Process Evaluation of the ‘No Money No Time’ Healthy Eating Website Promoted Using Social Marketing Principles. A Case Study
2. Materials and Methods
2.1. Ethical Considerations
2.2. Development of No Money No Time (NMNT)
- Personal assessment of diet quality with feedback: the site includes ‘call to actions’ to encourage users to complete the embedded Healthy Eating Quiz (HEQ); a brief, validated tool to assess diet quality [29,30,31,32,33,34]. Once completed, the user obtains a diet quality feedback report that compares individual score with population normative data (Supplementary Material Figure S2).
- Fast, inexpensive recipes for healthy eating: The site also includes over 150 fast, inexpensive and healthy recipes, with one new recipe added each week, that can be filtered based on potential barriers that were identified as part of the scoping work. Filters include ownership of specific kitchen equipment, nutrition motivators, meal type, dietary intolerances, number of serves, cost and dietary preferences (Supplementary Material Figure S3).
- Nutrition ‘hacks, myths and FAQ’ articles: The site has over 100 articles with one new article added each week, that translates nutrition research into lay language to address common dietary misconceptions. Blog topics are informed from common nutrition topics and from a data bank of questions from our Massive Online Open Course (MOOC) “The Science of Weight Loss—Dispelling Diet Myths” from over 57,000 individuals from >180 countries.
- Personal dashboard: Users are encouraged to sign-up to create a personalised dashboard which enables them to set SMART (Specific, Measureable, Attainable, Realistic and Time—bound) goals relating to their current HEQ diet quality score. The personal dashboard also enables users to store past HEQ results, save favourite recipes and blog articles, and receive recipes based on individual HEQ scores (e.g., if a user scores low in the vegetable sub-group score, then recipes with higher vegetable content will appear in dashboard) (Supplementary Material Figure S4).
- Automated email and social media presence: Those who complete the HEQ and sign-up to an account also receive regular communication via email (approx. 1–2 per month) in order to alert them to new content, recipes and diet improvement hacks on the website. This information is also disseminated on the NMNT social media channels (Twitter, Facebook and Instagram) with approx. 1–2 posts per week.
2.3. Development and Implementation Plan for the Social Marketing Strategy to Maximise NMNT User Acquistion and Engagement
- Implement search Engine Optimisation (SEO) audit: defined as the process of maximising traffic to a website so that it appears high on the search engine results page and is accomplished through use of keywords and best-practice website design . An SEO audit was conducted pre and post launch to increase website visibility on search engines such as Google.
- Content strategy: regular, high quality content that was optimised for SEO was added to the site (target of one new content piece added each week).
- Backlink strategy: defined as another website linking to NMNT website . Existing, reputable sites (i.e., Queensland Health) were contacted to enquire about linking to NMNT website.
- Regular promotional activities conducted: including engaging with media (national and local TV, radio, print) and podcasts to ensure the evidence-based approach to this area of nutrition with links to NMNT website. These activities were facilitated by The University of Newcastle’s communications team preparing a media release in-kind.
2.4. Process Evaluation of the NMNT Social Marketing Strategy Over a 12 Month Period
2.4.2. Data Collection
- Bounce rate (%), defined as the percentage of immediate abandonment or single page visits during a session . A low bounce rate indicates that site visitors explore additional content beyond the home page and click deeper into the site and is therefore indicative of high overall engagement [43,44].
- Mean number of sessions per user. A session is defined as a group of user website interactions that take place within a given period (expires after 30-min of inactivity or at midnight). Usage data (page views, events, social interactions) is all data associated with a session. Mean number of sessions per user is calculated as total sessions divided by total number of users. A higher number of sessions per user is indicative of greater engagement .
- Goal conversion rate (n and % of session): measures the proportion of sessions that accomplished a pre-defined goal. For NMNT, the goal was set as clicking on a call-to-action button to start the HEQ diet quality survey. Users were required to complete the HEQ to sign-up to an account and access more resources than those who do not. Therefore, starting the HEQ indicated higher engagement.
Potential Mediators of Engagement
- User acquisition channel: Channels used to access NMNT were categorised into; organic search (e.g., entry to site via search engine such as Google), direct source (e.g., typing the URL of website directly into a browser) referrals via another website, referral via social media and referral via email.
- Internet browser
- Device used to access the website:
2.4.3. Data Analysis
3.1. Implementation of the Social Marketing Strategy
3.2. Mechanisms of Impact
3.2.1. User Acquisition
3.2.2. User Engagement
Potential Mediator—User Acquisition Channel
Potential Mediators—Internet Browser and Devices
3.3. Contextual Factors
4.1. User Demographics
4.2. Effectiveness of Marketing Strategies
4.3. User Engagement
4.4. Website Improvement
4.5. Strengths and Limitations
- Utilising social marketing frameworks (e.g., Andreasen’s six benchmark criteria ) to guide an overall marketing strategy.
- Seek advice from cross-disciplinary experts (e.g., human–computer interaction, digital marketing and design)
- Undertake extensive co-design with the target audience
- Drive organic traffic to the site as a sustainable way of obtaining users/participants long term.
- Continually monitor and evaluate website metrics using Google Analytics to identify issues with reach or engagement and act accordingly.
- If using social media related to the website, consider young adults’ social media use patterns and use relevant techniques to enhance engagement (e.g., different types of messaging or gamification).
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
- Murray, C.J.; Aravkin, A.Y.; Zheng, P.; Abbafati, C.; Abbas, K.M.; Abbasi-Kangevari, M.; Abd-Allah, F.; Abdelalim, A.; Abdollahi, M.; Abdollahpour, I. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396, 1223–1249. [Google Scholar] [CrossRef]
- Wang, X.; Ouyang, Y.; Liu, J.; Zhu, M.; Zhao, G.; Bao, W.; Hu, F.B. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: Systematic review and dose-response meta-analysis of prospective cohort studies. BMJ 2014, 349, g4490. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Aune, D.; Giovannucci, E.; Boffetta, P.; Fadnes, L.T.; Keum, N.; Norat, T.; Greenwood, D.C.; Riboli, E.; Vatten, L.J.; Tonstad, S. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. Int. J. Epidemiol. 2017, 46, 1029–1056. [Google Scholar] [CrossRef] [PubMed]
- Imamura, F.; Micha, R.; Khatibzadeh, S.; Fahimi, S.; Shi, P.; Powles, J.; Mozaffarian, D.; on behalf of the Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). Dietary quality among men and women in 187 countries in 1990 and 2010: A systematic assessment. Lancet Glob. Health 2015, 3, e132–e142. [Google Scholar] [CrossRef][Green Version]
- Winpenny, E.M.; Penney, T.L.; Corder, K.; White, M.; van Sluijs, E.M. Change in diet in the period from adolescence to early adulthood: A systematic scoping review of longitudinal studies. Int. J. Behav. Nutr. Phys. Act. 2017, 14, 60. [Google Scholar] [CrossRef]
- Ashton, L.M.; Sharkey, T.; Whatnall, M.C.; Williams, R.L.; Bezzina, A.; Aguiar, E.J.; Collins, C.E.; Hutchesson, M.J. Effectiveness of interventions and behaviour change techniques for improving dietary intake in young adults: A systematic review and meta-analysis of RCTs. Nutrients 2019, 11, 825. [Google Scholar] [CrossRef][Green Version]
- Fjeldsoe, B.; Neuhaus, M.; Winkler, E.; Eakin, E. Systematic review of maintenance of behavior change following physical activity and dietary interventions. Health Psychol. 2011, 30, 99. [Google Scholar] [CrossRef]
- Morris, Z.S.; Wooding, S.; Grant, J. The answer is 17 years, what is the question: Understanding time lags in translational research. J. R. Soc. Med. 2011, 104, 510–520. [Google Scholar] [CrossRef]
- Laur, C.; Ball, L.; Keller, H.; Ivers, N. Building on what we know: Moving beyond effectiveness to consider how to implement, sustain and spread successful health interventions. BMJ Nutr. Prev. Health 2020, 3, 123–125. [Google Scholar] [CrossRef]
- Poobalan, A.; Aucott, L. Obesity among young adults in developing countries: A systematic overview. Curr. Obes. Rep. 2016, 5, 2–13. [Google Scholar] [CrossRef][Green Version]
- Bower, P.; Brueton, V.; Gamble, C.; Treweek, S.; Smith, C.T.; Young, B.; Williamson, P. Interventions to improve recruitment and retention in clinical trials: A survey and workshop to assess current practice and future priorities. Trials 2014, 15, 1–9. [Google Scholar] [CrossRef] [PubMed]
- Bennett, G.G.; Glasgow, R.E. The delivery of public health interventions via the Internet: Actualizing their potential. Annu. Rev. Public Health 2009, 30, 273–292. [Google Scholar] [CrossRef] [PubMed]
- Michie, S.; Yardley, L.; West, R.; Patrick, K.; Greaves, F. Developing and evaluating digital interventions to promote behavior change in health and health care: Recommendations resulting from an international workshop. J. Med. Internet Res. 2017, 19, e232. [Google Scholar] [CrossRef] [PubMed]
- Young, C.; Campolonghi, S.; Ponsonby, S.; Dawson, S.L.; O’Neil, A.; Kay-Lambkin, F.; McNaughton, S.A.; Berk, M.; Jacka, F.N. Supporting engagement, adherence, and behavior change in online dietary interventions. J. Nutr. Educ. Behav. 2019, 51, 719–739. [Google Scholar] [CrossRef] [PubMed]
- Evans, W.D. How social marketing works in health care. BMJ 2006, 332, 1207–1210. [Google Scholar] [CrossRef] [PubMed][Green Version]
- International Social Marketing Association; European Social Marketing Association; Australian Association of Social Marketing. The iSMA, ESMA and AASM Consensus Definition of Social Marketing. Available online: https://www.i-socialmarketing.org/assets/social_marketing_definition.pdf (accessed on 15 January 2021).
- Andreasen, A.R. Marketing social marketing in the social change marketplace. J. Public Policy Mark. 2002, 21, 3–13. [Google Scholar] [CrossRef]
- Carins, J.E.; Rundle-Thiele, S.R. Eating for the better: A social marketing review (2000–2012). Public Health Nutr. 2014, 17, 1628–1639. [Google Scholar] [CrossRef][Green Version]
- Moore, G.F.; Audrey, S.; Barker, M.; Bond, L.; Bonell, C.; Hardeman, W.; Moore, L.; O’Cathain, A.; Tinati, T.; Wight, D. Process evaluation of complex interventions: Medical Research Council guidance. BMJ 2015, 350, h1258. [Google Scholar] [CrossRef][Green Version]
- Ashton, L.M.; Hutchesson, M.J.; Rollo, M.E.; Morgan, P.J.; Collins, C.E. Motivators and barriers to engaging in healthy eating and physical activity: A cross-sectional survey in young adult men. Am. J. Men’s Health 2017, 11, 330–343. [Google Scholar] [CrossRef]
- Ashton, L.M.; Hutchesson, M.J.; Rollo, M.E.; Morgan, P.J.; Thompson, D.I.; Collins, C.E. Young adult males’ motivators and perceived barriers towards eating healthily and being active: A qualitative study. Int. J. Behav. Nutr. Phys. Act. 2015, 12, 93. [Google Scholar] [CrossRef][Green Version]
- Ashton, L.M.; Morgan, P.J.; Hutchesson, M.J.; Rollo, M.E.; Collins, C.E. Young men’s preferences for design and delivery of physical activity and nutrition interventions: A mixed-methods study. Am. J. Men’s Health 2017, 11, 1588–1599. [Google Scholar] [CrossRef]
- Holley, T.J.; Collins, C.E.; Morgan, P.J.; Callister, R.; Hutchesson, M.J. Weight expectations, motivations for weight change and perceived factors influencing weight management in young Australian women: A cross-sectional study. Public Health Nutr. 2016, 19, 275–286. [Google Scholar] [CrossRef][Green Version]
- Hutchesson, M.J.; Morgan, P.J.; Callister, R.; Pranata, I.; Skinner, G.; Collins, C.E. Be positive Be health e: Development and implementation of a targeted e-health weight loss program for young women. Telemed. E-Health 2016, 22, 519–528. [Google Scholar] [CrossRef][Green Version]
- Ashton, L.M.; Morgan, P.J.; Hutchesson, M.J.; Rollo, M.E.; Collins, C.E. Feasibility and preliminary efficacy of the ‘HEYMAN’healthy lifestyle program for young men: A pilot randomised controlled trial. Nutr. J. 2017, 16, 2. [Google Scholar] [CrossRef][Green Version]
- Hutchesson, M.J.; Callister, R.; Morgan, P.J.; Pranata, I.; Clarke, E.D.; Skinner, G.; Ashton, L.M.; Whatnall, M.C.; Jones, M.; Oldmeadow, C. A targeted and tailored eHealth weight loss program for young women: The Be Positive Be Healthe randomized controlled trial. Healthcare 2018, 6, 39. [Google Scholar] [CrossRef][Green Version]
- Centre for Epidemiology and Evidence. Developing and Using Program Logic: A Guide; Evidence and Evaluation Guidance Series; Population and Public Health Division, Ed.; Ministry of Health: Sydney, Australia, 2017.
- Centers for Disease Control and Prevention. Evaluation Guide: Developing and Using a Logic Model Promotion; Division of Heart Disease and Stroke Prevention: Atlanta, GA, USA, 2004.
- Collins, C.E.; Burrows, T.L.; Rollo, M.E.; Boggess, M.M.; Watson, J.F.; Guest, M.; Duncanson, K.; Pezdirc, K.; Hutchesson, M.J. The comparative validity and reproducibility of a diet quality index for adults: The Australian Recommended Food Score. Nutrients 2015, 7, 785–798. [Google Scholar] [CrossRef][Green Version]
- Williams, R.L.; Rollo, M.E.; Schumacher, T.; Collins, C.E. Diet quality scores of Australian adults who have completed the healthy eating quiz. Nutrients 2017, 9, 880. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Ashton, L.; Williams, R.; Wood, L.; Schumacher, T.; Burrows, T.; Rollo, M.; Pezdirc, K.; Callister, R.; Collins, C. Comparison of australian recommended food score (ARFS) and plasma carotenoid concentrations: A validation study in adults. Nutrients 2017, 9, 888. [Google Scholar] [CrossRef][Green Version]
- Ashton, L.M.; Pezdirc, K.B.; Hutchesson, M.J.; Rollo, M.E.; Collins, C.E. Is skin coloration measured by reflectance spectroscopy related to intake of nutrient-dense foods? A cross-sectional evaluation in Australian young adults. Nutrients 2018, 10, 11. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Burrows, T.L.; Collins, K.; Watson, J.; Guest, M.; Boggess, M.M.; Neve, M.; Rollo, M.; Duncanson, K.; Collins, C.E. Validity of the Australian Recommended Food Score as a diet quality index for Pre-schoolers. Nutr. J. 2014, 13, 87. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Marshall, S.; Watson, J.; Burrows, T.; Guest, M.; Collins, C.E. The development and evaluation of the Australian child and adolescent recommended food score: A cross-sectional study. Nutr. J. 2012, 11, 96. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Google Analytics. About Organic-Search Sources. Available online: https://support.google.com/analytics/answer/2795821?hl=en (accessed on 30 November 2020).
- Kubacki, K.; Rundle-Thiele, S.; Pang, B.; Buyucek, N. Minimizing alcohol harm: A systematic social marketing review (2000–2014). J. Bus. Res. 2015, 68, 2214–2222. [Google Scholar] [CrossRef][Green Version]
- van de Sand, F.; Frison, A.-K.; Zotz, P.; Riener, A.; Holl, K. The Intersection of User Experience (UX), Customer Experience (CX), and Brand Experience (BX). In User Experience Is Brand Experience; Springer: Berlin/Heidelberg, Germany, 2020; pp. 71–93. [Google Scholar]
- HotJar. The Complete Guide to Website Heat Maps. Available online: https://www.hotjar.com/heatmaps/ (accessed on 15 December 2020).
- Rangaswamy, A.; Van Bruggen, G.H. Opportunities and challenges in multichannel marketing: An introduction to the special issue. J. Interact. Mark. 2005, 19, 5–11. [Google Scholar] [CrossRef][Green Version]
- Cushman, M. Search engine optimization: What is it and why should we care? Res. Pract. Thromb. Haemost. 2018, 2, 180. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Khan, M.; Mahmood, A. A distinctive approach to obtain higher page rank through search engine optimization. Sādhanā 2018, 43, 43. [Google Scholar] [CrossRef][Green Version]
- Google Analytics. About Bounce Rate. Available online: https://support.google.com/analytics/answer/1009409?hl=en#:~:text=About%20bounce%20rate&text=Bounce%20rate%20is%20single%2Dpage,request%20to%20the%20Analytics%20server (accessed on 30 November 2020).
- Drivas, I.C.; Sakas, D.P.; Giannakopoulos, G.A.; Kyriaki-Manessi, D. Optimization of Paid Search Traffic Effectiveness and Users’ Engagement Within Websites. In International Conference on Business Intelligence & Modelling; Springer: Berlin/Heidelberg, Germany, 2019; pp. 17–30. [Google Scholar]
- Vendivel, M. Virtual Rebel Website: A Strategy to Increase User Engagement through Bounce Rate Analysis. Master’s Thesis, University of Nevada, Las Vegas, NV, USA, 2014. [Google Scholar]
- Clark, D.J.; Nicholas, D.; Jamali, H.R. Evaluating information seeking and use in the changing virtual world: The emerging role of Google Analytics. Learn. Publ. 2014, 27, 185–194. [Google Scholar] [CrossRef][Green Version]
- Vona, P.; Wilmoth, P.; Jaycox, L.H.; McMillen, J.S.; Kataoka, S.H.; Wong, M.; DeRosier, M.E.; Langley, A.K.; Kaufman, J.; Tang, L. A web-based platform to support an evidence-based mental health intervention: Lessons from the CBITS web site. Psychiatr. Serv. 2014, 65, 1381–1384. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Google Analytics. Google Analytics Cookie Usage on Websites. Available online: https://developers.google.com/analytics/devguides/collection/analyticsjs/cookie-usage (accessed on 30 November 2020).
- Lam, E.; Partridge, S.; Allman-Farinelli, M. Strategies for successful recruitment of young adults to healthy lifestyle programmes for the prevention of weight gain: A systematic review. Obes. Rev. 2016, 17, 178–200. [Google Scholar] [CrossRef]
- Ashton, L.M.; Morgan, P.J.; Hutchesson, M.J.; Rollo, M.E.; Young, M.D.; Collins, C.E. A systematic review of SNAPO (Smoking, Nutrition, Alcohol, Physical activity and Obesity) randomized controlled trials in young adult men. Prev. Med. 2015, 81, 221–231. [Google Scholar] [CrossRef]
- Gough, B. ‘Real men don’t diet’: An analysis of contemporary newspaper representations of men, food and health. Soc. Sci. Med. 2007, 64, 326–337. [Google Scholar] [CrossRef]
- Shaw, H.; Ellis, D.A.; Kendrick, L.-R.; Ziegler, F.; Wiseman, R. Predicting smartphone operating system from personality and individual differences. Cyberpsychol. Behav. Soc. Netw. 2016, 19, 727–732. [Google Scholar] [CrossRef]
- Linardon, J.; Rosato, J.; Messer, M. Break Binge Eating: Reach, engagement, and user profile of an Internet-based psychoeducational and self-help platform for eating disorders. Int. J. Eat. Disord. 2020, 53, 1719–1728. [Google Scholar] [CrossRef]
- Mehmet, M.; Roberts, R.; Nayeem, T. Using digital and social media for health promotion: A social marketing approach for addressing co-morbid physical and mental health. Aust. J. Rural Health 2020, 28, 149–158. [Google Scholar] [CrossRef]
- Song, M.J.; Ward, J.; Choi, F.; Nikoo, M.; Frank, A.; Shams, F.; Tabi, K.; Vigo, D.; Krausz, M. A process evaluation of a web-based mental health portal (WalkAlong) using google analytics. JMIR Ment. Health 2018, 5, e50. [Google Scholar] [CrossRef]
- Google Analytics. About Benchmarking: Compare your Property’s Performance to That of Your Industry Peers. Available online: https://support.google.com/analytics/answer/6086666?hl=en (accessed on 30 November 2020).
- Gupta, A.; Calfas, K.J.; Marshall, S.J.; Robinson, T.N.; Rock, C.L.; Huang, J.S.; Epstein-Corbin, M.; Servetas, C.; Donohue, M.C.; Norman, G.J. Clinical trial management of participant recruitment, enrollment, engagement, and retention in the SMART study using a Marketing and Information Technology (MARKIT) model. Contemp. Clin. Trials 2015, 42, 185–195. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Patrick, K.; Marshall, S.; Davila, E.; Kolodziejczyk, J.; Fowler, J.; Calfas, K.; Huang, J.; Rock, C.; Griswold, W.; Gupta, A. Design and implementation of a randomized controlled social and mobile weight loss trial for young adults (project SMART). Contemp. Clin. Trials 2014, 37, 10–18. [Google Scholar] [CrossRef][Green Version]
- Topolovec-Vranic, J.; Natarajan, K. The use of social media in recruitment for medical research studies: A scoping review. J. Med. Internet Res. 2016, 18, e286. [Google Scholar] [CrossRef] [PubMed]
- Madia, S.A. Best practices for using social media as a recruitment strategy. Strateg. HR Rev. 2011. [Google Scholar] [CrossRef]
- Klassen, K.M.; Douglass, C.H.; Brennan, L.; Truby, H.; Lim, M.S. Social media use for nutrition outcomes in young adults: A mixed-methods systematic review. Int. J. Behav. Nutr. Phys. Act. 2018, 15, 1–18. [Google Scholar] [CrossRef][Green Version]
- Chung, A.E.; Skinner, A.C.; Hasty, S.E.; Perrin, E.M. Tweeting to health: A novel mHealth intervention using Fitbits and Twitter to foster healthy lifestyles. Clin. Pediatrics 2017, 56, 26–32. [Google Scholar] [CrossRef] [PubMed]
- Jenkins, E.L.; Ilicic, J.; Molenaar, A.; Chin, S.; McCaffrey, T.A. Strategies to Improve Health Communication: Can Health Professionals Be Heroes? Nutrients 2020, 12, 1861. [Google Scholar] [CrossRef]
- Klassen, K.M.; Borleis, E.S.; Brennan, L.; Reid, M.; McCaffrey, T.A.; Lim, M.S. What people “like”: Analysis of social media strategies used by food industry brands, lifestyle brands, and health promotion organizations on Facebook and Instagram. J. Med. Internet Res. 2018, 20, e10227. [Google Scholar] [CrossRef]
- Saura, J.R.; Reyes-Menendez, A.; Thomas, S.B. Gaining a deeper understanding of nutrition using social networks and user-generated content. Internet Interv. 2020, 20, 100312. [Google Scholar] [CrossRef]
- Hearn, L.; Miller, M.; Lester, L. Reaching perinatal women online: The Healthy You, Healthy Baby website and app. J. Obes. 2014, 2014. [Google Scholar] [CrossRef] [PubMed][Green Version]
- MarketingSherpa. The MarketingSherpa E-commerce Benchmark Study. Available online: https://www.marketingsherpa.com/article/chart/ecommerce-percentage-returning-visitors (accessed on 30 November 2020).
- Murphy, A.L.; Peltekian, S.; Gardner, D.M. Website analytics of a Google Ads campaign for a men’s mental health website: Comparative analysis. JMIR Ment. Health 2018, 5, e12428. [Google Scholar] [CrossRef] [PubMed]
- Chaffey, D. Total E-Mail Marketing: Maximizing Your Results from Integrated E-Marketing; Routledge: London, UK, 2007. [Google Scholar]
- Moniz, K.; Yuan, Y. Reaching Critical Mass: The Effect of Adding New Content on Website Visitors and User Registration. In International Conference on Trustworthy Computing and Services; Springer: Berlin/Heidelberg, Germany, 2014; pp. 359–369. [Google Scholar]
- Willis, M. The Dynamics of Social Media Marketing Content and Customer Retention. In Leveraging Computer-Mediated Marketing Environments; IGI Global: Hershey, PA, USA, 2019; pp. 1–21. [Google Scholar]
- Brusk, J.J.; Bensley, R.J. A comparison of mobile and fixed device access on user engagement associated with Women, Infants, and Children (WIC) online nutrition education. JMIR Res. Protoc. 2016, 5, e216. [Google Scholar] [CrossRef] [PubMed]
- Zhang, D.; Adipat, B. Challenges, methodologies, and issues in the usability testing of mobile applications. Int. J. Hum. Comput. Interact. 2005, 18, 293–308. [Google Scholar] [CrossRef]
- Adams, R. Decision and stress: Cognition and e-accessibility in the information workplace. Univers. Access Inf. Soc. 2007, 5, 363–379. [Google Scholar] [CrossRef]
- Short, C.E.; DeSmet, A.; Woods, C.; Williams, S.L.; Maher, C.; Middelweerd, A.; Müller, A.M.; Wark, P.A.; Vandelanotte, C.; Poppe, L. Measuring engagement in eHealth and mHealth behavior change interventions: Viewpoint of methodologies. J. Med Internet Res. 2018, 20, e292. [Google Scholar] [CrossRef] [PubMed]
- Arden-Close, E.J.; Smith, E.; Bradbury, K.; Morrison, L.; Dennison, L.; Michaelides, D.; Yardley, L. A visualization tool to analyse usage of web-based interventions: The example of positive online weight reduction (POWeR). JMIR Hum. Factors 2015, 2, e4310. [Google Scholar] [CrossRef]
- Baltierra, N.B.; Muessig, K.E.; Pike, E.C.; LeGrand, S.; Bull, S.S.; Hightow-Weidman, L.B. More than just tracking time: Complex measures of user engagement with an internet-based health promotion intervention. J. Biomed. Inform. 2016, 59, 299–307. [Google Scholar] [CrossRef]
- Couper, M.P.; Alexander, G.L.; Maddy, N.; Zhang, N.; Nowak, M.A.; McClure, J.B.; Calvi, J.J.; Rolnick, S.J.; Stopponi, M.A.; Little, R.J. Engagement and retention: Measuring breadth and depth of participant use of an online intervention. J. Med. Internet Res. 2010, 12, e52. [Google Scholar] [CrossRef]
- Alonso-Dos-Santos, M.; Llanos-Contreras, O.; Farías, P. Family firms’ identity communication and consumers’ product involvement impact on consumer response. Psychol. Mark. 2019, 36, 791–798. [Google Scholar] [CrossRef]
- Farías, P. The Use of Fear versus Hope in Health Advertisements: The Moderating Role of Individual Characteristics on Subsequent Health Decisions in Chile. Int. J. Environ. Res. Public Health 2020, 17, 9148. [Google Scholar] [CrossRef]
|Andreasen’s Social Marketing Benchmark Criteria||Brief Description of Benchmark Criteria||How We Addressed the Criteria in No Money No Time|
|Behavioural objective||The objective of social marketing is to change people’s behavior.||Goal: To help people to improve diet quality measured using HEQ score.|
|Audience segmentation||Segmentation investigates key needs and motives for unique groups to inform different marketing and promotion mixes accordingly.||Identification of unique groups based on key motivators, individually targeted using personalised emails, recipes and blog articles specific to motivators. These were: (i) to achieve or maintain a healthy weight, (ii) to find out whether my diet is healthy (iii) to perform better in sport (iv) to know more about how to eat better and (v) to feel better or improve well-being.|
|Formative research||Formative research investigates the consumers’ needs and provide understanding of motives that can be influenced to achieve desired behavior change goals.||Previous formative research on needs, motivators, preferences and barriers undertaken with target audience (young adults) [20,21,22,23,24].|
|Exchange||Social marketing exchange reduces effort for users and emphasises/maximises the consumer benefit, e.g., “what would motivate people to engage willingly with the website and offer them something beneficial in return” ||Goal—increase user engagement through: |
Heightened user experience (UX): i.e., the process of supporting user behaviour through usability, usefulness, and desirability provided in the interaction with a website . A pre-launch site audit of user-experience (UX) was conducted. Young adults (n = 30) tested the site prior to launch to further optimise UX for the needs of intended audience.
Continual site monitoring and response to feedback: obtained via an embedded evaluation tool (HotJar) to help understand users website behaviour and to obtain feedback through feedback polls, session recordings and heatmaps to visualise popular (hot) and unpopular (cold) webpage elements . This assisted in prioritising enhancements for ongoing improvements to UX and user-engagement, with enhancements deployed sequentially.
New weekly content to address trending diet topics.
Multi-channel marketing, defined as the implementation of a single strategy across multiple channels for better engagement with users/participants . These included: automated emails (approx. 1–2 emails per month to those who complete the HEQ and sign-up to account) and regular (1–2 posts per week) social media presence (Twitter, Instagram and Facebook) to inform of new content and encourage users to return to the site.
Encouragement to track progress over time by email and website messaging to re-take the HEQ every 3 months and track progress over time.
|Marketing mix||Moving beyond communication using multifaceted interventions (e.g., more than promotion and communication). Refers to many benefits for the target audience considering the 4p’s (product, place, price and promotion) ||Benefits for user includes: institutional trust, free access to website, evidence based information from accredited practicing dietitians and nutrition researchers, personalised support (i.e., dietary feedback report which compares score to Australian normative data). |
Benefits promoted on site and in marketing materials.
Conversion Rate Optimization (CRO) tested UX variations and adjusted marketing strategies to increase percentage of website visitors, sign up rate and HEQ completions.
|Competition||Competition faced by the desired behavior. Competition could be harmful behaviors that will lead to this behavior or any behavior, product or idea that negatively impacts health and wellbeing ||Analysis of direct and indirect competition.|
|Scheme 2||Publication/Release Date||Number of Users on the Day of Release/Pub|
|Local Radio interview, local Newspaper article x2, online blog x2||18/07/2019||271|
|Local Newspaper article||19/07/2019||431|
|Local Newspaper article||22/08/2019||47|
|Academic news article||27/08/2019||105|
|Link to site on Massive Online Open Course||4/09/2019||22|
|Podcast shared on social media by podcast creator||25/09/2019||512|
|National radio interview (number 1)||17/10/2019||1089|
|Local Newspaper article and local TV news segment||11/02/2020||664|
|National radio interview (number 2)||20/02/2020||1003|
|Online article in International news resource||20/03/2020||112|
|Promoted by state health organisation on social media||24/03/2020||544|
|Local newspaper article x2||4/04/2020||120|
|National radio interview (number 3)||9/07/2020||2987|
|Demographics||Category||Total, n (% of Users)|
|Country (150 countries)||Australia||33,841 (79.5%)|
|United Kingdom||2795 (6.6%)|
|United States||1582 (3.7%)|
|South Africa||685 (1.6%)|
|New Zealand||536 (1.3%)|
|Other ≠ (145 other countries)||2974 (7.3%)|
|Age range (n = 15,258 *)||18–24||1738 (11.3%)|
|Gender (n = 15,574 *)||Female||10,530 (67.2%)|
|Session||Full Sample (n = 61,273), n%||Young Adults (n = 10,418), n%|
|1||36,849 (60.1%)||6232 (59.8%)|
|2||9620 (15.7%)||1646 (15.8%)|
|3||4276 (7.0%)||747 (7.2%)|
|4||2453 (4.0%)||431 (4.1%)|
|5||1588 (2.6%)||275 (2.6%)|
|6||1097 (1.8%)||188 (1.8%)|
|7||796 (1.3%)||119 (1.1%)|
|8||599 (1.0%)||92 (0.9%)|
|9–14||1878 (3.1%)||326 (3.1%)|
|15–25||1017 (1.7%)||188 (1.8%)|
|26–50||524 (0.9%)||66 (0.6%)|
|51–100||318 (0.5%)||53 (0.5%)|
|101–200||247 (0.4%)||48 (0.5%)|
|201+||11 (0.0%)||0 (0%)|
|Session Duration (mins)|
|≤1 min||40,188 (65.6%)||6665 (64.0%)|
|>1 min to ≤3 min||6880 (11.2%)||1230 (11.8%)|
|>3 min to ≤10 min||6949 (11.3%)||1220 (11.7%)|
|>10 min||7256 (11.8%)||1303 (12.5%)|
|Total Sample (18+ years)||Young Adults (18–34 year olds)||Return Users|
|Page||Total (% of Total Page Views: 273,170)||Page||Total (% of Total Page Views: 39,363)||Page||Total (% of Total Page Views: 100,317)|
|Homepage||39,606 (14.5%)||Homepage||7557 (19.2%)||Homepage||10,679 (10.7%)|
|Recipes page 1||23,121 (8.5%)||Recipes page 1||4303 (10.9%)||Recipes page 1||8729 (8.7%)|
|Recipes page 2||6776 (2.5%)||Recipes page 2||1185 (3.0%)||Recipes page 2||2254 (2.3%)|
|Individual recipe||5191 (1.9%)||Individual recipe||970 (2.5%)||Recipes page 3||1871 (1.9%)|
|Recipes page 3||5181 (1.9%)||Hacks, Myths, FAQ’s||938 (2.4%)||Hacks, Myths, FAQ’s||1858 (1.9%)|
|Hacks, Myths, FAQ’s||4953 (1.8%)||Recipes page 3||886 (2.3%)||Individual recipe||1537 (1.5%)|
|Recipes page 4||3907 (1.4%)||Recipes page 4||648 (1.7%)||Recipes page 4||1468 (1.5%)|
|Everyday superfoods||3362 (1.2%)||Everyday superfoods||571 (1.5%)||Everyday superfoods||1296 (1.3%)|
|Recipes page 5||3048 (1.1%)||Recipes page 5||524 (1.3%)||Recipes page 5||1159 (1.2%)|
|Recipes page 6||2444 (0.9%)||Recipes made with microwave||487 (1.2%)||Recipes page 6||931 (0.9%)|
|Total Sample (18+ years)||Young Adults (18–34 years)|
|Channels||Sessions (n = 61,273), n (%)||Bounce Rate||Pages per Session, n||Mean Session Duration (min:s)||Conversions, n Rate (%)||Sessions (n = 10,418), n (%)||Bounce Rate||Pages per Session, n||Mean Session Duration|
|Conversion Rate (%)|
|Organic Search||31,770 (51.9%)||41.8%||4.6||3:43||26.9%||6117 (58.7%)||38.7||5.2||4:04||27.2%|
|Direct||19,360 (31.6%)||39.4%||4.5||3:35||20.7%||2318 (22.3%)||36.3||4.6||3:38||24.2%|
|Referral||6115 (10.0%)||37.7%||4.6||3:47||20.7%||1212 (11.6%)||37.8%||4.7||3:46||18.7%|
|Social media||3765 (6.1%)||31.1%||3.0||2:12||40.7%||758 (7.3%)||31.7%||3.4||2:44||36.8%|
|262 (0.4%)||57.3%||2.4||2:00||5.7%||13 (0.1%)||46.2%||2.6||0:23||7.7%|
|Total Sample (18+ years)||Young Adults (18–34 year olds)|
|Browser||n (% of Total Sessions: 61,273)||Browser||n (% of Sessions for this Age Group—10,418)|
|Google Chrome||25,391 (41.4%)||Google Chrome||7841 (75.3%)|
|Safari||25,083 (40.9%)||Samsung Internet||823 (7.9%)|
|Samsung internet||2883 (4.7%)||Safari (in-app)||528 (5.1%)|
|Safari (in-app)||2329 (3.8%)||Android Webview||401 (3.8%)|
|Edge||1455 (2.4%)||Safari||364 (3.5%)|
|Other (15 other browsers)||4132 (6.8%)||Other (4 other browsers)||461 (4.4%)|
|Total Sample (18+ years)||Young Adults (18–34 year olds)|
|Device||Sessions (n = 61,273), n (%)||Bounce Rate||Pages per Session, n||Mean Session Duration||Conversions, n Rate (%)||Sessions (n = 10,418), n (%)||Bounce Rate||Pages per Session, n||Mean Session Duration||Conversion Rate (%)|
|Mobile (phone)||39,137 (63.9%)||47.5%||3.5||2 min, 50 s||24.0%||6457 (62.0%)||46.2%||3.6||2 min, 49 s||24.9%|
|Desktop (inc laptop)||18,452 (30.1%)||25.0%||6.4||5 min, 2 s||28.0%||3762 (36.1%)||22.3%||7.0||5 min 33 s||28.7%|
|Tablet||3684 (6.0%)||36.5%||5.3||4 min, 18 s||21.9%||199 (1.9%)||43.7%||5.5||4 min, 06 s||21.1%|
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Ashton, L.M.; Rollo, M.E.; Adam, M.; Burrows, T.; Shrewsbury, V.A.; Collins, C.E. Process Evaluation of the ‘No Money No Time’ Healthy Eating Website Promoted Using Social Marketing Principles. A Case Study. Int. J. Environ. Res. Public Health 2021, 18, 3589. https://doi.org/10.3390/ijerph18073589
Ashton LM, Rollo ME, Adam M, Burrows T, Shrewsbury VA, Collins CE. Process Evaluation of the ‘No Money No Time’ Healthy Eating Website Promoted Using Social Marketing Principles. A Case Study. International Journal of Environmental Research and Public Health. 2021; 18(7):3589. https://doi.org/10.3390/ijerph18073589Chicago/Turabian Style
Ashton, Lee M., Megan E. Rollo, Marc Adam, Tracy Burrows, Vanessa A. Shrewsbury, and Clare E. Collins. 2021. "Process Evaluation of the ‘No Money No Time’ Healthy Eating Website Promoted Using Social Marketing Principles. A Case Study" International Journal of Environmental Research and Public Health 18, no. 7: 3589. https://doi.org/10.3390/ijerph18073589