Crowdsourcing vs. Surveys: Insight Beyond Forms and Votes

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The relatively new data collection model of crowdsourcing is becoming increasingly prevalent in modern marketing strategy. Those familiar with survey methodology are most likely wondering when to utilize crowdsourcing vs. surveys, and how to interpret the resulting data. And although they have much in common (for example, both data collection systems can be set up quickly, and lend themselves to large, geographically-varied samples), the strategy for a particular campaign should always be determined by looking at what data is being collected and what the data will be used for.

Survey methodology creates a straight shot from data gathering to analysis:

  • When a company or organization is looking for answers to specific questions, a survey campaign may prove to be the answer.
  • A survey allows administrators control over the direction of feedback acquired from participants. In this way, a large quantity of data may be obtained on the pre-determined subjects that the business or organization are interested in.
  • Survey data is reliably processed through statistical analysis. Once gathered, the data can be directly turned into evidential support of a cause or action.

Crowdsourcing takes a different approach. With crowdsourcing, the concept is to look mainly to the participants for questions and potentially also the answers.

  • The crowd will lead the discussion to what matters most to them. This introduces topics that would not have been unearthed using other methods.
  • Participants may choose to simply vote for and against ideas posted by others. Or, they can go in-depth with comments. This open-ended tactic yields richer qualitative data.
  • The crowd presents their complaints and suggestions directly to users, who are potential and actual customers. This continuous cycle of suggest/comment/vote broadens the scope of the data being obtained. Within one crowdsourcing campaign, numerous idea lifecycles play out.

The linear results of survey-sourced data are readily processed through traditional statistical analysis. Once the data is collected, it can be plugged into different analytical frameworks to answer an array of business questions. The results are reliable and the answers are entirely comparable.

Crowdsourced data is richer and therefore not always as straightforward in the analysis phase. The sophisticated qualitative data oftentimes requires custom analysis if you’re going to learn anything beyond what idea was most popular. Participants provide ideas, questions, and broad subjects that all have the potential to yield large effects. The challenge is to sift through this bounty of information for the ideas that have the most potential – and the most business value.

On Tuesday April 29th, Suzan Briganti, IdeaScale’s SVP of strategy, will present a complimentary webinar on the process of analyzing the results of a crowdsourced campaign. Get in touch with IdeaScale to learn more about “How to Leverage Collective Wisdom: Getting Beyond the Top-Voted Idea” and register for this complimentary webinar today.

Jessica Day is a marketing and technology writer and editor for IdeaScale (, a leading innovation software solution for idea management. She received her Masters in Writing from the University of Washington. Day also blogs about crowd-based innovation and idea management solutions at

About Jessica Day

Jessica Day manages marketing and communications for IdeaScale. She has been working in the marketing industry for more than five years with a variety of companies including digital agencies like Ascentium and Knee Deep Marketing and contracting for larger companies like Microsoft.

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