Why did your NPS score drop so significantly last quarter? Why are customers contacting your support team and what could you do to drive down your support burden? And why has satisfaction with your support team increased over the last two months with your highest value customers?
Without feedback analysis software, uncovering these answers is laborious, time-consuming, or downright impossible.
Artificial intelligence (AI) and Natural Language Processing (NLP) technology has advanced by leaps and bounds in the past few years. Plenty of new feedback analytics software has appeared on the market. With so many solutions to choose from, figuring out which is right for your business can be challenging.
Every platform’s feature set and functionality varies, so understanding the must-have features for feedback analytics software will help you zero in on the right option for you.
Let’s start with value
Before we get started, let’s quickly recap what feedback analytics software is and what makes a feature important.
Customer feedback can significantly impact your business—but only if you can make sense of it. Feedback analytics software is the most efficient and effective way to analyze open-ended customer feedback.
Because of this, every growth-focused company should invest in a feedback analysis platform to process and analyze customer feedback.
What should you expect when you adopt a customer feedback analysis tool? You should see four different kinds of value:
Increased revenue: Feedback analytics software uncovers the ‘why’ behind hundreds or thousands of pieces of open-ended customer feedback, giving you deep insights into customers’ pain points and desires. This positions you to improve your product and experience, leading to increased loyalty and retention rates. Remember, companies that lead their industry in NPS also grow significantly faster than their competitors.
Reduced costs: Manually analyzing feedback is incredibly time-consuming. Feedback analytics software can do the same work in minutes that would take humans weeks or months, all while delivering better results. That’s what makes the ROI of feedback analytics software so large. Eliminating the cost of hiring or outsourcing someone to tag customer feedback means you can instead spend those resources devising strategies that will improve your customer experience.
Informed business strategy: If you’re just making guesses about which areas of customer experience you should improve, you’ll waste time and money. Feedback analytics software makes it clear which issues to prioritize based on what customers are saying. This enables strategic decisions to be based on data instead of hunches, which also means reduced human bias.
Measuring success: With better data and insights, you’ll be able to accurately measure the impact your decisions have on customers over time. Did they deliver the impact or value you expected? Were they an efficient use of resources? Answering these questions creates a learning cycle for your business.
In order to deliver this value, your feedback analytics solution needs the features and capabilities that make this possible. If you’re evaluating potential feedback analytics platforms, here’s a summary of the must-have features you should be looking for.
1. Quickly pulls data from different sources
It might seem obvious, but one of the most important features of feedback analytics tools is the ability to ingest data seamlessly from multiple sources and produce quick results from it.
Customer feedback analysis software replaces the painstaking process of manually combining and sifting through data. For example, say you need to process twenty-five thousand rows of customer feedback from your survey tool and Zendesk. A good feedback analytics tool can ingest that data and deliver insights within minutes. Coding that amount of data manually would take about three months (yikes!).
Source: Kapiche
Importing data from multiple sources allows you to combine demographic, behavioral, spend, and CX data from disparate systems such as CRMs, survey tools, social media, support software, and cloud storage providers. Your ideal analytics software should integrate with your entire tech stack.
2. Sentiment analysis to gauge customers’ feelings
Sentiment analysis, sometimes known as "opinion mining," is a technique that analyzes text to determine the emotions behind it. It helps you determine whether your customers feel positively, negatively, or neutral about a given topic—whether that’s your product, your brand, or your customer experience.
Source: Kapiche
When evaluating feedback analytics software, sentiment analysis capability is a must-have. It’s one of the quickest ways to know how your customers feel, which is a critical step in understanding why they behave the way they do (although it isn’t always a silver bullet). Humans are emotional creatures. We don’t always act rationally and logically—no matter whether we’re six or sixty-five.
If you want to understand your customers, you can’t ignore their emotions.
Sentiment analysis can also identify critical issues in real-time, such as whether a PR crisis on social media is about to explode or whether an angry customer is about to churn. These discoveries can trigger quick interventions to prevent sticky situations from becoming true nightmares.
3. Easily connect and analyze ad hoc data
Your business is constantly evolving, which means the data sources you need to evaluate will constantly change too. Plus, we all know that business is full of unexpected surprises. When your needs change or a one-off situation requiring feedback analysis presents itself, you don’t want to have to jump through hurdles.
Some vendors make it difficult to connect new or ad hoc data sources to your feedback analytics platform. One-off surveys. Social media comments. Reviews from third-party sites. All of these data sources (and more) can contain a wealth of valuable insights, so it’s important to choose a feedback analytics tool that enables you to easily and quickly plug in these types of data sources.
The more data sources you can connect to your feedback analytics tool, the less likely you’ll be to have organizational blind spots about your customers.
4. Question answering
It’s usually smart to track key feedback topics consistently over time, because it makes it easier to observe trends and pick up on sudden changes. You don’t want to be constantly shifting things around and redefining how you’re measuring things.
But sometimes business brings unique and sudden challenges. Sometimes you have to quickly do something new to respond to a challenge that has cropped up.
When something unexpected happens, your feedback analysis tool should enable you to quickly adjust the questions you’re asking of your customer data to help you make sense of the change. In other words, your tool should be dynamic—like your business—so that you can adjust what you’re analyzing any time you need to.
Investing in a customer feedback analytics solution without this capability means you risk getting stuck in the past. The things you measured three, six, or twelve months ago may no longer be relevant (COVID-related consumer and market shifts are prime examples of this). Don’t get stuck in the past—invest in software that can flex to suit today’s needs.
5. Create custom dashboards to report actionable insights
Your feedback analysis software should enable you to easily create and share customized dashboards so that you and your stakeholders can get essential information at a glance.
The ability to customize dashboards means you’ll be able to highlight different types of customer insights, such as NPS and sentiment data, saved queries, major themes, and the relationship of those themes to your key metrics. You should be able to determine what information gets shown on the dashboard, and what gets hidden.
This is critical because your stakeholders only want to see the insights that are most relevant for them. Include anything extra, and you risk losing their attention.
It’s also critical that your feedback analytics software enables you to easily share the dashboards you create. Your goal should be to make it nearly effortless for your teams and leaders to stay up to date on important insights, and your software should help you do that.
6. Spot emergent trends and themes in your feedback
It’s easy for customer insights teams to focus on the past. Your customers provide feedback about past experiences, so you naturally find yourself looking in the rearview mirror a lot. And when you’re manually analyzing customer feedback, it takes so much time that you can’t help but fall months behind.
But growing businesses can’t afford to get stuck in the past, and that’s where a feedback analytics platform can help. We’ve already talked about how feedback analytics software massively speeds up the analysis process. One important impact of this is that it enables you to identify emerging trends in close to real-time.
If you just launched a new product and your customers hate it because it’s missing one vital feature, you can’t afford to spend a quarter categorizing feedback and creating a report. You need that insight ASAP so that your engineering team can quickly build and release that feature.
Feedback analysis software can crunch customer feedback immediately, highlighting those themes and enabling you to react faster.
7. Impact scores for better prioritization
Understanding the impact of different factors helps you identify which customer issues you should prioritize first, based on the potential return on investment (ROI).
For example, say you knew that by adding more movies and games to your in-flight entertainment offer, you’d improve your NPS by ten points. Making seats more comfortable would likely improve NPS by one point. Which one would you choose?
Source: Kapiche
The answer is obvious if you have the graph above. But if you don’t have feedback analytics software that can provide you with this information, the decision is a lot less clear. Your ideal feedback analysis solution should help you reach these kinds of meaningful insights quickly and easily.
8. Ability to drill down into different segments
Imagine you’re an insights manager for a major airline. Your flight experience team recently implemented a change to your in-flight menu, and now they need to know what customers that flew Premium Economy think about the new menu versus the old menu.
Or here’s another example: Say you’re a retailer that notices an increase in complaints about inventory levels in the past thirty days. That’s good to know, but if you’re a global retailer it doesn’t tell you much; it’s not specific enough. What is causing this increase?
To find an answer, you’d need to drill down to see what types of customers are complaining and which regions the complaints are coming from. You’d want to see the affected products. Drilling down deep enables you to understand the problem more fully, which allows you to create a far more effective solution.
Being able to filter down to a specific customer segment lets you find answers to complex questions like these. It shouldn’t matter whether you’re segmenting customers based on geography, revenue, company size, product type, or even a combination of these factors or others—a powerful feedback analytics tool lets you slice and dice data in as many ways as you need to.
9. Search across data sources
Virtually every feedback analytics tool will let you connect many data sources (although it may not always be easy, per feature #3 above).
Connecting all of your data sources is great, but it’s only a first step. Once connected, you really need to be able to query and search across all of your data sources. This functionality can be complex, since data sources can be so different from each other. But there’s no point in adding all your data to one tool if you’re still functionally treating it like it’s siloed data.
For instance, say you recently discontinued a product. You’ll want to be able to see if customers are still talking about the product in the ensuing weeks and months. Where are they talking about it? What’s the sentiment? How do their feelings differ across your different channels?
A customer feedback analysis tool should empower you to ask and answer these questions. Unfortunately, some feedback analytics tools can’t effectively solve this problem. When you’re choosing the right tool for you, make sure that your chosen software enables you to query across all of your data sources—without making it a major headache.
The best feedback analytics software has the features you need
Before investing in a customer feedback analytics solution, make sure you spend time understanding your needs as a business. It’s the only way to know which features you’ll require in order to discover powerful insights that drive informed decisions. Think about where you are today and what you’d like to know about your customers in the coming years.
We’ve covered a number of must-have features that every modern feedback analytics platform should include. Investing in new software is a big decision. It pays to take a long-term view. Your business might need all of these features today, or it might be a few years before you’ll take full advantage of each of them.
Whatever your current state is, Kapiche has all the top features needed to conduct deep and flexible feedback analysis, giving you actionable insights from any data source within minutes. If your feedback analytics software isn’t delivering the actionable insights you need, Kapiche can help. Watch a demo today!
