University of Amsterdam
T H E R O L E O F I N C E N T I V E S I N T H E M O T I V A T I O N O F C U S T O M E R C A R E E M P L O Y E E S T O G E N E R A T E L E A D S
Bachelor Thesis Finance and Organization
Michèlle Gittens 30-1-2017
Statement of Originality
This document is written by Student Michèlle Gittens who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text
and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This research studies the role that incentives play in the motivation of customer care employees to generate leads. The analysis is based on a combination of weekly empirical data (1.5 years) and survey data (n=33). Main finding from the empirical data is that monetary incentives do not appear to play a discernible role in the motivation of customer care employees in this study. However, 42.42% of the employees report that they are motivated by monetary incentives. This effect might not be reflected in the empirical data because the monetary reward is too low to make a discernible difference. In this research study, 66.67% of the respondents stated that their motivation to generate leads is driven by the desire to offer extra service to customers. The second finding is that service-oriented customer care employees who consider generating leads as part of extra service for the customer, outperform sales-oriented customer care employees in generating leads. This implies that intrinsic motivation is stronger than extrinsic motivation to generate leads.
1 Introduction
Even though monetary incentives have been widely discussed by academia and in the corporate world, consensus on the effects of monetary incentives has yet to be reached. There have been many debates between economists and psychologists regarding the effect of monetary rewards on behaviour. The behaviour of individuals within firms is highly influenced by the firms incentive structure (Baker, Jensen, & Murphy, 1988).
Implemented correctly and with the right performance measures, incentives can be a powerful tool to align the interest of the individual with the interests of the firm. However, some studies conclude that monetary incentives may reduce (crowd-out) intrinsic motivation (Kunz & Pfaff, 2002). Crowding out occurs when a (monetary) reward replaces the intrinsic reward otherwise received by that activity. Gneezy and Rustichini (2000) conclude that when a monetary reward is payed for an interesting activity, the intrinsic motivation decreases.
This study will build on the findings of previous studies and will look into the effect of monetary incentives on motivation of customer care employees to generate sales leads. Analysing a real life situation in a business environment allows to not only analyse the empirical data, but also to survey the employees to get additional information the empirical data might not show.
The key question that will be addressed in this study is: What role do monetary incentives play in the motivation of customer care employees to generate leads? Present study is based on data obtained from an (online) marketing company focussed on small businesses. Employee motivation to generate leads will be measured by using a survey amongst customer care employees (n=33) combined with weekly performance data on leads generated by these employees. By combining survey results with performance data, the opportunity arises to observe the effect of monetary incentives based on empirical data, while crosschecking these results with the employees own belief on what motivates them to generate leads.
The main finding of the analysis of the empirical data set is that monetary incentives do not seem to play a strong role in the motivation of customer care employees while 42.42% of respondents report that they do feel motivated by monetary incentives. This discrepancy might not be apparent in the empirical data due the monetary reward provided in the scenario analyse d being relatively low. In this study, 66.67% of the respondents stated that their motivation to generate leads is “extra service” to the customer. Service-oriented employees who consider
generating leads part of extra service for the customer outperform sales-oriented employees in generating leads.
In the following section present study will review previous research and relevant theories, then in the third section the model and the hypothesis will be formulated, followed by the analysis in the fourth section, and the discussion and suggestions for further research will follow in the fifth, and final, section.
2 Literature
Customer care employees are often the only employees of a company the customer has contact with (Netemeyer, Maxham, & Pullig, 2005). As Desphande, Farley and Webster (1993) conclude, according to the marketing concept, success of an organization depends on satisfying customer needs. This fact positions customer care employees as effective influencers of the customer’ perception of a company. Contact with customer care also provides opportunity to assess customer satisfaction and to generate leads. Identifying and generating leads is a valuable tactic for companies to create more profits from existing customers. Customer care employees should be motivated and incentivized to recognize and leverage possible sales signs.
There is various existing literature regarding the effect of incentives on employee behaviour. Standard economic theory assumes that effort is costly and monetary rewards are positive. Gneezy and Rustichini (2000) report that an increase in monetary incentives for a given task will improve performance. Behaviourist theory uses different reasoning, but the outcome is the same as the standard economists. Behaviourism argues that instrumental conditioning explains the effect of incentives. When individuals who receive a monetary incentive for a costly task, they will start to associate that costly task with the positive reward and over time they will associate a positive feeling with that costly task.
However, cognitive psychology challenges this conclusion as they state that every task has an intrinsic motivation, independent of any reward or compensation. This intrinsic motivation may be reduced by implementing monetary incentives because the focus on pay reduces the intrinsic reward otherwise obtained from the task (Baker, Jensen, & Murphy, 1988). Individuals who were compensated for their effort with a fixed reward did not show any decrease in motivation. However, the individuals that received a reward based on their performance showed a decline in intrinsic motivation. If the decrease of intrinsic value is higher
the reward has a negative impact on the employees utility. Thus implementing a monetary incentive may reduce the overall motivation and cause a decline in effort and outcome (Gneezy & Rustichini, 2000).
Using monetary incentives induces certain behaviour, the individual will choose his behaviour based on the task that will maximize his utility. For instance with the introduction of a piece rate workers will pick quantity over quality and executives who are paid based on profits are incentivised to focus on short-term goals over long term goals to maximize their utility. Because it is quite difficult to specify what the objective outcome should be and how to measure performance, the monetary incentive might have counterproductive effects (Baker, Jensen, & Murphy, 1988). In case of a poorly chosen performance measure the effort induced by implementing the monetary incentive may not benefit, and may even harm the firms interest. The company analysed in this study uses converted leads as performance measure instead of generated leads. This prevents employees trying to maximize their utility by generating low quality leads, as only converted leads get rewarded.
Another reason why monetary incentives can be counterproductive is that they may come with costly side effects like horizontal equity concerns, problems due to mismanagement and unclear performance measures that negatively affect the individuals motivation, efficiency and productivity (Hamner, 1975). According to Baker, Jensen and Murphy (1988), the cost of these side effects may outweigh the benefits. However, this implies that monetary incentives, given that they are based on aligned performance measures, can greatly motivate employees to exert a certain task.
After a set of controlled experiments, Gneezy and Rustichni (2000) concluded that the effect of introducing a monetary incentives based on performance, is non-monotonic. In situations where monetary incentives were used, an increase of this incentive led to a better performance. However, individuals that received a monetary incentive performed worse than individuals who did not receive additional compensation. This implies that performance might be negatively affected by introduction of a monetary compensation. If the amount of the monetary incentive is not high enough to outweigh the initial negative effect, the introduction of the monetary compensation will have a negative effect on outcome and performance. Since the monetary incentives used by the company studied are relatively low, this effect is likely to be present.
3 Method
The aim of present research is to determine what role incentives play in the motivation of customer care employees to generate leads and additionally to use this opportunity to analyse what motivates customer care employees to generate leads based on a combination of empirical and survey data. This study considers weekly data of 1.5 years for approximately 30 employees on their total generated leads, their contacts per month and whether there was a promotion of the monetary incentive that week. Promotion of monetary incentives is done in various ways, for instance by giving workshops and coaching, but also by giving extra incentives like gift cards, team battles where the winning team wins a team outing, small presents etc. The survey had a response rate of 89%, 33 of the 37 employees answered all the questions of the survey from which 5 were answered anonymously Additional survey questions and results can be found in part A2 of the appendix.
3.1 Data and definitions
A lead is defined as a potential sales contact. In this study we measure generated leads by customer care employees forwarding their call to the sales department or making a call back appointment for the sales department or account manager. Generating leads can be considered extra service, when adding a product or service to the customers product portfolio benefits the customers’ business. This is particularly the case for small businesses owners who lack knowledge of online marketing and would otherwise stay behind in the digitalization.
A lead is considered converted when the contact with account manager initiated by the customer service employee results in extra sales, whether by extending current services or adding new services.
Variable Obs Mean Std.Dev Min Max CONPH 1086 3.694 1.406 0 12.16 Leads 1124 1.285 1.938 0 23 PromoDum 1124 0.207 0.405 0 1 Competitive 1124 6.690 1.277 4 9 Sales 1124 5.471 2.409 0 9 Service 1124 8.275 0.812 7 10 IncenMoti 1124 3.136 0.872 1 4 ServDum 1124 0.769 0.422 0 1 MonDum 1124 0.442 0.497 0 1 PromoMoti 1124 3.582 1.187 1 5 TMMoti 1124 3.431 0.904 1 5 JobSat 1124 4.005 0.915 3 5 Importance 1124 4.980 0.142 4 5 GenDum 1124 0.864 0.343 0 1 WebDum 1124 0.456 0.499 0 1 RelDum 1124 0.446 0.498 0 1 PromoDumxG enDum 1124 0.174 0.380 0 1 TMMotixGen Dum 1124 3.034 1.456 0 5
Table 1 Descriptive statistics
3.2 Survey
The survey is focussed on the employees opinions about their motivation for generating leads and monetary incentives. The employees were asked to respond to the survey by email and in person by the researcher, emphasising the importance of their opinion for this study. As extra incentive they were informed that among the respondents 3 employees would be randomly selected who would receive two tickets for the movie theatre. The survey questions could be answered online on the computer or with a smartphone. Most of the respondents used their computer. The respondents were informed that their answers would be treated confidentially. After answering the questions they were asked for their personnel number but also had the
option to leave it blank. At the end of the survey they were asked if they agreed to share their answers with the company, if not the answers would remain confidential (33.33% agreed to share the answers with the company)
The questions of the survey were formulated in such a way that most of the answers are on a 5 or 11 point Likert scale, so these can be interpreted as interval data and can be used in a regression. For the full results of the survey see part A2 of the appendix.
3.3 Hypothesis
To determine the role of monetary incentives in the motivation of customer care employees to generate leads the following hypothesis is constructed. We test if monetary incentives are the main component of customer care employees motivation to generate leads. The hypothesis is summarized below.
H0: Monetary incentives are the main driver for customer care employees to generate leads H1: Monetary incentives are not the main driver for customer care employees to generate leads
3.4 Company specific information (incentives, department, promotion)
The research is based on data obtained from the customer care department at an online marketing company aimed at small businesses. The customer care department is considered a part of the marketing department and is led by the CMO. Contact with customers in 2015 was mainly via traditional communication channels: phone and email. In 2016 web care (social media) and chat (pop-up on the website) channels were introduced. The biggest difference between these channels is that with the online channels it is possible to service multiple customers at the same time, while with the traditional channels it is only possible to service one customer at a time. The main contact customer contact channels are slowly shifting from traditional channels towards the online channels.
The customer care department is split up in 3 different teams. The web care team focusses mainly on servicing the customer through the online channels (social media, chat, WhatsApp). The transactional team focusses on customer care through the traditional channels, they specialize in servicing the customers who are not assigned to a account manager, their customer contact is usually by phone or email. The relational team is specialized in working
with larger accounts, where focus lays on maintaining the customer relationship and where the account manager is very involved.
The aim of the customer care department is to leverage the contact with the customer to generate leads for the account managers. Generating leads is defined as forwarding a customer contact (regardless of contact channel) towards the account manager.
For the past two years the base incentive scheme has been the same, for every converted lead employees get a monetary incentive starting with 5 euros which could be doubled if other goals were met. The average conversion rate is on average 34 percent. The dependent variable for present study is generated leads because there are too many factors that play a role in conversion that are out of the customer care employees control. Next to the base incentive scheme, the company worked with various ways of promoting the monetary incentives to motivate their customer care employees to generate leads. For instance, gift cards, team battles, workshops or coaching. Management also used different approaches to motivate the employees.
The answers of the questionnaire about the motivation for generating leads will be used together with empirical data. Since the monetary incentive scheme is constant over time (the 1.5 years analysed) we will focus at the effect of promoting the monetary incentives and the reported answers of the survey regarding the motivation by incentives.
3.5 Model
The following models are constructed to answer the research question. The panel data is unbalanced, the data varies because some employees leave and new hires replace them. The regression method used is a standard OLS-regression with individual employee dummy variables and week variables that account for the time period. The fixed and random effects panel data regressions were considered, but the fixed effects panel data regression excludes the survey responses because they are constant over time and the fixed effects panel data regression is only allowed when the Haussmann test is significant which was not the case.
The dependent variable is total leads generated because this is the desired outcome.
3.5.1 Main model
𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑒𝑑 𝑙𝑒𝑎𝑑𝑠𝑖𝑡
= 𝛽0+ 𝛽1∗ 𝑃𝑟𝑜𝑚𝑜𝑀𝑜𝑡𝑖𝑖 + 𝛽2∗ 𝑀𝑜𝑛𝐷𝑢𝑚𝑖+ 𝛽3∗ 𝑃𝑟𝑜𝑚𝑜𝐷𝑢𝑚𝑖 + 𝛽4 ∗ 𝐼𝑛𝑐𝑒𝑛𝑀𝑜𝑡𝑖𝑖 + 𝛽5∗ 𝑇𝑀𝑀𝑜𝑡𝑖𝑖+ 𝜀
To explain the generated leads the following variables are used. PromoMoti to test if the self-perceived effect of promotions on motivation results in more generated leads. MonDum to investigate if the employees who list monetary incentives as their motivation to generate leads also significantly generate more leads. PromoDum is used to highlight the weeks where there was a promotion for the monetary incentive and to see if these weeks result in more generated leads. IncenMoti is added to see if a higher level of motivation resulting from monetary incentives result in higher generated leads. Ideally a variable for experience would be added to all three models to test if a more experienced employee generates more leads, but this was not possible due lack of available data.
Variable Definition
Leads Total leads an employee generates per week
PromoMoti How motivated employees feel by promotions for the monetary incentives on a 5 point Likert scale
MonDum 1 if employee lists monetary incentive as motivation for generating leads, 0 otherwise
PromoDum 1 if there was a promotion for the monetary incentive that week, 0 otherwise
IncenMoti If employees feel motivated by monetary incentives on a 5 point Likert scale
Table 2 definition variables main model
3.5.2 Extended version of main model
This extended version of the main model takes in account the gender of the employee, if the employee feels motivated by team management and which team the employee was part of at the time of the survey.
𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑒𝑑 𝑙𝑒𝑎𝑑𝑠𝑖𝑡
= 𝛽0+ 𝛽1∗ 𝑃𝑟𝑜𝑚𝑜𝑀𝑜𝑡𝑖𝑖+ 𝛽2∗ 𝑀𝑜𝑛𝐷𝑢𝑚𝑖 + 𝛽3 ∗ 𝑃𝑟𝑜𝑚𝑜𝐷𝑢𝑚𝑖 + 𝛽4 ∗ 𝐼𝑛𝑐𝑒𝑛𝑀𝑜𝑡𝑖𝑖 + 𝛽5∗ 𝑇𝑀𝑀𝑜𝑡𝑖𝑖 + 𝛽6∗ 𝐺𝑒𝑛𝐷𝑢𝑚𝑖+ 𝛽7∗ 𝑊𝑒𝑏𝐷𝑢𝑚𝑖 + 𝛽8 ∗ 𝑅𝑒𝑙𝐷𝑢𝑚𝑖+ 𝜀
The TMMoti variable is added to test whether reported motivation by team management results in more total generated leads. GenDum is added to see if gender explains difference in generated leads. WebDum and RelDum are added to test if different teams have an effect on employees total generated leads. Ideally interaction terms PromoDumxGen and TMDumxGen would be added to the extended model, but they made the model less precise by reducing the adjusted R-square.
Variable Definition
TMMoti How motivated employees feel by team management to generate leads on a 5 point Likert scale
GenDum 1 if male, 0 if female
WebDum 1 if employee is part of web care team, 0 otherwise RelDum 1 if employee is part of relational team, 0 otherwise Table 3 definition of added variables for extended model
For both the main model and the extended version there was no multicollinearity. See part A1 in the appendix for the correlation matrix .
3.5.3 Motivation model
To determine what motivates customer care employees a third model was constructed. This model focusses on factors that might explain the motivation of customer care employees to generate leads.
𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑒𝑑 𝑙𝑒𝑎𝑑𝑠𝑖𝑡
= 𝛽0+ 𝛽1∗ 𝑆𝑒𝑟𝑣𝑖𝑐𝑒𝑖+ 𝛽2∗ 𝑆𝑎𝑙𝑒𝑠𝑖+ 𝛽3∗ 𝐽𝑜𝑏𝑆𝑎𝑡𝑖+ 𝛽4∗ 𝑆𝑒𝑟𝑣𝐷𝑢𝑚𝑖+ 𝛽5 ∗ 𝑀𝑜𝑛𝐷𝑢𝑚𝑖 + 𝛽6∗ 𝐼𝑚𝑝𝑜𝑟𝑡𝑎𝑛𝑐𝑒𝑖 + 𝜀
The Service and Sales variables are added to see what effect service and sales orientation has on generated leads. JobSat is used to test if a higher level of job satisfaction results in higher total generated leads. Similarly to MonDum, ServDum is added to test if extra service as motivation to generate leads results a higher total leads generated for the employee. The Importance variable tests if employees who think leads are important for the company generate more leads.
Variable Definition
Service Self-perceived level of service orientation on the scale of 0 to 10 Sales Self-perceived level of sales orientation on the scale of 0 to 10 JobSat Level of job satisfaction on a 5 point Likert scale
ServDum 1 if employee lists extra service for the customer as motivation to generate leads, 0 otherwise
MonDum 1 if employee lists monetary incentive as motivation for generating leads, 0 otherwise
Importance If employee thinks leads are important for the future of the company on a 5 point Likert scale
4 Results
By implementing the previous models the following results are obtained.
4.1 Main model
Table shows that PromoMoti, MonDum, PromoDum and IncenMoti all have a negative coefficient. The promotion motivation coefficient (PromoMoti) suggests that employees who reportedly feel motivated by the monetary promotions generate less total leads, however this result is insignificant. The monetary dummy (MonDum) shows that employees who report to be motivated by monetary incentives generate less total leads. The promotion dummy (PromoDum) is negative, this means that in weeks with monetary incentive promotion the total generated leads was lower than in weeks without promotion of the monetary incentive.
The incentive motivation coefficient (InenMoti) is negative, it suggests that employees who report that their motivation to generate leads comes from monetary incentives generate less leads, but is this also not significant. The team managers coefficient(TMMoti) is positive, this shows that the more employees are motivated by team managers, the more leads they generate.
Leads Coefficient Std. Err t-value P-value 95% Confidence interval
Lower bound Upper Bound
PromoMoti -0.135 0.512 -0.26 0.792 -1.140 0.870
MonDum -2.353 0.796 -2.96 0.003 -3.915 -0.791
PromoDum -0.449 0.213 -2.11 0.036 -0.867 -0.030
IncenMoti -0.628 0.784 -0.80 0.423 -2.167 0.910
TMMoti 1.033 0.276 3.74 0.000 0.491 1.575
Table 4 Main model Adj. R-square 0.2816
4.2 Extended version of main model
The extended version of the main model includes variables that account for gender and employees from different teams within the customer care department. The main difference is that IncenMoti changed signs and is now positive, however it remains insignificant. The added variables gender (GenDum), web care team (WebDum) and relational team (RelDum) are all positive but insignificant. Adding the extra variables also made TMMoti insignificant and the adjusted R-square is slightly lower.
Leads Coefficient Std. Err t-value P-value 95% Confidence interval
Lower bound Upper Bound
PromoMoti -3.274 3.436 -0.95 0.341 -1.002 3.470 MonDum -2.364 0.802 -2.95 0.003 -3.938 -0.789 PromoDum -0.453 0.217 -2.08 0.037 -0.879 -0.026 IncenMoti 4.076 5.158 0.79 0.429 -6.043 1.419 TMMoti -0.533 1.722 -0.31 0.757 -3.912 2.847 GenDum 0.455 1.225 0.37 0.711 -1.950 2.858 WebDum 1.125 1.180 0.95 0.341 -1.191 3.441 RelDum 1.108 1.176 0.94 0.347 -1.201 3.416
Table 5 Extended version main model Adj. R-square 0.2802
4.3 Motivation model
Next to determining what the role of incentives are on motivation, this research gives a good opportunity to see what motivates customer care employees to generate leads.
The service coefficient is negative, this suggests that employees who perceive themselves as service-oriented generate significantly less leads. The sales coefficient is
positive, this implies that employees who report to be sales-oriented generate more leads. The job satisfaction coefficient(JobSat) is negative, but insignificant.
In contrast to in the main models, the monetary incentive dummy (MonDum) is positive. The service dummy (ServDum) is also positive, however the service dummy has a higher positive effect than the monetary incentive dummy (4.163>2.177). These results can be explained that most of the customer care employees perceive themselves as service-oriented, but not all of them associate service with generating leads. The employees that do associate generating leads with extra service outperform the employees who are motivated by incentives. Importance of leads for the company has a negative coefficient, but is insignificant.
Leads Coefficient Std. Err t-value P-value 95% Confidence interval
Lower bound Upper Bound
Service -2.085 0.318 -6.56 0.000 -2.709 -1.462 Sales 0.394 0.108 3.64 0.000 0.182 0.607 JobSat -0.032 0.073 -0.44 0.662 -0.176 0.112 ServDum 4.163 1.019 4.08 0.000 2.163 6.163 MonDum 2.177 0.499 4.36 0.000 1.197 3.156 Importance -0.243 1.696 -0.14 0.886 -3.571 3.086
Table 6 Motivation model Adj. R-square 0.2780
4.4 Survey results
The above models show an interesting relation between incentives, motivation and generated leads. There is mostly a negative relation between incentives and generated leads even if employees report to feel motivated by those incentives. The survey is a valuable tool to get a better insight into how employees feel about the incentives and their motivation in general.
Almost half (45.45%) of the respondents report that they agree with the statement that they are motivated by incentives to generate leads, 27.27% is neutral, 21.21% disagrees and 6.06% strongly disagrees.
Around one third (31.43%) agrees with the statement that incentive promotions motivate them to generate leads, 5.71% fully agree with this statement, 42.86% feel neutral and respectively 8.57% and 11.43% disagree and strongly disagree.
Comparing these two would suggest that customer care employees are more often motivated by the monetary incentives than by the additional incentive promotions.
Figure 1 n=33 Figure 1 n=35
It is not only of interest to determine if the customer care employee feels motivated by the monetary incentives, but it is also relevant to see what the opinion is regarding the monetary incentive in place.
It is surprising that almost half (48.57%) of the respondents reported that they did not pay attention to the monetary incentive. 34.29% responded that they think the monetary incentive is too low, 11.43% responded that the monetary incentive is exactly right and 5.71% stated that they generally do not generate leads.
The gross group of respondents either pays no attention to the monetary incentives or think that the incentive is too low. This might be explained by the effort it takes to generate a lead. 42.86% of the respondents report that they disagree with the statement that it is easy to generate leads, 2.86% strongly disagrees 37.14% is neutral and only 17.14% reports that the find it easy to generate leads. The answers to the question if the employee finds the monetary incentive in proportion to the effort it takes to generate leads are divided. Half of the group (51.52%) is neutral, 21.21% agree that it is in proportion, while 21.21% disagrees and 6.06% strongly disagrees with the statement.
0,00% 45,45% 27,27% 21,21% 6,06% 0,00% 15,00% 30,00% 45,00% 60,00% Strongly agree Agree Neutral Disagree Strongly disagree
The monetary incentive motivates me to generate leads 5,71% 31,43% 42,86% 8,57% 11,43% 0,00% 15,00% 30,00% 45,00% 60,00% Strongly agree Agree Neutral Disagree Strongly disagree
The incentive promotions motivate me to generate leads
Figure 3 n=35 Figure 4 n=33
Figure 5 n=35
5 Discussion
The results of the analysis of the different models show that (monetary) incentives have an ambiguous effect on the motivation of customer care employees to generate leads.
In both the main model and the extended version of the main model the self-perceived level of motivation by promotion of incentives (PromoMoti) and the monetary dummy (MonDum), for employees who report to be motivated by incentives, have a negative relation with the total leads generated. This is supported by the negative relation of the promotion
48,57% 0,00% 34,29% 5,71% 11,43% 0,00% 0,00% 20,00% 40,00% 60,00% I don't pay attention to
it
I think it's too high I think it's too low I don't generate leads I think it's exactly right I don't need a monetary
incentive
How do you feel about the monetary incentive you receive for
a converted lead? 0,00% 17,14% 37,14% 42,86% 2,86% 0,00% 15,00% 30,00% 45,00% 60,00% Strongly agree Agree Neutral Disagree Strongly disagree
I think it's easy to generate leads
0,00% 21,21% 51,52% 21,21% 6,06% 0,00% 15,00% 30,00% 45,00% 60,00% Strongly agree Agree Neutral Disagree Strongly disagree
The monetary incentive is in proportion to the effort it takes to
dummy (PromoDum) that takes in account the weeks that a promotion of incentives was active. The incentive motivation coefficient (IncenMoti) differs between the two models. It has a negative relation in the main model consistent with the other variables. But the extended model shows a positive relation between the self-perceived motivation by incentives and the total generated leads. However the results of the incentive motivation coefficient are insignificant for both models.
This analysis gives sufficient evidence to reject the null-hypothesis that states that incentives are the main driver for customer care employees to generate leads. It seems that monetary incentives do not have a big influence on the motivation for generating leads of customer care employees.
The motivation model is constructed to determine the motivational drivers of customer care employees to generate leads and which characteristics result in higher total leads generated. It shows that the service coefficient has a negative relation and the sales coefficient has a positive relation. This aligns with the assumption that service-oriented employees might focus more on their service level and sales-oriented employees might be more inclined to recognize and act on opportunities to generate leads.
However, the service dummy and the monetary dummy are both significantly positive, while the service dummy shows a stronger relation than the monetary dummy (4.163>2.177). This can be explained by the observation that most of the customer care employees are service-oriented, but not all service-oriented employees associate generating leads with offering extra service to the customer. Employees that do associate offering extra service with generating leads outperform the employees who are mainly motivated by the monetary incentive.
This would suggest that management should emphasise the relation between extra service for the customer and generating leads to appeal to the intrinsic motivation of a customer care employee.
The main finding of the survey is that almost half of the respondents do feel motivated by incentives, but the issue is that the incentives used are not sufficiently high to effectively motivate employees. Employees report that generating leads is difficult and they think that the current reward is too low compared to the effort it takes to generate a lead. Increasing the monetary incentive might give employees who do not mainly generate leads out of extra service the extra enticement to put more effort in generating leads.
This study has several limitations that imply the need for future research. The empirical data used in this study is from a relatively short time period (1.5 years) and a relatively small customer care department. It would be interesting to see if similar results would be observed in larger departments and across different industries.
Secondly, this study is conducted at a company whose customer care department is fully integrated with the company itself. It is arguable that employees of companies that outsourced their customer care departments to remote call centres might have less of a binding with the company and thus might feel less intrinsically motivated to generate leads. The same argumentation holds for call centres at companies generating a lead is less likely to be considered extra service.
Thirdly, the amount of the monetary incentive might play a big role in the scope of the motivation induced by the incentive. It is arguable that with a bigger reward, a bigger group of employees will feel incentivized to generate more leads. And with a bigger reward the employees are likely to take more risks to generate leads.
Another effect to take in account is the selection bias, the employees in this study were not randomly assigned to the different teams, but rather selected on their performance and abilities. Studying a group where employees are randomly assigned might give different results.
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Appendix
A1 Correlation matrix
PromoMoti MonDum IncenMoti TMMoti PromoDum GenDum WebDum RelDum
PromoMoti 1 MonDum 0.1576 1 IncenMoti -0.0131 0.2332 1 TMMoti 0.2532 0.4302 0.1392 1 PromoDum 0.0467 0.0308 0.0184 0.0308 1 GenDum 0.2497 0.1862 0.0650 0.2265 -0.0338 1 WebDum 0.0793 0.0454 -0.0014 0.1236 0.1933 0.1339 1 RelDum -0.0105 -0.0271 -0.0580 0.0164 -0.2069 0.1837 -0.8202 1
Table 1 Correlation matrix
A2 Survey answers
Q1 - Who benefits most from generating leads?
Answer % Count
Myself 0.00% 0
The customer 8.57% 3
The sales representative /account
manager 22.86% 8
customer care managers 0.00% 0
Management Team 0.00% 0 The company 68.57% 24 I have no idea 0.00% 0 Total 100% 35
Q2 - How do you feel about the monetary incentive you receive for a converted lead?
Answer % Count
I don't pay attention to it 48.57% 17
I think it's too high 0.00% 0
I think it's too low 34.29% 12
I don't generate leads 5.71% 2
I think it's exactly right 11.43% 4
I don't need a monetary incentive 0.00% 0
Total 100% 35
Q3 - Leads: before and during customer contact. To what extent do you agree with the following statements?
Question Strongly agree Agree Neutral Disagree Strongly disagree Total
Leads are important for the future
of the company 65.71% 23 28.57% 10 5.71% 2 0.00% 0 0.00% 0 35
I'm actively trying to generate leads 5.71% 2 40.00% 14 40.00% 14 14.29% 5 0.00% 0 35
I have the right skills and
knowledge to generate leads 11.43% 4 28.57% 10 40.00% 14 17.14% 6 2.86% 1 35
I think it's easy to generate leads 0.00% 0 17.14% 6 37.14% 13 42.86% 15 2.86% 1 35
The incentive promotions motivate
me to generate leads 5.71% 2 31.43% 11 42.86% 15 8.57% 3 11.43% 4 35
I keep track of the amount of leads I
generate 8.57% 3 31.43% 11 14.29% 5 25.71% 9 20.00% 7 35
During customer contact I create
the opportunity to generate a lead 5.71% 2 28.57% 10 40.00% 14 25.71% 9 0.00% 0 35
I generate more leads than the
co-workers in my team 0.00% 0 5.71% 2 31.43% 11 40.00% 14 22.86% 8 35
I feel confident when I try to
generate a lead 5.71% 2 28.57% 10 48.57% 17 17.14% 6 0.00% 0 35
I feel satisfied by my work as
customer care representative 11.43% 4 65.71% 23 20.00% 7 2.86% 1 0.00% 0 35
I feel motivated by the customer
care managers to generate leads 11.43% 4 54.29% 19 28.57% 10 5.71% 2 0.00% 0 35
Q4 Leads: de lead is converted. To what extent do you agree with the following statements?
Question Strongly agree Agree Neutral Disagree Strongly Disagree Total
I have a great influence of the outcome of the lead (if its
converted) 2.86% 1 17.14% 6 25.71% 9 42.86% 15 11.43% 4 35
I keep track of the monetary
incentive I receive 2.86% 1 8.57% 3 22.86% 8 34.29% 12 31.43% 11 35
I want to know if a lead has been
converted 54.29% 19 40.00% 14 5.71% 2 0.00% 0 0.00% 0 35
When I generate a lead, I want
everyone to know 2.86% 1 2.86% 1 48.57% 17 28.57% 10 17.14% 6 35
I feel proud when a lead I generated
gets converted 28.57% 10 65.71% 23 2.86% 1 0.00% 0 2.86% 1 35
I feel proud when I generate a lead 22.86% 8 51.43% 18 20.00% 7 2.86% 1 2.86% 1 35
Q5 Leads: the reward. To what extent do you agree with the following statements?
Question Strongly agree Agree Neutral Disagree Strongly disagree Total
The monetary incentive motivates
me to generate leads 0.00% 0 45.45% 15 27.27% 9 21.21% 7 6.06% 2 33
The monetary incentive is in
proportion to the effort it takes to
generate a lead 0.00% 0 21.21% 7 51.52% 17 21.21% 7 6.06% 2 33
The structure of the monetary
incentive program is clear 3.03% 1 30.30% 10 21.21% 7 33.33% 11 12.12% 4 33
I prefer team incentives to
individual incentives 3.03% 1 9.09% 3 54.55% 18 27.27% 9 6.06% 2 33
Q6 Leads: motivation. What motivates you to generate leads (multiple answers possible)
Answer % Count
Extra service for the customer 66.67% 22
Monetary incentive 42.42% 14
Feeling appreciated by co-workers
and customer care managers 24.24% 8
Appreciation from the sales
department 27.27% 9 Other: 24.24% 8 Total 100% 33 Q6 Other: Obtain sales skills Personal development Profits for the company
Added value product portfolio for customers The company needs it
Nothing
Q7 Show on a scale of 0 to 10 how much the following characteristics describe you (if you don't want to answer, choose I don't know)
Question 0 1 2 3 4 5 6 7 8 9 10 Total Competiti ve 1 (3.03%) 1 (3.03%) 0 (0.00%) 0 (0.00%) 2 (6.06%) 4 (12.12%) 10 (30.30%) 5 (15.15%) 8 (27.27%) 1 (3.03%) 0 (0.00%) 33 Fear of failure 2 (6.06%) 3 (9.09%) 3 (9.09%) 1 (3.03%) 5 (15.15%) 5 (15.15%) 12 (36.36%) 0 (0.00%) 1 (3.03%) 1 (3.03%) 0 (0.00%) 33 Team player 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 2 (6.06%) 2 (6.06%) 6 (18.18%) 17 (51.52%) 3 (9.09%) 3 (9.09%) 33 Proactive 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 7 (21.21%) 10 (30.30%) 12 (36.36%) 3 (9.09%) 1 (3.03%) 33 Hesitant 1 (3.03%) 0 (0.00%) 5 (15.15%) 0 (0.00%) 4 (12.12%) 8 (24.24%) 4 (12.12%) 6 (18.18%) 2 (6.06%) 3 (9.09%) 0 (0.00%) 33 Individual 0 (0.00%) 0 (0.00%) 1 (3.03%) 0 (0.00%) 3 (9.09%) 4 (12.12%) 8 (24.24%) 5 (15.15%) 9 (27.27%) 2 (6.06%) 1 (3.03%) 33 Confident 0 (0.00%) 0 (0.00%) 0 (0.00%) 1 (3.03%) 0 (0.00%) 1 (3.03%) 6 (18.18%) 14 (42.42%) 8 (24.24%) 2 (6.06%) 1 (3.03%) 33 Service oriented 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 6 (18.18%) 14 (42.42%) 9 (27.27%) 4 (12.12%) 33 Sales oriented 2 (6.06%) 2 (6.06%) 0 (0.00%) 4 (12.12%) 1 (3.03%) 4 (12.12%) 11 (33.33%) 6 (18.18%) 2 (6.06%) 1 (3.03%) 0 (0.00%) 33
Q8 What do you need from this company to be able to generate (even) more leads? (multiple answers possible)
Answer % Lead training 69.70 % Product training 57.58 % Articulation/ conversation skills training 12.12 % Assertiveness/ self-confidence training 6.06%
More time per customer contact 45.45 % One-on-one coaching 27.27 % Other: 6.06% Total 100% Other:
Joint visits other departments to stimulate connections within the Once in a while product update training
Q9 How many leads do you generate per week on average? 1, 0, 2, 1, 1, 0.5, 2, 3, 2, 2, 2, 1, 1, 0.5, 1, 1, 4, 3, 5, 0, 2, 1, 1, 1, 1, 0, 1, 0.2, 1, 3, 0.5, 2, 0 Q10 How many hours a week do you work on average? 32, 24, 40, 20, 40, 12, 12, 40, 32, 38, 32, 32, 30, 16, 28, 16, 40, 40, 40, 16, 15, 36, 28, 12, 40, 40, 24, 13, 16, 30, 21, 40, 12 Q11 How many generated leads do you expect to be converted in the next 2 weeks? 2, 0, 6, 2, 1, 1, 6, 5, 1, 1, 5, 0, 2, 2, 1, 2, 8, 0, 5, 1, 4, 3, 2, 2, 2, 0, 2, 2, 1, 2, 0, 0, 0
Q12 In which age group are you? Answer % Count 20-24 30,30% 10 25-29 12,12% 4 30-34 15,15% 5 35-39 6,06% 2 40-44 12,12% 4 45-49 18,18% 6 50-54 3,03% 1 55-59 0,00% 0 60-64 3,03% 1 65+ 0,00% 0 Total 100% 33
Q13 In which team are you? Answer % Count Transactional 36,36% 12 Webcare 24,24% 8 Relational 39,39% 13 Total 100% 33
Q14 Enter your personnel number (the answers to this survey are confidential)
Q15 How likely is it that you would recommend this company to a friend of co-worker?
Answer % Count 1 0,00% 0 2 0,00% 0 3 0,00% 0 4 6,06% 2 5 9,09% 3 6 15,15% 5 7 24,24% 8 8 27,27% 9 9 9,09% 3 10 9,09% 3 Total 100% 33
Q16 Can we contact you for further information or questions?
Answer % Count
Yes (I agree that my answers can be accessed by the
company) 33,33% 11
No (the answers stay
confidential) 66,67% 22
