Effectively utilize SurveyCake’s survey analysis features to create greater value for each response data.
After collecting survey data, the next step is to break down the vast amount of information and conduct survey analysis based on the survey objectives. The SurveyCake dashboard not only visualizes the data, allowing you to analyze results at a glance through statistical charts but also provides diverse survey analysis methods. You can utilize cross tabulation and filter to easily break down survey data.
With SurveyCake’s survey analysis features, you can dig into the analysis of data, identify the audience that suits your brand, and understand respondent profiles and consumer behavior. Whether it’s in formulating brand marketing strategies or defining product directions and optimizing service processes, SurveyCake’s survey analysis features make these tasks much easier!
Now, we will guide you to apply SurveyCake’s analysis features to your surveys:
- Survey Analysis Feature: Visualized Statistical Charts
- Survey Analysis Export: Excel, SPSS Detailed Export
- Survey Statistics Essential: Calculation Mode
- Survey Analysis Essential: Filter
- Survey Analysis Essential: Cross Tabulation
- Survey Statistics Essential: Combined Analysis
- Survey Segmentation Essential: Label
- Survey Analysis Tracking: Google Analytics Tracking Code
-
Chart Report: Visualize survey analysis.
In the past, when collecting surveys, you may have encountered issues with a large amount of data, requiring manual formula calculations or individual statistics. However, in SurveyCake’s backend system, it directly converts respondents’ answers into statistical data and visualizes the data. It generates corresponding analysis charts for different question types, providing a clear overview of the survey analysis results.
If you need to consolidate the data into a report, you can also directly convert the “Chart Report” into “Slideshow.” This allows you to present individual charts for each question, and you can either download them in PDF format or copy and paste the charts into presentations. This feature saves you time on statistical calculations and chart creation!
-
Export to Excel, SPSS: Simplify survey analysis and statistics.
In addition to Chart Report, analyzing respondent details is also a crucial aspect of survey analysis. Utilizing SurveyCake’s “Data Report”, you can browse data, specify sorting, delete information, and transform the viewing experience. If you prefer to keep a hard copy of the data, you can directly download an Excel file to print and backup the information.
For those looking to apply further analysis to survey data, you can download an SPSS file compatible with most statistical analysis software. This allows you to import detailed data into specialized software for in-depth analysis.
Of course, you also have the option to directly link your survey results with Google Sheets. This automatically imports all survey data into Google Sheets, making it convenient for colleagues within the company to collaborate, edit, and review collectively.
To learn more about integrating SurveyCake responses to Google Spreadsheet, you can refer to:
-
Calculation Mode: Automatically sum numerical data.
SurveyCake provides a “Calculation Mode” feature, allowing you to easily sum up numerical data in your survey, such as the number of people, scores, amounts, quantities, etc., without manual calculations.
Survey creators can set up calculation logic based on different scenarios, adding numerical values to question options or responses. For example, if you want to design a quiz survey and automatically calculate the score for each survey, you can enable “Calculation Mode,” set up “Variables” and “Logic,” choose the correct answer for each question, and specify how many points should be awarded for each correct response.
Left side is for variable settings and the right side is for logic settings.
- Variable settings: “Variable Name” represents the name of the calculation result, making it easy to identify when designing the survey. “Default Value” indicates the starting numerical value for the calculation (If set to 0, it will start calculating from zero).
- Logic settings: Insert the question and select the correct answer, then set the score for each correct response.
The scores calculated using “Calculation Mode” will be displayed in the “Chart Report” on the “Survey Results Page.” The system will automatically calculate various values such as ‘Mode,’ ‘Average,’ ‘Sum,’ etc., making it more convenient for teachers to analyze test scores!
You can view various statistical values in the backend system.
-
Filter: Easily break down extensive data for advantageous survey analysis.
Through “’Filter”, analyzing the behavior of specific demographics can reveal insights hidden beneath the data, assisting in future marketing strategy planning or product optimization.
For example, after receiving customer feedback from a “Product Satisfaction Survey”, in addition to the two indicators “Satisfied” and “Dissatisfied”, you can narrow down the scope and set specific conditions for analysis, such as “Female” or “Technology Industry & Dissatisfied with the Product”, etc.
Single condition: You can filter based on “Gender”, comparing differences between variables, and understanding how “Male” and “Female” perspectives on the product differ. When you set the “Female” filter, the backend will only display data related to “Female”, allowing for a quick analysis of the behavior of the female demographic.
If a majority of “Female” respondents select “Dissatisfied”, as a brand, you can consider whether the target audience for this product should be shifted towards males. Alternatively, it could indicate that the product’s features are not as practical for females, leading to a less favorable user experience for female consumers. This insight can guide the planning of future product optimization strategies.
Multiple conditions: You can also set two or more conditions for filtering. For example, if your company is launching a new product and the target audience is in the technology industry, with a focus on this group’s responses compared to other industries, the product or marketing department can use “’Filter Combinations” to narrow down customers who are both in the “Technology Industry” and have selected “Satisfied” with the product. With this filtered group, you can then adjust marketing strategies or optimize product performance based on their feedback.
-
Cross Tabulation: Avoid survey analysis averaging bias.
In data analysis, a crucial aspect is Cross Tabulation which involves using comparison rules to analyze the relationship between two variables. The results are presented in the form of a Cross Tabulation Chart allowing you to clearly observe the response patterns of the two variables after comparison.
For example, while conducting a “Product Satisfaction Survey,” overall statistics may show that the majority of customers are “Satisfied” with the product experience. However, upon deeper analysis, the situation might not be as straightforward as it appears on the surface. Are there variations in satisfaction levels across different industry demographics? Or perhaps, is there a difference in satisfaction levels among various age groups?
If you only focus on a specific value or indicator, you might unintentionally dilute the underlying opinions, affecting subsequent product marketing strategies or improvement directions. To avoid this situation, you can effectively use the “Cross Tabulation” feature by setting “Base Questions” and “Comparative Questions” to present the interactive relationships between options in charts and tables.
For example, if you perform a cross-analysis on “Occupation” and “Satisfaction with User Experience,” you may notice that the majority of respondents in the “Technology Industry” and “Students” categories tend to select “Dissatisfied ~ Very Dissatisfied.” In such a case, the brand can consider whether the product is not suitable for these two occupational groups or if adjustments to the product need to be made based on the feedback from these target demographics.
-
Combined analysis : Consolidate parent and child surveys for extremely convenient survey analysis.
In the past, creating multiple surveys of the same type required copying and recreating survey questions, and when consolidating data, you had to export data from each survey for analysis, making the process inconvenient and time-consuming.
However, with the “Subsurvey” feature, you only need to create a master survey. You can quickly replicate multiple subsurveys and distribute them to different target audiences. Finally, you can merge and analyze the data directly in the backend system, significantly reducing the time and effort involved in survey creation and management.
For example, a chain of fitness centers may want to manage the reservation time slots for each branch to control the flow of people reserving the gym. The business only needs to design a “parent survey” and generate “ subsurveys” for each branch using the master survey. This makes it easy to maintain consistent survey content across all branches, and in the end, the results from each branch’s survey can be merged for analysis.
In this way, each branch can easily monitor the number of reservations for each time slot, facilitating the management of capacity limits. In the event of reaching full capacity, the system can immediately notify customers to consider other branches or time slots.
-
Label: A helpful tool for survey analysis and automated segmentation.
In addition to collecting feedback through surveys, SurveyCake’s backend system also provides a “Label” feature. This feature helps systematically categorize respondents, bringing order to the survey data. By automatically categorizing respondents who share the “same attributes,” you can effectively organize survey data, assisting businesses in gaining insights into consumer profiles. This, in turn, allows for more precise targeted marketing or advertising strategies in the future!
For example, in the aforementioned chain of fitness centers’ reservation survey, you can set “Labels”’ within each branch option to categorize respondents into regions such as North, Central, and South based on their responses. In the future, if the fitness center adds new classes or time slots, they can send Line messages or EDMs according to the categorized lists previously collected. This ensures that customers receive push notifications that align with their specific needs.
-
Google Analytics Tracking Code: Grasp respondent profiles for more precise survey analysis.
In addition to the “Label”, you can also utilize Google Analytics (GA) to understand the profiles of survey respondents. Embedding “GA tracking codes” in surveys allows for the classification of audiences and the creation of remarketing lists. When businesses implement brand advertising, EDMs, and other remarketing strategies, these insights can effectively enhance conversion rates.
You can use Google Analytics to organize the collected survey data into “target audience” lists based on different variables such as website dwell time, specific page views, demographics, etc. Import the remarketing lists set up in GA into your Google Ads account, enabling more precise advertising targeting. This way, you can reach users who have a genuine interest in your content, ultimately boosting conversion rates.
Discover your brand audience through survey analysis!
Make the most of SurveyCake’s survey analysis feature to break down extensive data, gain deep insights into consumers, identify your brand audience, and formulate the most comprehensive marketing strategies!
Click here to sign up for FREE!
For further inquiries, feel free to contact us anytime!
SurveyCake is a cloud-based survey platform developed in Taiwan. Stay tuned to our blog for the latest news and survey-related content. You are also welcome to share our posts with your friends by crediting us. If you have any questions or further inquiries, you can contact us through support@surveycake.com.
