off potential problems before they arise.

For instance, studios like Ubisoft have recently taken to integrating NFTs into their video games, and were swiftly met with extreme backlash from the gaming community. If they had been using sentiment analysis, they could have identified this potential issue before it became a PR nightmare.

But it's not just about avoiding problems. Sentiment data can also help you identify opportunities for growth. Perhaps there's a new market trend that your target market is particularly excited about. For example, gacha games (or mobile games that are monetized via randomized virtual goodies) are exploding in popularity right now. If you're a game developer, this is information that could help inform your next project.

No matter what industry you're in, understanding the sentiment of your target market can be extremely valuable.

Identifying The Strengths and Weaknesses of Your Business

In addition to helping you understand your target market better, sentiment data can also be used to identify the strengths and weaknesses of your business.

For example, let's say you run a luxury skincare brand. You might use sentiment analysis to track how customers feel about your products over time. Are they getting more or less positive reviews? Are there any particular products that seem to be receiving especially positive or negative feedback?

This information can be used to inform everything from your product development roadmap to your marketing strategy. If customers are loving a certain product, you might want to double down on your marketing efforts for that product. And if they're not so thrilled with another product, you may want to consider reformulating it or improving the way you're selling it.

Identify Opportunities For Growth

In addition to helping you understand your target market and the strengths and weaknesses of your business, sentiment data can also be used to identify opportunities for growth.

For example, let's say you're a small startup in a highly competitive space. You could use sentiment analysis to track your competitor's mentions and see how customers feel about them. If you see that they're constantly getting negative reviews, that could be an opportunity for you to swoop in and capture some of their market share.

On the other hand, if you see that your competitor is consistently getting positive reviews, that could be an indication that they're doing something right that you're not. In this case, you might want to take a closer look at their business and see if there's anything you can learn from them.

Improve Customer Service

Another way sentiment data can be used is to improve customer service.

Let's say you run an e-commerce store. You could use sentiment analysis to track customer reviews and identify areas where your customers are unhappy. Perhaps there's a particular product that keeps getting negative reviews because it's constantly out of stock. Or maybe there's a shipping issue that's causing a lot of people to leave negative feedback.

This information can be used to improve your business and make sure that your customers are happy. In the case of the out-of-stock product, you might want to increase your inventory levels. And in the case of the shipping issue, you might want to figure out what's going wrong and fix it.

How do you do it? What data points do you use for customer sentiment analysis? 

One common way to collect customer sentiment data is through social media platforms like Twitter and Facebook. You can monitor feedback and look for patterns in customer behavior.

After all, customers turn to social media to voice their thoughts and opinions, both good and bad. So, if you’re not monitoring those channels, you could be missing out on important insights.

Another way to collect customer sentiment data is through polls and surveys. You can include a survey on your website or send it out via email campaigns.

Asking customers directly about their experience with your product or service can give you valuable insights into their level of satisfaction. And, it can help you identify areas where you need to make improvements.

Finally, you can use tools like Google Analytics to monitor website traffic and identify trends in visitor behavior. This can be helpful in spotting potential problems that might be affecting customer satisfaction levels.

How to implement customer sentiment analysis?

The modern consumer generates a huge amount of data every day - from social media interactions to website clicks to product reviews. This data is a goldmine for understanding customer sentiment, yet most businesses are not leveraging it to its full potential.

There are many tools available that allow businesses to collect and analyze data, such as SurveyMonkey and Google Analytics. With these tools, you can monitor visitor behavior, identify trends, and create reports to share with your team. 

SurveyMonkey, for instance, lets you run interviews with customers and ask questions about their experience with your product or service. This data can be valuable for understanding how customers feel about your brand.

Meanwhile, Google Analytics can be used to track website interactions and identify areas where customers might be having difficulty. This information can help you improve the customer experience on your site. However, these tools are not designed for AI-powered sentiment analysis.

This makes it challenging to gain meaningful insights into customer sentiment at scale. This is where Akkio comes in. Akkio is an artificial intelligence platform that makes it easy for anyone to build and use machine learning models to predict outcomes.

With Akkio, you can predict anything from clinical trial abandonment rates to sales conversion, churn rate, and more. You can also use it to forecast revenue, component and commodity prices, and more. In other words, Akkio gives you the power to make data-driven decisions about your business - decisions that are informed by customer sentiment.

If you want to take your customer sentiment analysis to the next level, Akkio is the solution for you.

5 steps to apply customer sentiment analysis to a business 

In a rapidly developing digital world, understanding and responding to customer sentiment has never been more important. Businesses that can quickly and accurately interpret customer sentiment stand to gain a significant competitive advantage.

Fortunately, there are now a number of cutting-edge tools and techniques available to help businesses take full advantage of customer sentiment data. Here are five key steps for applying sentiment analysis to your business:

1. Connect Your Data

Data is the fuel that powers sentiment analysis. In order to get started, you'll need to connect your relevant customer data sources - whether it's social media, customer reviews, survey responses, a CRM, forums, customer support tickets, or even webinar transcripts.

Tools like Hubspot and Intercom have easy options to export their data for training your sentiment model.

2. Build a Sentiment Model

Once you have your data, it's time to build a sentiment model. Traditionally, this would involve hiring a data scientist to develop a custom solution based on complex algorithms.

Fortunately, there are now a number of pre-trained machine learning models available that can be easily deployed to predict sentiment with high accuracy. After connecting your data to tools like Akkio, you can automatically build natural language processing (NLP) models that analyze customer interactions in real-time to understand customers’ feelings in real-time.

3. Deploy the Model

Once you have your sentiment model built and trained, it's time to deploy it. This will involve setting up a way to automatically receive new customer data (such as through an API), and then passing this data through your sentiment model in order to generate predictions.

The legacy solution for this would be to write custom code to handle each data source and prediction type. However, there are now a number of platforms that make it easy to deploy machine learning models with just a few clicks, such as Akkio.

4. Take Immediate Actions

Once you have your sentiment predictions, it's important to take action on them in order to improve your business. For example, if you're seeing positive sentiment scores, you might want to retweet positive tweets or reviews; if you're seeing negative experiences, you might want to respond directly to the customer.

In some cases, it may even make sense to take automatic actions based on predicted sentiment. For example, if you're running an e-commerce store, you might want to offer a discount to customers who have been predicted to be unhappy with their purchase. Taking these actions will boost your net promoter score, or NPS, as you’ll create more positive customer experiences by removing pain points in the customer journey.

Secondary effects of higher NPS and CSAT (customer satisfaction) metrics include improved customer loyalty and therefore better retention. As customer churn is the silent killer of SaaS businesses, using sentiment analysis tools can make-or-break your firm.

5. Improve Your Business

Finally, it's important to continuously improve your sentiment analysis solution by incorporating feedback and new data sources. This will help ensure that your predictions remain accurate and actionable over time.

Further, you’ll want to consider implementing sentiment analysis in multiple areas of your business. For instance, if you're selling products online, it's important to monitor customer feedback in order to improve your products. Sentiment analysis can be used to automatically classify customer feedback by sentiment, making it easy to identify and address areas for improvement.

And by monitoring customer sentiment, you can stay ahead of the curve in terms of what customers want. For example, if you notice a surge in positive sentiment around a particular product category, you could start stocking more of these products in your store.

Further, if you're losing customers, it's important to identify the root cause so that you can take action to prevent further churn. Sentiment analysis can be used to predict which customers are most at risk of leaving, based on changes in their sentiment over time. By using AI to detect unhappy customers, bad experiences, and negative sentiment, businesses can improve the customer journey at every stage.


If you're not using AI to analyze customer sentiment, you're missing out on a crucial tool to improve your business. By better understanding your target customer's needs and wants, you can more effectively market to them and improve the overall customer experience. Further, by identifying the strengths and weaknesses of your business in the eyes of customers, you can make necessary changes to improve.

In the past, AI was only accessible to large companies with the resources to hire expensive engineers and use expensive AI platforms. Akkio has changed that by making it easy and affordable for small businesses to get started with AI. With Akkio, training time is free and much faster - you can get an accurate model in 10 minutes without using code.

If you're ready to take your business to the next level with AI, click here to start your free trial of Akkio today.

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