Survey Analytics
Survey Data Analysis demands high level of expertise and years of industry exposure to tackle the practical problems that emerge from sensitivity of data collected through primary research. Our extensive experience in data processing and ability to analyze them professionally make us capable of providing our clients the apt insight of the market. We deal with the most critical projects that demands data cleaning and tabulation using tools such as R, SPSS, Quantum, WinCross, etc.
Our major areas of expertise are as follows:
- Proficiency in summarizing survey data
- Ability to create clear and informative visualizations
- Strong knowledge of hypothesis testing to determine the statistical significance of survey findings.
- Expertise in using statistical tests like t-tests, chi-square tests, ANOVA, and regression analysis for inference and prediction
- Proficiency in analyzing and extracting insights from open-ended survey responses
- Capability to create comprehensive reports and presentations that effectively convey survey findings
- Skill in creating compelling data visualizations, charts, and graphs
In terms of our experience in survey reporting, we typically use MS-PPT on client specified template. We also have capability of using, Google Studio, Tableau, animation layout, AI, visualization tool and live presentation, both manual and automated formats.
Techniques Used
- ANOVA/ANCOVA
- Association Analysis
- Canonical Correlation
- CHAID
- Cluster Analysis
- Conjoint Analysis
- Cross-Tabulation
- Discriminant Analysis
- Factor Analysis
- Linear Regression
- MANOVA/MANCOVA
- Markov Chains
- Multidimensional Scaling
- Neural Nets
- Non linear Regression
- Structural Equation Modeling
- Time series Analysis
FAQ on Survey Analytics
Categorical data is a popular route for survey questions. This is the easiest type of data to analyze as you’re limited to calculating the share of responses in each category. Collect, count, divide are the main steps while analyzing any data.
To describe the characteristics of a large population surveys are useful. There is no other research method that can provide this broad capability, which ensures one more accurate sample to gather targeted results in which to draw conclusions and make important decisions.
Data analysis has two major methods including qualitative research and quantitative research. Each of the methods has their own techniques. Interviews and observations are forms of qualitative research, while experiments and surveys are quantitative research.
Report writing is one of the most important components in the survey research cycle and the aim of the written report is to communicate the survey findings. Report provides a formal record of the survey research, and also provides a foundation for future research efforts.