How Keatext lets you analyze Surveymonkey responses at scale

Expand your survey horizons with better qualitative data, customer sentiment, and text analysis, all powered by Keatext's Surveymonkey integration.

Surveymonkey can be an invaluable tool for your business, providing deep insights into both your customers and your employees. 

Provided, that is, you can effectively analyze the responses you collect. And that’s precisely the problem — many businesses lack the capacity to comprehensively analyze Surveymonkey data. 

Because they have to collate and analyze responses manually, they’re limited both in what data they can collect and how they leverage that data. Rather than in-depth sentiment analysis or text analysis, they must focus on raw variables with only a sample of qualitative data. This not only restricts your post-survey analysis, but also represents a considerable barrier to survey design. 

To explain why, we’ll first need a quick refresher on quantitative vs. qualitative survey data. From there, we’ll show you exactly how you can leverage Keatext to take your Surveymonkey solution to the next level.

Qualitative vs. Quantitative Data Analysis

Quantitative survey data involves hard numbers, facts, or figures. It’s tangible, scalable, and measurable, typically expressed in numbers. According to Zapier, there are four broad categories of quantitative data that can be gathered in a survey.

No matter the scale at which you conduct your survey, Keatext will automatically pull in survey responses, analyze them, and ensure you get the best, most accurate insights possible.

  • Categorical or Nominal data: Labels such as brand name, feelings, colors, product types, and so on.
  • Ordinal data: Most commonly takes the form of a question attached to a likert scale (strongly disagree-strongly agree or never-often). 
  • Interval data: An ordered set of numbers or number ranges. 
  • Ratio data: Numeric data without a predetermined range or set of choices. 

Qualitative survey data is much less concrete, but no less valuable. Qualitative survey questions tend to focus on emotions, opinions, and sentiment. They’re far more in-depth than quantitative questions, typically requiring a short form or long form answer from respondents.  

How Keatext’s Automation Enables Better Qualitative Data Analysis on Surveymonkey

As you’ve likely surmised, qualitative survey questions are challenging to manually evaluate, as they require each answer to be independently analyzed. This requires considerable time and effort, even with a smaller sample size. As your organization begins to scale, that verges on impossible, particularly if your team has other data it must manage. 

Here’s where automation enters the picture. With Keatext’s Surveymonkey integration, you can analyze every single piece of data, whether qualitative or quantitative. No matter the scale at which you conduct your survey, you need no longer rely solely on impressions — instead, Keatext will automatically pull in survey responses, analyze them, and ensure you get the best, most accurate insights possible. 

Rather than simply providing you with individual snapshots of your Surveymonkey data, Keatext orchestrates it into an ongoing data feed. This allows you to benchmark your survey responses over time, allowing you to directly measure the results of any ongoing initiatives. And if you’re leveraging any other customer or employee feedback tools alongside Surveymonkey, Keatext integrates with over 400 different survey and customer relationship management tools. 

The real strength of the platform lies in how Keatext evaluates qualitative data. It’s a seamless, painless process that frees your team to focus on utilizing data rather than analyzing it.

This is in addition to feedback uploaded from elsewhere, including product reviews, helpdesk tickets, and call center transcripts. Through automation and orchestration, Keatext not only keeps all this data in one place, it does so while providing a level of consistency that’s difficult to attain with manual analysis. 

Human agents inevitably have some level of bias, after all. They may miss data that falls outside their expected scope, or ignore insights that don’t conform to expectations. Keatext eliminates this confirmation bias, even in the event of a change in staff. 

The real strength of the platform, however, lies in how it evaluates qualitative data — and how that evaluation empowers a mixed method approach. 

The Value of a Mixed Approach to Customer Sentiment Analysis

A numbers-based approach to survey analysis will only ever provide a limited view of your results. By mixing qualitative data with quantitative, you can add significantly more context to the feedback you collect. Rather than simply looking at a list of raw numbers and values, you’ll have a complete picture of what all that information actually means. 

Keatext achieves this in a few ways: 

  • Opinion and Sentiment Metrics: Collected data is automatically arranged into categories that include praises, problems, suggestions, mentions, and questions. These categories can be further customized based on your organization’s needs. 
  • Natural Language Processing: Keatext’s multilingual algorithm is proficient in both English and French, and capable of translating 50+ other languages to English. 
  • Advanced Filtering: Once data has been fed into Keatext, you can intuitively control and segment how it’s displayed based on predefined categories and keywords. 
  • No-Codebook Insights: Instead of requiring your team to spend time creating a codebook, Keatext automatically identifies topics in your survey data. It’s a seamless, painless process that frees your team to focus on utilizing data rather than analyzing it. Better yet, it can even provide insights you weren’t initially expecting. 
  • Visualization and Reporting: With Keatext, it’s easy to understand how feedback impacts your business, and it’s just as easy to share that understanding with key stakeholders in your organization. 

Create Better, More Flexible Surveys with Keatext

Platforms such as Surveymonkey are invaluable when it comes to gathering customer feedback. Yet analyzing and organizing the data gathered from those platforms is often tedious and time-consuming. It doesn’t have to be, though. 

With Keatext, you can spend less time analyzing feedback and more time putting insights into practice. Its powerful algorithm can analyze thousands of customer comments and survey results in a matter of minutes, automatically identifying sentiment and grouping similar topics together. This information is displayed in a single pane of glass, giving you a comprehensive, omnichannel view of your most critical data — all updated in real time.

Discover how leading companies are using Keatext to revolutionize how they design, evaluate, and analyze their customer surveys — and redefine your own surveys in the process.

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