Skip to main content

The Difficulty of Predicting Behaviour

Why Existing Market Research Methods Aren’t Good Enough

  • Chapter
  • First Online:
Applying Behavioural Science to the Private Sector
  • 395 Accesses

Abstract

Businesses want to change behaviour but conventional market research processes are often poor at predicting it. Predicting behaviour is hard and the intention–behaviour gap is significant. Conventional market research methods make it even harder because the data is often poor quality, data is confused with insight, data collection fails to focus on the factors that drive behaviour and a lot of research is done to confirm existing biases rather than to prove or refute behavioural hypotheses. Rubinstein discusses the barriers to gaining a deeper understanding of consumer behaviour and makes the case for better research tools and methods that apply the principles of behavioural science. In particular, she discusses the importance of having a good theoretical framework to allow researchers to find out what people really do, not what they say they do.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 69.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    In 2016, the global market research industry was estimated to be valued at $44bn (https://www.statista.com/statistics/242477/global-revenue-of-market-research-companies/).

References

  • Bagozzi, R. P. (2006). Explaining consumer behaviour and consumer action: From fragmentation to unity. Seoul Journal of Business, 12(2), 11–143.

    Google Scholar 

  • Castellion, G., & Markham, S. K. (2013). Perspective: New product failure rates: Influence of argumentum ad populum and self-interest. Journal of Product Innovation Management, 30(5), 976–979. https://doi.org/10.1111/j.1540-5885.2012.01009.x

    Article  Google Scholar 

  • Crawford, C. M. (1977). Marketing research and the new product failure rate. Journal of Marketing, 41(2), 51–61.

    Article  Google Scholar 

  • Janis, I. L. (1982). Groupthink: Psychological studies of policy decisions and fiascoes (6th ed.). Boston: Houghton Mifflin.

    Google Scholar 

  • Sheeran, P. (2002). Intention–behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003

    Article  Google Scholar 

  • The Psychometrics Centre, Innovia Technology, & Edelman. (2016). Trust and Predictive Technologies 2016 Report. London.

    Google Scholar 

  • West, R. (2015). The P.R.I.M.E. theory of motivation as a possible foundation for the treatment of addiction. In Addiction treatment: Science and policy for the twenty-first century. Baltimore, MD: John Hopkins Univeristy Press.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2018 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rubinstein, H. (2018). The Difficulty of Predicting Behaviour. In: Applying Behavioural Science to the Private Sector. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-01698-2_2

Download citation

Publish with us

Policies and ethics