Process VoC data for reliable insights

Business benefits

Transform data into information and knowledge.

Create a spreadsheet with its first column titled with your question.

If you have VoC data from multiple questions, start a new sheet for each.

Add VoC quotes from customer surveys, interviews, and user tests to the question column of your spreadsheet.

List common themes that you see in the VoC quotes.

Group your themes into a few categories. Add these to column titles.

For example, Price is too high, Quality is good, Improves my day.

Score each response’s relevance to each category with a 0 for irrelevant or 1 for relevant.

Tally up the score for each category column and note the highest-scoring categories.

Use coding tools when the breadth of responses becomes too complex for manual processing.

Popular natural language processing tools include:

  • Amazon Comprehend, a DYI NLP service with integrated API.
  • Textalyser, a free topic modeling option for quick responses.
  • Sprig, a survey tool that also offers NLP.
  • Chattermill and Luminoso, enterprise-level NLP tools for complex surveys.

Develop simple statements that summarize the highest-scoring categories of themes.

For example, if the highest scoring categories are Price is too high and Quality is good, a statement might be Customers don’t like the high price, but find the quality worthwhile.

Use your statements as hypotheses for building value propositions and running marketing experiments to improve your brand’s digital experience.

Last edited by @hesh_fekry 2023-11-14T10:08:50Z