Buyer’s guide: How to choose the right enterprise feedback analysis tool for reliable insights

Survey responses, NPS trackers, Google reviews, … the number of places your customers can give feedback is ever-increasing, so is the number of verbatims and data variables one can dig into. The same applies when gathering feedback from thousands of employees.  

Analyzing this feedback with precision is far from easy without the right tools and processes. While reading through Excel spreadsheets sounds like a thing of the past (or a nightmare if you've been there), finding your way around the available solutions in the AI era can feel overwhelming.  

As you dig into the voice of your customers or employees, your goal is to discover reliable insights and make data-backed decisions. So how can you break it down into simple and relevant selection criteria? 

The feedback analysis tool you work with determines: 

• the type of feedback you can analyze 

• the quality of your analysis 

• the speed of your analysis 

• the ease (and confidence) with which you can draw conclusions 

...and so much more. Choose the wrong one, and you'll leave valuable information on the table or - even worse – lack trust in your insights or take action on faulty data interpretation.

 In what follows, we will go over the criteria to keep on your checklist when choosing your feedback analysis tool.

What to Look for When Choosing Your Feedback Analysis Tool 

Creating your list of requirements is the first step before choosing the right tool for your use case. To get you started, we've built an evaluation matrix (yes, in Excel!). That’s probably the most low-tech tool we have ever built 😜, but we know such a spreadsheet can be handy when comparing solutions.  

You can download your evaluation matrix here, then use it to compare solutions. You can also add more criteria or adjust the weighting to match your specific needs.

In this article, here are the criteria we will go through in detail:

1.  Ease of data import

2. Speed of analysis

3. Speed of implementation

4. Quality of text analysis

5. Reporting & Insight discovery

6. Privacy, compliance & security

Read on for the complete breakdown on the criteria to look for and the questions to answer to choose the right solution for your enterprise needs.

1. Ease of data import  

The chance of your company receiving feedback in just one place only is as good as non-existent (think about nps trackers, surveys, point-of-sale feedback, online reviews, etc.). To speed up time to insights, you need a flexible tool that lets you bring your data without the help of a tech wizard.  


Questions to answer 🤔

• Can you upload your desired file types by yourself (xlsx, csv, spss, …)?

• Is there a modern API, and/or integrations with your data sources?  

• Can you easily ingest metadata and bring other variables in addition to text responses?  

• Can you easily compute columns together, or combine datasets into 1 project?  

How Caplena does it ⬇️

Caplena allows you to import data in three different ways: 

1. by integrating Caplena with review sites, app stores, and survey tools. 

2. by uploading your data yourself. A wide range of file types (xlsx, csv, spss, …) is supported and there's no need to rely on a support team to help you.

3. by connecting Caplena to an almost limitless list of platforms through its public API. 

You can combine data into a single analysis or keep it separate. For instance, you can combine survey data with your online reviews for a unified understanding.  

2. Speed of analysis  
 

If you've been there, you know that a manual analysis takes time, sweat, and tears. To manually "code" a survey of around 2,000 comments, it will probably take around 2 weeks. Yet, there's a big difference in the speed at which different tools perform feedback analysis. While traditional (rule-based) feedback analysis with platforms like Qualtrics can take from 30 minutes up to 48 hours to upload data if there are a lot of text responses, an AI-powered platform like Caplena can process half a million rows per hour.  

As a Voice of Customer (or Voice of Employee) analyst, what matters to you is: 

• How fast can you get from upload to insights, even with thousands of verbatims.   

• How fast can you keep up with changes in your data (especially if you analyze tracking studies).  

Even if your company does not mind spending a lot of resources on employee or customer feedback analysis once, it's not something you can keep doing without falling behind. Indeed, your topics aren’t static and will change over time. This is key to spotting feedback trends and evaluating the impact of a product update or a change you've made in the customer journey. 

You want a tool that can continuously process any new data and dynamically adapt (or guide you to adapt) your topic collections accordingly.  

Questions to answer 🤔

• How long does it take to import a new 10k row project? 

• How much time should you spend on topic modeling?

• Can you be alerted when significant changes happen?

How Caplena does it ⬇️

On average, Caplena can help you analyze 10,000 text responses in just 2 hours. That’s the time from import to insights, including verifying the quality of your topics and sentiment assignments.  

You can also set alerts to be notified when significant changes happen, or to receive digests at the frequency of your choice (more on that later).  

3. Speed of implementation  

If fast processing is key, implementation time is equally important. Some platforms can take weeks (even months) to set up initially.  And you'll most likely want to make changes as you refine your analysis process, especially to tailor it to your industry and use case. It makes a big difference if you can make those changes yourself in just a few hours versus when you have to contact support and potentially wait several days. 

It is key to choose a platform that's flexible so you can ingest data quickly, make interactive changes, and get results back almost in real time. 

Questions to answer 🤔

• How many weeks does it take to be up and running?  

• What do the implementation steps typically look like?  

• How much of the setup can be done autonomously vs. with the help of engineering or customer success? 

How Caplena does it ⬇️

Caplena's intuitive interface allows you to get started right away - no need to wait for support to help you get set up. Initial setup takes a few minutes, and we have designed a 2-week onboarding provided by insights professionals to support you with your first steps.

4. Quality of text analysis 

4.1. Complete topic modeling (and without overlap) 

First, you want a tool that can assign the relevant topics to each verbatim it analyzes. Then, you want to make sure that all of these topics cover every aspect of your business that you've received comments on, without any overlap between them. Imagine you are running a customer feedback analysis for a nationwide health food chain. One of your customer feedback comments may be assigned the topic "in-store service" while another may get the topic "staff friendliness". These two topics overlap, which can cause issues for your analysis. 

Questions to answer 🤔

• Do topics have to be defined through keywords? (ideally, you want to avoid pre-defined topics and let your platform discover the topics emerging from your data to mitigate bias)

• Is the topic modeling process interactive?  

• Are you able to import existing taxonomies? Can you add topics yourself?

• Can you add a sufficient number of topics per project? (typically up to 100 topics for ad-hoc surveys, up to 200 topics for trackers - companies like Lufthansa analyse 600 topics)  

How Caplena does it ⬇️

Caplena identifies topic collections to ensure mutual exclusivity and collective exhaustiveness (MECE). That means the assigned topics will cover all themes that come up in your feedback (95%+) while avoiding any overlap between them. 

And, you can interact with your topic collections and fine-tune them (more on that in the next section).

4.2. Correct analysis and quality assurance

Researchers who have coded open-ended responses manually know it too well. On top of the time manual analysis takes, there is a higher risk for bias and inconsistency, regardless of how well a codebook is defined. Rule-based analysis isn't great either. It will leave comments uncategorized if they don't neatly meet the pre-defined criteria.  

An AI-powered tool solves these problems by discovering the topics emerging from the data, thanks to advanced Natural Language Processing and Machine Learning.  That being said, there are so many parameters that go into AI feedback analysis that it's impossible to have full transparency on exactly how an analysis came to be.

This wouldn't be an issue if it weren't that an analysis can be faulty, and many tools don't allow you to assess the quality and correct (fine-tune) the AI's interpretation.  Imagine having analyzed thousands of comments only to realize that a portion of them has been miscategorized and not only is there nothing you can do about it, but you would also have to go through your entire data set to know how big the problem is.   

Questions to answer 🤔

• Is there a way to measure the quality of the topic assignments?

• Can you train, fine-tune and influence the AI? And can you do so without the help of customer support?  

• Can a proof of concept be done with your data to get a hands-on feeling for the quality of the assignments?  

• Is the platform designed to ensure a strong analysis foundation to give your team and stakeholders trust to act upon the insights discovered? 

How Caplena does it ⬇️

Caplena allows you to verify and correct the AI's topic assignments. This means you can fine-tune the analysis while simultaneously training the AI for your specific industry and use case. And when you make a change, the AI will remember that and apply its reasoning wherever it's relevant. 

On top of that, the tool auto-evaluates by assigning a quality score to its analysis (overall and at topic and sub-topic levels). You can then verify categorizations to achieve greater accuracy. 

This combination of fast and high-volume AI analysis with manual spot checks and corrections ensures higher precision. And most importantly, it provides trust in your results, so you can confidently present them to stakeholders and make data-backed decisions. 

4.3. Multilingual data support

Even if you only operate in one country, there's a chance your customers might not leave feedback in the same language. As a Swiss company, this is something we are used to.   

If your customer or employee base is multi-national, you cannot affort to you only analyze feedback in one language. On top of that, people from different countries or with different cultures may experience your brand in a different way. For instance, a company like DHL analyzes employee feedback across 45+ languages as part of their program "Every voice counts".

Questions to answer 🤔

• How many languages are supported?

• Are they supported natively, or through a translation service?  

• In the platform, can you toggle between translations to have confidence in the results?  

How Caplena does it ⬇️

With Caplena, you can analyze customer feedback in different languages inside a single project. Its AI natively supports more than 30 languages. Beyond these, its built-in integration with DeepL and Google Translate increases that support to over 100 languages.  

Also, in reports and dashboards, one can simply click on a result to see the verbatims attached, and translate them back to their original language.  

5. Reporting & insights discovery

5.1. Smooth reporting

Correctly analyzing your data is one thing, drawing actionable insights from it and sharing those with stakeholders is another. That's why you want a tool that summarizes your analysis in an easy-to-understand way and that can pull up specific information as you need it. 

Ideally, your tool will allow you to add these insights into a shareable report right within its interface, so you don't need to worry about creating reports from scratch on another platform. 

Questions to answer 🤔

• Can you create reports by yourself? Can you customize them? 

• Are there options to visualize the NPS score, categorical variables and numerical variables? 

• Can you visualize the different levels of the topics and their sentiment? 

• Are advanced methods like driver analyses, correlations and statistical significance calculation available?   

• Can you make dashboards available to other team members without having to pay for a seat?  

How Caplena does it ⬇️

With Caplena, you can create custom charts and dashboards that are easy to share with other users within your organization or with external stakeholders via a shareable link at no extra cost. A company like IKEA makes insights available to 16,000 employees. Aside from a current state of affairs, you can include statistically significant changes over time, demonstrate correlations between topics, and visually represent the true drivers of satisfaction. 

You can also use a chatbot to dig into your data at maximum speed. But instead of producing just convincing-looking text, this chatbot is designed to perform quantitative and qualitative analysis and supports advanced filtering options. Ask it things like "What do women aged 25-34 and living in the UK think of our product offer?" and it will let you know. It's an easy and more natural way to quickly get precise insights without having to go through your entire analysis. 

If you would like to get a feeling for how Caplena reporting works, request an interactive report here. 

5. 2. Filtering and segmentation 

It's great to know what drives customer or employee satisfaction overall, but understanding the needs and expectations of specific audience segments is an even more powerful way to drive targeted improvements. 

To get this information, look for a tool that allows you to segment your customers based on the information you have about them. This could include: 

• age 

• location 

• purchase history 

• … 

It's also important to know what has the biggest impact on your customer satisfaction and your business KPIs. If your NPS is down by 20%, and you notice that negative feedback comes from a topic like delivery failures, segmenting by location can allow you to quickly identify the affected market(s) and come up with an action plan that will have a huge impact on your business. 

Questions to answer 🤔

• Is flexible filtering supported? (by topics, or by other variables in your data) 

• Is it possible to look at, and compare segments?

How Caplena does it ⬇️

Caplena allows you to filter data in seconds. You can easily spot feedback differences between various customer segments and filter for specific topics to see which ones affect your overall customer satisfaction most. 

For instance, the car manufacturer Kia segments their feedback analysis based on vehicle fuel types. This helps them understand the expectations of specific customer segments, like Electric Vehicle buyers.  

5. 3. Competitor analysis  

If your competitors are doing much better or worse than you in certain areas, that's important information. They could be leaving a gap you can fill, or if their customer support appears to be awful and yours is great, you can highlight your support in your marketing communication. 

At the same time, if you notice that your customers are displeased with a part of your service and a competitor does great in that area, you know there's a risk of them crossing over.  

Going through your competitors' reviews manually takes a lot of time, so look for a tool like that allows you to analyze and compare competitor data to supercharge your benchmarking process.  

Questions to answer 🤔

• Can you easily pull in reviews from Amazon, Google Maps, Trustpilot, App stores and analyze them?  

How Caplena does it ⬇️

You can bring Google, Amazon and Trustpilot reviews, or mobile app reviews from the Apple App store and Google Play. This allows you to:

• benchmark your reviews against those of competitors 

• gain an understanding of your position in the market 

• learn where you can outperform your competitors 

• spot and track review trends 

5.4. Alerts   

Imagine that you're working for an airline that has recently started working with a different provider for its on-board meals. All of a sudden, your onboard meal satisfaction score drops drastically. 

If you check your analysis reports manually once in a while, you can go a long time without noticing this issue. If, on the other hand, you use a tool that alerts you when statistically significant changes happen, you'll be able to take action much more quickly. 

Questions to answer 🤔

• Are there options to be notified of significant changes?

• Can notifications be customized to your monitoring needs?

How Caplena does it ⬇️

With Caplena, you can set alerts for things such as 

• when sentiment on all or specific topics changes in a statistically significant way. 

• when specific topics are mentioned more or less frequently. 

• when potentially new topics pop up. 

This allows you to stay on the ball without needing to live in your feedback analysis tool. 

6. Privacy, compliance, and security 

To give you truthful feedback, people need to know they won't get called out on it and that their data is safe with you. Look for a tool that is GDPR compliant and SOC 2 Type II certified. Ensure that feedback can be automatically anonymized so no personally identifiable information gets shared. Protect respondents' identity looking for tools that don't allow drilling down on results to infer who a given comment is coming from. 

Questions to answer 🤔

On top of certifications, your due diligence process will most certainly include these questions:  

• Will the data be used to train third party LLMs (e.g. OpenAI, Gemini)? 

• Where are the data centers located and are they ISO 27001 certified? 

• Are network connections always encrypted TLS 1.2/1.3?  

• Do you support two-factor authentication and SSO? 

How Caplena does it 

Caplena automatically anonymizes text on import so that no personally identifiable information becomes accessible. We're also GDPR compliant and SOC 2 Type II certified. For more information, our team is available to answer all questions related to privacy, security and compliance.  

7. User interface  

No matter how powerful and feature-rich a tool is, if the interface is unintuitive, you'll shy away from using it. Book a demo, look at screenshots, watch videos, and browse the knowledge base, to get an idea of what you'll be working with if you sign up.. Ask if a trial or proof of concept is possible for hands-on evaluation.

Questions to answer 🤔

• Is the interface easy to navigate and intuitive?  

• Will your team and stakeholders easily adopt it?  

• How much training is needed to be up and running?  

How Caplena does it 

Caplena's interface is easy-to-use, visually appealing, and comes with presentable reports and an AI chatbot that can provide both qualitative and quantitative analyses to answer your queries.  The platform is designed for insights professionals and their stakeholders teams who have access to the shareable dashboards. The goal is to help all users quickly understand the voice of their customers and employees, discover insights and make data-backed decisions.

Onboarding is provided by insights professionals who are available to support with taxonomy and report creation, and to answer your questions at any stage of your projects. 

Caplena: The Best Feedback Analysis Tool for Enterprise Needs  

There's a lot at play when choosing a feedback analysis tool, regardless of whether you're looking to analyze customer feedback or employee feedback. Accuracy, speed, user-friendliness, and the flexibility to import data and make changes by yourself are just a few of the things to take into account. 

Enterprise brands and market research agencies can't take any risk with the huge amount of data they gather. Not using a capable tool might result in shaky analyses you won't trust or steer you in the wrong direction. 

Caplena was built to analyze enterprise feedback data quickly and precisely, with a unique combination of AI analysis and human fine-tuning that ensures transparency, quality and trust in your results. Book a call with us today to discover how Caplena can help you capture the voice of your employees or customers.

Define what your strong points are and compare solutions on your shortlist by downloading our customizable evaluation matrix. This tool can help you figure out which capabilities you need to prioritize to select the right tool for your business.