---
# System prepended metadata

title: Creating Actionable Insights from Survey Data

---

# Creating Actionable Insights from Survey Data

Whether you have ten consumers or ten million, surveys are remarkably easy to produce and deliver. Many survey programs are out there, and it seems like they grow simpler to use and implement each month. It's common knowledge that companies should gather client feedback. Therefore, this is all positive information.

What do you do with all of those survey results, though? How would you employ it? How should you approach the various survey questions and data types they provide? There are many ways to respond to these inquiries, but one is straightforward.

**What is actionable insight?**

Insights that can be immediately translated into action or response are known as "[actionable insights](https://getthematic.com/insights/how-to-get-actionable-insights-from-your-customer-feedback-analysis/)." The information guiding the insights may be quantitative or qualitative, organized or unstructured. Actionable insights motivate action, but people or procedures must carry it out.

![](https://hackmd.io/_uploads/Hybuu9rI2.jpg)

One or more individuals examining raw data produce actionable insights. Big data can yield actionable insights when structured and unstructured data are present in significant quantities.

While certain practical insights may be drawn immediately from data, analysis is required to guide the required actions in some circumstances. Data can provide a picture of what occurred, but further data or human analysis may be required to understand why. Frequently, the "why" rather than the "what" is what makes an insight into action.

Anyone, including [professional employer organisations](https://www.serviapgroup.com/peo-professional-employer-organization/), may benefit from practical insights. Managers may leverage actionable insights to enhance goods, services, corporate culture, employee morale, and staff retention. These insights' data sources may include partners, clients, or staff. Engineering, sales, marketing, finance, legal, operations, and executive management are just a few of the divisions in a business that may utilize actionable information to make adjustments and improvements.

The viability of the suggested course of action must be considered in actionable insights. A useful insight is of little value if the suggested action is difficult or impossible. For instance, a finding from client interviews may imply that 60% of clients desire a lunar visit because the organization needs more resources to implement this knowledge, so it cannot be implemented.

**Survey score data**

Data that is a key performance indicator (KPI) is survey score data. It provides quantitative information and typically offers a big figure to concentrate on. Customer effort score (CES), Net Promoter Score (NPS), and customer satisfaction (CSAT) are three common types of score data.

Simply put, score data refers to information often appearing on your consumer insights dashboards. High-level, top-line data offers an instant overview of your team and business performance.

The fact that survey score data is comprehensible makes it extremely valuable. If NPS was 70 last quarter and 20 this quarter, something has probably gone wrong, and you don't need to be a CX expert or analytics whiz to see that. Sharp drops in score data often indicate the need for some sort of intervention, and the sooner, the better.

Another beneficial feature is the ability to score data to assist in establishing North Star objectives. The moniker "North Star" refers to long-term, aspirational goals that are supposed to lead and chart the course of your business. Setting a North Star objective to raise NPS by 10 points yearly is reasonably simple if your leadership team wishes to emphasize being more customer-centric over the following years.

Significant objectives are challenging, but score data may be crucial in serving as your organization's North Star aim.

**Data from survey amplification**

You receive amplification data from your surveys as the second type of data.

![](https://hackmd.io/_uploads/SyFAOqHL2.jpg)

Consider a guitar amplifier. If you don't have an ear for music (guilty! ), an amp captures the signal from your guitar, runs it through a circuit to “shape” the sound, amplifies it, and finally pushes it through your speakers. The guitar's relatively weak signal is increased in volume and fullness by the amp so your audience can enjoy it.

Data amplification functions similarly. Specific survey questions will yield data that "amplify" your score data. It gives you a complete view of what your consumers think and feel so you can appreciate it—or, at the very least, completely grasp it.

In other words, amplification data enables you to comprehend the reasons behind your score data and offers suggestions for future improvement. Attribute data and verbatims are the two main categories of amplification information.

**Attribute data in customer surveys**

Like score data, attribute data is often quantitative. The distinction between the two is that your top-line score data often comes before your attribute data.

Consider the scenario when CSAT is the top KPI in your survey results. The question "How would you rate your overall satisfaction with your customer support experience?" is one that you pose to consumers. You determine your CSAT score by using their responses ranging from 1 to 7.

Customers can be questioned more about particulars of their experience after responding to the initial question, for example:

* How responsive do you think our support staff is?
* How often did you contact us to fix your problem?
* How simple was it to acquire the assistance you required?

These questions let consumers provide a more complete picture of their experiences when they respond. Even if your total CSAT score maybe 85%, the attribute data from these follow-up questions will help you understand why consumers are so happy with your service.

Attribute data is often most beneficial for your CX team, even if score data is frequently essential for keeping your entire business informed and in sync. Attribute data is frequently helpful for an agent- or team-specific coaching and improvement initiatives since it is more particular and divides each customer's experience into more granular categories. As a result, the managers and leads of your support staff should pay special attention to this data.

You may learn from attribute data what went well and poorly during a particular contact. Increasing each particular attribute's region should improve your top-level score data, another significant consequence of attribute data. Organizing your replies into categories and scanning your many characteristic questions for trends is the simplest method to spur beneficial changes.

**Verbatims survey data**

The second category of survey amplification data consists of verbatims. Your verbatims represent your consumers’ unstructured comments. Verbatim questions allow you to hear from your consumers in their own words, while structured questions (like multiple choice) provide lovely clean statistics.

Most of your verbatim data will come from your free text survey questions, such as "What else could we do to improve your experience?" and "Why did you choose that response?"

![](https://hackmd.io/_uploads/rysItqS8n.jpg)

If you work as an insights or support manager, you undoubtedly already know how difficult and time-consuming verbatim analysis can be. But it's not necessary to be that way. You have two options for analysis when you have a large collection of client verbatims: manual analysis or employing a feedback analytics solution.

**Using a feedback analytics tool to analyze data from open-ended surveys**

Use a feedback analytics platform like Kapiche to evaluate open-ended survey data, which is a second—and far more straightforward—method. Open-ended data is not the only type that can be analyzed with feedback tools, but here is one instance where they excel.

Feedback analytics systems can handle unstructured text data far more quickly than humans—in minutes instead of hours, weeks, or months. These tools are objective, better at seeing themes, and can assist you in spotting new trends in the information from your consumer survey. A feedback analysis tool may be frequently done quickly and easily:

* Choose a tool.
* Your data sources together
* Start working

In order to provide deeper insights to your business and better serve your consumers, you may focus on comprehending the insights in your survey data while your tool handles the time-consuming analysis.

**How to create a survey**

Are you weary of manually gathering information and comments from website visitors? You can easily make unique surveys and quizzes with the [WordPress Survey Maker plugin](https://ays-pro.com/wordpress/survey-maker). Make data-driven decisions to enhance your website’s performance by gathering your audience’s viewpoints, preferences, and insights.

You may select from various question formats with Survey Maker, such as multiple-choice, rating scales, and open-ended inquiries. Make your survey's appearance and feel unique to reflect the branding and layout of your website. Anywhere on your website, such as articles, pages, and sidebars, may contain surveys. Additionally, you can display your surveys in response to specific triggers like scroll depth or time spent on a page.

Use this WordPress survey plugin to create surveys for your website. It is an excellent tool with many options, including 22 distinct inquiry types. Suppose the shortcodes for User History, Conditional Results, and Emails, Send Mail To Users. In that case, Unlimited Surveys and Submissions, Logic Jump, Multi-Page Survey, and Submission Analytics (Charts) are available on your website.

Utilizing the WordPress plugin for survey development will yield fantastic results. One advantage is the plugin’s ability to schedule, export, and import surveys. The 22 question types provided by the plugin are the best additional tool, as was already said. The evaluation test and feedback forms are also included.

Survey Maker’s user-friendly interface makes your surveys simple to develop, maintain, and analyze. You may export your data in CSV format for additional analysis and view real-time survey results and analytics. Users can be sent to specific sites after completing a survey, and you can modify the survey completion messages that appear to them.







