Future of online research

Ben Leet from ‘Instantly’ on the importance of good written, interesting surveys and rewarding incentives on quality of online surveys. http://goo.gl/LDs93n

I like his listing of questions that define sample quality:

  1. What is your recruitment methodology? Describe the different sources and blends used to build the research panels/drive the survey routers.
  2. Does your company have the ability to track respondent quality back to source and therefore actively manage those sources? How is this done?
  3. What are average drop-out rates, disqualification rates and recall rates across the panels that you manage?

Often research departments choose the online panel provider simply based on pricing and these questions are a great help to check on quality first.

But I somehow disagree with his conclusion on how online surveys will be conducted by 2020:

Considering the speed at which big data and machine learning is taking hold, I can confidently predict that we could build algorithms to replace respondents, and our research agency clients would not notice any differences in data.

There are ways that algorithms can be used to predict the future. Nearly any regression model can be used for prediction purposes.

Predictive modelling is used extensively in analytical customer relationship management to produce customer-level models that describe the likelihood that a customer will take a particular action. The actions are usually sales, marketing and customer retention related.

It is also utilised in vehicle insurance to assign risk of incidents to policy holders or in healthcare by using predictive modelling to help identify patients at high risk of readmission.

At any rate do we need broader knowledge and information on the individuals we are predicting and this is even more valid when it comes to testing of new products and trends never seen on the market before.

We also see more differentiated markets nowadays and in depths knowledge of different customer groups will help companies today and in future to boost sales and win new customers.

https://en.wikipedia.org/wiki/Predictive_modelling

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