Analysing Social Value Data in Surveys

Posted on the 19th June 2019

Online surveys are accessible, easy to get along with, and familiar to most people – regardless of their digital or social value background. More on the pros and cons of using surveys here. They can be tailored with your key objectives in mind, and are capable of capturing vast data sets, as well as the granular insights acquired through qualitative research. This makes them an excellent solution, and a worthwhile consideration when deciding how to most effectively accrue social value data for social value/CSR reports

This is what you need to know to analyse social value data through surveys.

Types of Analysis

Qualitative

Wordclouds – are a quick, accessible and stakeholder-friendly way of presenting top-level qualitative data. They allow you to identify the language and sentiments used to express your user’s experiences.  They are useful as they enable you to reviews insights without having the drill too deeply into the data.

Semantic analysis and coding – involves a more in-depth method of analysis. It involves, either manually or via automated software, assessing the patterns that exist within a qualitative dataset. Words or phrases that meet certain criteria (such as happy or sad, or about a particular topic) are coded, and assessed together or within the context in which they’re written.

Quantitative

Data visualisations Boards and c-suite executives gravitate towards this method of conveying data. While bar graphs are nothing new, having both qualitative and quantitative insights in one place makes it easy to marry data sets with one another, and to ‘tell the story’ of your impact.

Pie charts – shows data according to a series of ‘multiple choice’ answers, where this data can be calculated as a percentage.

Line charts – are best used to show data grouped by date, shown over time, or to show data grouped according to a series of ‘multiple choice’ answers.

Cross-tabs – are a helpful – but under-used – method of highlighting the relationship between different variables in a dataset. The method helps to uncover insights which are provided in an interface that clearly displays pertinent data in a matrix. More of this in an upcoming article!

Longitudinal – (aka ‘distance travelled’). This approach enables you to evaluable the impact of an intervention on an individual’s physical or mental wellbeing at significant points in time.

In-depth statistical analysis of large datasets – If you are able to send your social value survey to a large enough group of people – in the hundreds or thousands – then it might be possible to conduct an in-depth statistical analysis of answers. This approach would allow you to understand, to a degree of statistical significance, the relationship between variables. For example, whether someone’s age, or gender, or location has an effect on the degree of social value generated as a result of the work you do.

Things to consider

1) The context of your survey is always important when analysing the data. This involves considering:

  • The purpose of the survey
  • Who was surveyed
  • Why it’s been created
  • Who’s completed it
  • When it was completed
  • Where it was completed

This is largely due to the risk of ‘response bias’ – arguably the most significant limitation to surveys validity. Response bias takes into consideration multiple variables that influence and manipulate the authenticity of responses – thus skewing your data. As an example, a patient completing a survey immediately before surgery is unlikely to give a true reflection of their stay in hospital.

 2. When conducting surveys, remember to take into account the sampling method.

The number of respondents is relevant as surveys with low response rates shouldn’t be ‘generalised’ too much, as they may not be representative of the larger population. Likewise, if the sampling method is not valid and not established, then even a large dataset may not be representative of the audience you claim to benefit.

Final thoughts

There are various ways to analyse social value data, making them a significant part of your reporting arsenal. While the analyses of social value data may seem overwhelming at first, digitising this process through a tool such as IMPACT can make it quicker and simpler.

Identify what options are most suitable for your organisation and be consistent with your approach. As always, don’t hesitate to give us a call should you need any support! Happy reporting!

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