Wondering how to analyze survey data?
It is natural for businesses to sit on a truckload of data after a survey marathon. While it is good to rest on your laurels, albeit briefly, you are missing out on the essential part of the survey process if you don’t do this- analysis.
If your goal with the survey were to collect data, you wouldn’t gain anything except having data that you can post on your blog posts.
How do you use the feedback that you get from your customers?
Fret not. We are here to help you with the entire survey analysis process
Why analyze survey data?
Data doesn’t add any value when it stands on its own. Data is only valuable when transformed into information that can be used to make business decisions.
The word ‘analysis’ can make many businesses run for cover. You don’t have to use complicated algorithms to analyze the survey feedback from your customers.
Following the details in the guidebook here, you can fish out brilliant strategic decisions for your business based on the survey results.
When you send surveys to your clients, you do not use the same questions in the entire study, right?
Imagine the respondent’s dismay when they find that all the questions in the survey are open-ended or yes/no type questions.
This is why you need to prepare a set of questions that ask for a varied type of data.
When you get the answers, they will be in different formats. The question remains: how do you analyze the data in various forms?
Points to consider when analyzing survey results:
Your Objective When You Analyze Survey Data
If the goal of the survey was to get high-level insights, then you might not be missing out on much, even if the response rate is low.
But if you want a deep understanding of the issues that plague you, it makes sense to get higher response rates as it is essential for more precise insights. When you seek more insights, your respondents must indulge you in your follow-up surveys.
Segment the survey results.
One of the most important marketing rules is segmentation because customers are different and don’t want the same thing. There are a lot of variables using which you can segment your customers.
It could be demographic factors like sex, age, region, and other factors like the type of customer, their total duration, the amount of money they have spent on your products, and so on.
Separating the respondents based on these characteristics helps you identify what works for them and makes your targeting laser-sharp.
Bird’s eye view of the result
After the survey, while you will get a lot of profound insights, don’t forget to take note of the results as a whole. Use questions like below to get information you can share with your customers and employees.
- What is the overall percentage of customers extremely satisfied with the product?
- Percentage of customers who said they would renew the subscription?
- How many are subscribers to our newsletter among the respondents?
- How many of the customers plan to invest in more of our products?
- Which mode of communication did the customers like most?
- Which is one area that we need to improve?
Answers to all these questions hold a lot of weight, and it can reveal direct business-related insights.
Search for patterns
The best part of analyzing survey results is that you will find surprising insights leaving you in awe. It is all about finding patterns that you would have otherwise missed.
Break down the results that you get and look for patterns that emerge when using the data. Identifying patterns can help you narrow in on the target audience more carefully and help save the efforts of your sales and marketing team.
Open text comments
You don’t have to scout for patterns in open-text comments, as the customers will open their hearts out. This question has a lot of value as it gives the respondents the option to write what they feel without having to use the predetermined options offered in the survey.
Make it a point to assign a separate person to read through all the text comments.
More often than not, these fields will have a lot of ideas that the respondent throws at you. The written words will have a lot of unsavory comments as well. Make sure that you follow up with these respondents to ensure that you solve their problem.
Conduct a series of surveys.
If it is in your budget, conduct your surveys a few times to avoid any drastic business changes that might affect you.
If a small sample of customers say they want a feature installed, do not immediately go with that. You may want to verify that it is indeed something your customers would want.
The next time you ask for customer feedback, draft the questions differently and see how they respond. The answers might be different this time. It is better not to make any decisions in haste.
Visual representation of the results
Using the right visuals can make the data compelling; even a non-specialist can find it easy to understand. It is pivotal, especially since you will also send the results to your customers.
Pie Charts, Columns, Bar Graphs, Line Graphs, Word Clouds, Stacked columns, and Custom Charts are some of today’s most popular visual representation tools.
Choosing the right visuals can make the survey data easy or difficult to interpret. Even users would like to see the data in different formats. It will be great for them if you give them the option to change a particular data set in graphs to columns, bar graphs, and others.
Visualizations have a lot of impact, especially since you will present the survey results. Always ensure you have the best visual representation planned to get the survey results.
We mainly insist on creating stunning visual models of the survey results because specific data can only be understood in visual forms.
Determine the next step of action you want to take
Once you have analyzed the entire stretch of results, you need to create a step-by-step process to figure out what you want to do with it.
If there is a set of customers who are entirely disgruntled with what you do, it is high time that you take immediate action to counter it. Then, take care of the next set of issues that plague your business based on the feedback from the survey.
Create a series of steps to communicate with your customers how you want to take it forward. Tell them about the mistakes you have been doing so far to have elicited the kind of feedback you got.
Promise to work on the steps and assure them that the mistakes you made were in the past and you will do your best to better your previous performance.
Share your results
No, sharing the survey results is not a part of analyzing them. However, you must take the time to share the results of the survey with all the stakeholders involved, especially the ones to whom you sent the survey to.
Tell them you appreciate their taking the time to respond to your survey.
If you plan to work on any of the suggestions that the feedback gave, then make it a point to address that as well. Let them know you will be working on the input and give them a deadline if possible.
Share your customers’ misgivings and the nice things they say about you. Being honest and transparent will give you more brownie points.
In today’s business world, being authentic is everything. It is the only thing in business that would never backfire- authenticity.
Should you use a tool to analyze survey data?
The traditional method of analyzing surveys is not only passe, but they will waste your time. If you look at it closely, you will notice that you are spending money down the drain in the long term.
Why? Because it takes a lot of time to analyze the data while ensuring that there is no human error that results in inaccurate analysis.
When a large amount of data in the form of feedback is involved, it becomes too much to manage the entire workload properly. An online survey tool is the best way to ensure all the work is completed correctly and with little human intervention.
Also, an online survey tool like SurveySparrow doesn’t care about the workload. It can run through thousands of data sets within seconds to produce a brilliant mixture of visual representations.
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How to Use Advanced Methods to Analyze Survey Data
Regression analysis is a powerful method to analyze survey data. It helps identify relationships between variables and predict outcomes. You can uncover hidden patterns and make informed decisions by utilizing regression analysis in your survey data analysis. Whether studying customer satisfaction or employee performance, regression analysis allows you to delve deeper into your data and draw meaningful conclusions.
Factor analysis is an indispensable tool when you need to analyze survey data with multiple interrelated variables. It helps simplify complex data sets by identifying underlying factors that drive responses. By employing factor analysis, you can reduce data dimensionality, enhance interpretability, and better understand survey results. This technique is particularly valuable for market research, where identifying latent customer preferences can be crucial.
Cluster analysis is an essential technique for categorizing survey respondents into meaningful groups. Whether you want to segment customers based on their preferences or employees based on their engagement levels, cluster analysis can provide valuable insights. It helps you identify common characteristics within groups and differences between them. By applying cluster analysis to your survey data, you can tailor strategies and interventions to specific segments, enhancing the effectiveness of your decision-making process.
Analyze Survey Data to Make Informed Decisions
Surveys are an effective method to understand the psyche of your customers. The feedback that you get from your customers can be used to make essential business decisions. Before you start your survey, ensure that there are clear objectives listed so that you can narrow down the questions you use in it.
While surveys carry many biases based on the design or type of questions, sending them out periodically can help you get more precise results.
While you must find the right answers, it lies in your marketing team drafting the right questions.
Once you get the survey results, the next step is to analyze the results. Sitting on rough data is not going to give you any benefit. A robust step-by-step process for analyzing your data will fetch you a lot of insight.