How to Analyze Open-Ended Data in Surveymonkey

1. What’s different about qualitative and quantitative data in surveys?

Quantitative survey data involves hard numbers and statistics that are tangible, scalable, and measurable. Examples of these include NPS or CSAT scores, which are easily understandable metrics for either one survey response or many. It simplifies a lot of the context behind why customers give that score, but fits pretty neatly into a quick report.

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 automatically analyzes survey responses and ensures 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 quantifiable, but no less valuable. These are survey questions that tend to focus on emotions, opinions, and sentiment, prompting respondents to type short form or long form answers. Of course, you can’t point to a singular number and say “this is how customers feel”, but you can uncover a great deal of important context within customers’ responses that helps you prioritize next steps.

However, this is the kind of text data that can accumulate large volumes very fast and become a massive challenge for manual analysis. Imagine you have 10 survey responses a day with customers writing in their feedback – that’s not bad to read through on your own! But if you have upwards of 100, 200, 500 responses a day – now this is where you need an AI text analytics solution to take the lead of your analysis.

2. How do you analyze SurveyMonkey text data with AI?

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 analyze survey responses 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, help desk 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.

Your team inevitably has some level of bias, after all. You might miss data that falls outside your expected scope, or ignore insights that don’t conform to expectations. Keatext eliminates this confirmation bias, even if your team changes over time.

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

3. Why do you need a mixed method approach to survey analysis?

A numbers-based approach to survey analysis will only ever provide a limited view of your results. By mixing qualitative data with quantitative in your approach to customer sentiment analysis, 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: Our platform automatically categorizes survey data into praises, problems, suggestions, and questions. These categories can be further customized based on your organization’s needs.
• Multilingual analysis: Keatext is proficient in both English and French, and capable of translating 50+ other languages to English.
• Advanced filtering: Once you’ve uploaded data into Keatext, you can intuitively control and segment how it’s displayed based on predefined categories and keywords.
• No-codebook insights: Instead of spending time creating a codebook with your team, 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.

With Keatext, you can easily build a 360-degree view of your survey responses in SurveyMonkey to better understand and improve customer satisfaction.

About Keatext’s SurveyMonkey integration

With Keatext, you can spend less time analyzing feedback and more time putting insights into practice. Our AI text analytics platform provides automatic recommendations through advanced predictive analytics that identify the top action items with the greatest impact on customer experience.

Our powerful algorithm can analyze thousands of customer comments and open-ended survey responses 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.

Understanding how customers feel and what drives behavior at each step of the customer journey is difficult. With Keatext, you can easily build a 360-degree view of your survey responses in SurveyMonkey to better understand and improve customer satisfaction.

• Get recommendations to prioritize actions that maximize ROI: Understand what has the greatest effect on customer satisfaction metrics like CSAT or NPS. Keatext automatically provides you with the top recommendations from your survey responses – this predictive layer connects satisfaction drivers in your surveys with an impact score thanks to our innovative AI.
• Build a 360-degree view of your survey responses: Keatext supports rich data visualizations, customizable dashboards, and sharing features to help you understand and align your team on what drives behavior at each step of the customer journey.
• Reduce your analysis time by 98%: Keatext leverages AI-driven text analytics to instantly process your open-ended survey responses. Once a survey is imported, Keatext analyzes existing responses from the date you select, and automatically triggers the analysis of new responses.

Keatext enables your team to:

• Browse predictive recommendations to take action
• Create and customize multiple dashboards
• Explore a heatmap of top topics and opinions
• Adjust topic groupings and apply tags

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.

…And check us out on the SurveyMonkey app directory!