Amoo, NA

Meaton, J

Robinson-Maynard, A

Leeds Beckett Repository

Page 192 of 312  Establishing an Evaluation Template and Grid   Audrey Robinson-Maynard38, Dr. Julia Meaton & Dr. Nii Amoo   University of Huddersfield Business School  United Kingdom                                                                                              38 Audrey Robinson-Maynard is a former Divisional Manager in Local Government, Social Services Children Assessment Services and budget holder for that service.  She holds various qualifications in Social Work and Management.  Audrey gained a BA from the University of Huddersfield and her MSc from London Guildhall University.  She is at present completing a PhD in Social Marketing at the University of Huddersfield.   Audrey has been and still is actively involved in setting up and the progressing of Community Organisations, from hostels for homeless young people to after school clubs.  She has been involved in many community research projects and has published work relating to Child Care and the law.            Page 193 of 312  Introduction The concept of social marketing (SM) is still a developing discipline and still without a universal definition.  It is subject to the interpretation of its global users, as they implement intensive and extended programmes ranging from ‘healthy eating’ to ‘clean air’.  This kaleidoscope of applications has meant that few campaigns are the same, many being shaped by the varied interpretations of SM.  While this ambiguity allows a flexibility of applications, it also makes it difficult for marketers to identify contributing key criteria for successful SM campaigns.  Several researches and practitioners have previously identified benchmark criteria for the streamlining of social marketing exercises, including Andreasen’s (1995, 2002), French & Blair- Stevens (2005, 2007) and Lefebver (2006).  However, these criteria have not been fully analysed regarding their individual contribution to the success or failure of SM campaigns or even how well they work together.  This paper attempts to address this gap and presents an ‘Evaluation Template and Grid’ (ETG) that identify these key criteria that have been statistically proven to contribute to the success of SM campaigns.  This paper further explains how and why ETG was developed and discusses the appraisal procedures that can be used to guide the development of successful social marketing campaigns.   Theoretical Procedure  ETG was developed after an in-depth study of 12 SM case studies that represented campaigns from around the world (see appendix A).  They were selected because they generally complied with Andreasen’s (2002) benchmarks, were peer reviewed, dealt with diverse problems of mixed target groups and were all in the public domain, authored by various commentators in the field of SM such as, Forster et al. 1998; Hastings, 2007; Quinn et al. 2007 and Sun et al. 2007.  For the profile of these companies see appendix B.   Evaluation Procedure and Techniques The different aspects in each of the 12 case studies were investigated and their major variables appraised.  Two  objectives became fundamental to the research, (a) ‘to identify variables evident in successful SM campaigns’ and (b) ‘to evaluate relationship building with target audiences and the effect these have in advancing and sustaining exchange behaviours.’  Together these objectives lead the researcher to ask the broader research question - “are there other variables that would define more precisely SM processes to earn them the true title of SM”?    Through a qualitative data analysis of these 12 case studies factors hypothesised to be of key importance for success were identified, resulting in 19 bench marketing criteria (see appendix C).  These were then tested by quantitative survey of the study’s research population of one hundred global cases (see appendix D for countries).  Using both qualitative and quantitative methods helped to identify patterns and relationships in the data allowing for a more comprehensive understanding of the case studies and their variables (Creswell, 2007; Hennink, Hunter & Batley, 2011; Silverman, 2006 and Stake, 1995).   A test of significance of the variables provided an assurance of reliability and validity.   Results – SPSS (PASW) 18.0. Using ‘success of campaign’ as the dependent variable (with its three categories) and 19 benchmarks as independent variables, a cross tabulation and Chi-Square Tests were applied.  Some benchmarks showed greater statistical significance as key determinants in campaign success than others.  Further analyses, using other dependent variables such as ‘finances’ and ‘length of campaigns’, subject to ‘2 - tailed’ and ‘1 - tailed’ tests to ascertain any refinement in their statistical significance (Sweet & Grace-Martin, 2008).  The analyses found that of the Page 194 of 312  19 benchmarks, five were of statistical significance in campaign success these were: whether the campaign was piloted, whether it showed clear benefits for the target audiences, how well marketers understood the background of the target audience and their ability to understand and comply with the marketing message –understanding concept, whether the campaign had long term sustainable support and whether the marketers had covered a wide range of eventualities within the marketing remit – absence of biases and flaws.    Most important of these was the need for marketers to show their target audiences that there were ‘clear benefits’ to be gained from behavioural changes, together with ongoing support systems to combat competitions.  Understanding the context of the target audience’s problems helped in the planning and execution of campaign strategies and contributed to the relationship building between the target audience and the marketers and hence the sustainability of behaviour changes.  Campaigns that also showed versatility and creativity in their marketing strategies were more likely to be successful.    During further data exploration it was apparent that although five benchmarks were clearly the most important, the 19 benchmarks tended to work in harmony with each other.  Thus, there is a strong argument for all of them to be used as a package so as to optimise campaign development, sustainability and success.  All 19 benchmarks are therefore included in the proposed ETG.  Appendix C gives an example of how one case study is assessed using the benchmarks from the Evaluation Template and Grid.  Conclusion  The research produced some interesting findings that will enrich our knowledge-base of what determines successful SM campaigns.  This research highlights the use and value of an evaluation grid in the assessment and investigative processes dealing with the diversity of behaviours in social marketing campaigns.  It suggests that these benchmarks may be good predictors of success but also emphasises the complexity and kaleidoscopic nature of SM.   This research represents the first stage of the identification and testing of the Evaluation Template and Grid (ETG).  It is acknowledged that the analysis has so far only been conducted on a limited number of case studies and that in order to further refine it and to ensure it is robust, it needs to be more widely tested.  However, this initial step is important as it clearly demonstrates that SM can benefit from the criteria of the ETG methodology.  The research represents a significant step forward in understanding the essential components of successful SM campaigns.   It’s difficult to change people’s behaviour and acquire an effective and long lasting change of desired behaviours.  The ETG could help to define a more efficient marketing mix in a climate of budget constraints and encouraging a better quality of interaction between the marketer and the target audience.  The research is underpinned by past works of great marketers (Andreasen, 1995; Dann, 2010; Donovan & Henley, 2003; Kotler & Zaltman, 1971 and Kotler, Roberto & Lee, 2002) and should therefore be considered as a valuable addition to the planning, implementation and evaluation of any social marketing campaign.          Page 195 of 312  References Andreasen, A.R.,(1995) ‘Marketing Social Change’, Jossey-Bass, San Francisco.  Andreasen, A. R. , (2002) ‘Marketing Social Marketing in the Social Change Marketplace’, Journal of Public Policy and Marketing, vol. 21 (1). p3-13.  Creswell, John W., (2007) ‘Designing and Conducting Mixed Methods Research’, Sage Publications, London.  Dann, S. ,(2010) ‘Redefining Social Marketing with Contemporary Commercial Marketing Definitions’,  Jopurnal of Business Research, vol. 63, no. 2, p144 – 153.  Donovan, Robert J. and Henley, Nadine, (2003) ‘Social Marketing Principles and Practice’, IP Communications, Melbourne.  French, J. and Blair – Stevens, C. (2005) ‘Social Marketing Pocket Guide’ 1st Ed., National Social Marketing Centre for Excellence, Department of Health, London.  French, J. and Blair-Stevens, C. (2007) ‘Big Pocket Guide Social Marketing’ 2nd Ed. , National Social Marketing Centre,  Department of Health, London.   Forster, Jean L.; Murray, David M.; Wolfson, Mark; Blaine, Therese M.; Wagenaar, Alexander C. and Hennrikus, Deborah J., (1998) ‘The Effectives of Community Policies to Reduce Youth Access to Tobacco’, American Journal of Public Health, vol.88, no.8, p1193 – 1198.  Hasting, G. (2007) ‘Social Marketing: Why should the Devil have all the best tunes? Elsevier Ltd., Oxford.    Hennink, Monoque; Hunter, Inge; Batley, Ajay, (2011) ‘Qualitative Research Methods’ Sage Publications Ltd., London.  Kotler, P. and Zaltman, G. (1971) ‘Social Marketing: An Approach to planned Social Change’, Journal of Marketing, vol. 35 (July) p 3-12.  Kotler, P.; Roberto, N. and Lee, N. (2002) ‘Social Marketing: Improving the Quality of Life’ 2nd Ed., Sage Publications Ltd. London.   Lefebvre, R. Craig, (2006) ‘On Social Marketing and Social Change: When is it Social Marketing?’ http://socialmarketing.blogs.com/r_craiig_lefebvres_social/2006/06/when_is_it_soci.h...   01/02/2012.  Quinn, P.; Bell-Ellison, B.A.; Loomis, W. and Tucci, M., (2007) ‘Adolescent perceptions of violence:’ Journal of the Royal Institute of Public Health, vol.121, p357 -366.   SPSS – Statistical Package for Social Scientists, SPSS, PASW Statistics, version 18.0 for Windows. 2010.    

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