Effects of service brands’ current marketing strategies on customer attitude and behaviour

Dublin Core


Effects of service brands’ current marketing strategies on customer attitude and behaviour


Laura Gould




This project investigated current marketing strategies used by service brands, including car insurance and household energy companies, on customer’s attitudes and behaviours. The investigation involved a nationally representative sample of 1,977 participants completing an online survey, along with 30 participants taking part in a supporting qualitative online community panel exploring customers’ attitudes in more depth. Descriptive analysis showed that although participants’ loyalty reasons and bad provider experiences were predominantly determined by price, service quality was also an important factor. When choosing service providers, participants showed no preference between price and service, however slightly preferred price over reputation. Furthermore, significant correlations were found for the majority of provider switching attitudes and switching behaviours. Segmentation analysis identified four types of customers based on awareness of offers and convenience to switch: ‘Passive Loyals’, ‘Sceptical Loyals’, ‘Loyal Opportunity Switchers’ and ‘Conditioned Switchers’. A pattern was found amongst age groups – the older the participant, the more likely they preferred new customer deals over loyalty offers, were more interested in price over service quality and brand reputation, and had more expertise in the service industry. Due to the importance of customer retention (Berry, 1983), results implied brands should focus on loyalty rewards, along with gaining customers’ trust in their service quality and reliability.


Materials and procedure
The online survey included both closed and open questions, thus a mixture of quantitative and qualitative methods. Participants were asked a few demographic questions: their gender, age, employment status, type of residence, location, and how long they had been a UK resident. Those who had not been screened were quizzed on their switching and service provider behaviours and attitudes. The questions were repeated for each service type, depending on whether participants had confirmed to paying for, or making decisions on electricity, gas or car insurance, and whether they’re household energy was on a dual fuel package or organised separately. The questions that were repeated were a select few, which required separate data for each service type. These included inquiries into people’s prior switching behaviour, reasons for maintaining a relationship with their current provider, and any ‘bad’ experiences they had encountered with a service provider. This was then followed by general attitudinal scales concerned with loyalty and switching amongst service providers. The data was collected in Confirmit, a software used to create, monitor and analyse online surveys (http://www.confirmit.com/). The quantitative information was analysed in Reportal, Confirmit’s analysis feature. The qualitative answers were transferred into Microsoft Excel, and examined through the CIT (Flanagan, 1954).

Stage 2:
The second stage of the project involved segmenting participants into different groups, in order to identify different people’s needs and desires in regard to switching and loyalty, and how brands should consider different types of individuals in their marketing and advertising. First, segmentation dimensions were established, and every participants was assigned to a particular segmentation cluster. Secondly, the different segments were profiled to make each group as distinct as possible.
Identifying the segments was explorative, thus there were no set guidelines as to which dimensions to use. However, segmentation was based around the idea of switching and loyalty, and whether participants were able to be classed as different types of customers according to this. Attitudinal scales used in the online survey in stage 1 were either negatively or positively related to switching. Using k cluster means analysis on SPSS, the following variables were used as dimensions for the segmentation (along with the statements used in the online survey):
Convenience of switching: I find that switching service providers is inconvenient
Awareness of other deals: I’m not aware of offers available from other providers other than my current one
The first variable determined how constrained individuals were from switching brands. This gave an idea of whether participants felt dedicated or constrained by service brands (constrained by brands: Stanley & Markman, 1992). If a person found switching convenient, they were not held by constraints to stay within the company, thus were more likely to remain with the provider due to their brand dedication.
The second variable determined participants’ characteristics, whether they actively sought to evaluate other providers’ offers (awareness of other offers: Zeithaml, 1981). According to the research, if someone showed both awareness of other offers and convenience to switch, the individual felt they were more able to switch and were presumably more likely to switch.
Both statements were answered on a 10 point scale in the online survey, thus when segmentation divisions were made according to these dimensions, the following cluster centres for each segment were identified:
I find that switching service providers is inconvenient

I’m not aware of offers available from other providers other than my current one

Table 4. Typical scores observed for each statement across the 4 segments identified
Each participant who took part in the survey was assigned to one of the four segments according to their scores on the two dimensions. Whichever segment cluster centres were closest to their scores determined their segment group.
The next phase of the segmentation process was profiling each group in order to make them as identifiable and different to the other groups as possible. This was carried out by comparing answers from the online survey by producing crosstabs across the four clusters. Once the variation of answers were cross tabbed, comparisons were able to be carried out. This gave an insight into how many people in a particular segment gave a certain answer to the questions. In order to find any significant differences from the overall mean, answers were indexed.
Indexing was used to look at how over-represented or under-represented certain characteristics were for the four segments, relative to the base sample (1,977 participants). This was carried out by calculating an index score:
Percentage incidence of the variable for the target group x 100
Percentage incidence of the variable for the base group
The index score indicated whether the variables for the two groups were showing significant differences. Comparing them gave an idea of which variable was over indexing the most or least, giving a picture of what ‘ingredients’  may be making up the main differences between segments. Generally an index of less than 80 or greater than 120 was considered significantly statistically different.
Supporting qualitative attitudes
This was supported by a of the project involved an in-depth qualitative investigation, exploring participants’ attitudes on brand loyalty and switching, past experiences with household energy and car insurance providers, and attitudes on current loyalty and switching strategies. Participants were identified into 1 of the four segments and analysed through noting important themes and patterns of people’s attitudes in the data.


Lancaster University






John Towse











Leslie Hallam

Project Level



Psychology of Advertising

Sample Size

A nationally representative sample of 1977 participants were recruited, all over 18 years of age in order to comply with the MRS code of conduct (https://www.mrs.org.uk/standards/code_of_conduct/) and were picked according to the current UK’s demographic statistics (see appendix C). Furthermore, individuals were screened from the survey if they had lived in the UK for only a very short period of time as they would not have had enough experience with household energy and car insurance providers to reliably compare them on their previous switching behaviour. Individuals were also screened if they were not involved in the payment of, or in the decision making for household energy or car insurance. 2596 people took part in the survey, which included those who did not fully complete the questions (338), started the survey after the deadline (21) and those that did not comply with the projects’ requirements (236). This left a total of 2001 complete responses which were used in the project.
The qualitative data collection involved recruiting 30 participants of those who opted to take part in further research from the 1,977 original sample. A mixture of dual fuel, gas, electricity and car insurance customers were contacted via email (200 emails in total) (see appendix E.1). Of those that responded, 30 were chosen to take part in the qualitative research

Statistical Analysis Type





Laura Gould, “Effects of service brands’ current marketing strategies on customer attitude and behaviour,” LUSTRE, accessed April 19, 2024, https://www.johnntowse.com/LUSTRE/items/show/34.