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Consumer behaviour and sales forecast accuracy: what’s going on and how should revenue managers respond?

Consumer behaviour and sales forecast accuracy: what’s going on and how should revenue managers respond?
Consumer behaviour and sales forecast accuracy: what’s going on and how should revenue managers respond?
Since the Lehman’s crash in 2008 anecdotal evidence from the Revenue Management Society in the UK suggests that consumer buying behaviour has changed significantly. Consumers are buying different things, at different times and through different channels. As a result forecast accuracy is poor and many companies are turning off the automated forecasting systems and relying on analysts to predict booking behaviour. Historical data alone cannot be used to predict future sales in times of flux such as these and drawing together a wider range of internal and external data would help improve forecast accuracy. The impact on Revenue Managers varies widely. Where sales forecasts are important, adjustments to Revenue Management (RM) System outputs are needed to retain credibility and stop systems ‘panicking’. When customer behaviour is volatile and poorly understood, there may be a need for novel selling mechanisms such as auctions, or online experimentation to probe the market response
1476-6930
374-376
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Rowley, Ian T.
8b76d103-247b-4009-9ac9-b1508b271614
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Rowley, Ian T.
8b76d103-247b-4009-9ac9-b1508b271614

Currie, Christine S.M. and Rowley, Ian T. (2010) Consumer behaviour and sales forecast accuracy: what’s going on and how should revenue managers respond? Journal of Revenue and Pricing Management, 9, 374-376. (doi:10.1057/rpm.2010.22).

Record type: Article

Abstract

Since the Lehman’s crash in 2008 anecdotal evidence from the Revenue Management Society in the UK suggests that consumer buying behaviour has changed significantly. Consumers are buying different things, at different times and through different channels. As a result forecast accuracy is poor and many companies are turning off the automated forecasting systems and relying on analysts to predict booking behaviour. Historical data alone cannot be used to predict future sales in times of flux such as these and drawing together a wider range of internal and external data would help improve forecast accuracy. The impact on Revenue Managers varies widely. Where sales forecasts are important, adjustments to Revenue Management (RM) System outputs are needed to retain credibility and stop systems ‘panicking’. When customer behaviour is volatile and poorly understood, there may be a need for novel selling mechanisms such as auctions, or online experimentation to probe the market response

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Published date: August 2010
Organisations: Operational Research

Identifiers

Local EPrints ID: 181399
URI: http://eprints.soton.ac.uk/id/eprint/181399
ISSN: 1476-6930
PURE UUID: a13157d2-2c3d-43f2-b5e1-95972f35f060
ORCID for Christine S.M. Currie: ORCID iD orcid.org/0000-0002-7016-3652

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Date deposited: 19 Apr 2011 08:17
Last modified: 15 Mar 2024 03:15

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Author: Ian T. Rowley

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