Received Date: October 17, 2016; Accepted Date: November 16, 2016; Published Date: November 21, 2016
Citation: Duzgun F, Yamamoto GT (2016) The Effect of Promoter Incentive to the Smartphone Sales in Retail Chains: A Turkish Case. Int J Econ Manag Sci 5:382. doi: 10.4172/2162-6359.1000382
Copyright: © 2016 Duzgun F. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Mobile Phone market is getting more aggressive and competitive. Smartphone brands are looking for a way to increase their sales, especially in retail business where competition getting tough day by day. Therefore, companies are trying to do their best to increase the sales, for this reason technology stores are becoming important channels for the smartphone brands. These kinds of stores are also suitable for brand which wants to increase their sales in a short period of time. In these stores, dealer’s recommendation has becoming one of the key factors to affect consumer purchase decision in Turkey. The aim of our study is examine promoter incentive affect to the smartphone sales in technology chain stores. Promoters become key elements for the brands. So far, most of brands are allocate their brand promoters in technology stores to go one-step further from the other brands and affect consumer who get in the shop and looking for device. Our key question is if promoter’s sales performance increases for the specific brand with an incentive given by the dealer. We also want to search if there is an increase in specific brand smartphone sales with these incentives given to the sales promoters between all brands in these technology stores. Our expectation of promoter’s sales incentive system has positive affect to the sales. We finalize our study with a causal research designed to give proof for incentive affect with one of the global brand smartphone sales in Teknosa, which is the biggest chain store in Turkey.
Sales; Promoter; Incentive; Retail; Motivation; Smartphone; Mobile phone
Smartphone market continues to increase in all over the world. The worldwide smartphone market has reached a total of 1432.9 million units shipped in 2015, marking the highest year of shipments on record, up 10.1% from the 1301.7 million units shipped in 2014 .
Parallel to global smartphone market status, Turkey also become a potential market for smartphone business due to “monthly smartphone sales” exceed the 1 million in average. Thus, new global brands entering to the market and competition getting tough day by day in smartphone market in Turkey. Due to high competition in the market, brands are looking for a way to increase sales with efficient way. Turkey smartphone market has two main channels; Technology chain superstores (Teknosa, Vatan, Mediamarkt, Bimeks etc.) and Telecom retailers (Turk cell, Vodafone, Turk Telekom, and Mix shops). Technology superstores market share is around 23-28% and Telecom retailers 60-66%. Hence, these two channels are covering around 89% of total market (GFK – December 2015 report).
In Turkey, technology chain stores channel seems more suitable for fast growing brands based on the characteristics of these two channels. Mainly 2-3 technology chains are with around 200 important shops. Telecom retailing is another issue - that needs long-term investment. Smartphone retailing works around with 11.000 shops with different operators and different owners, which requires a successful franchise system. In our research, we wanted to study with technology chain stores that are generally modeled alike in all countries.
Sales and marketing are important for the fast growing brands. They are trying to face harsh competition, with several marketing attempts. According to research done by Akkucuk; Turkish customers are willing to buy smartphone from brands that they are familiar and have more information about them and on the other hand, they never consider any lesser-known brands when they purchase smartphone . Hence Field sales activity is getting important for new growing companies.
In technology stores, dealer’s recommendation is one of the key factors that affect customer purchase decision. Hence, brands are allocating promoters in these chain stores to catch and affect consumer for their products. We wanted to measure whether old method of giving commissions for the promoters are still effective in smartphone market.
Promoters are used for the sales deals in technology stores. Because technology stores their own staff are not concerning deeply to the customers of a specific brand because there are several different products and units. Technology stores’ dealers and brand promoters are mostly young and energetic people, Promoter’s age scale is between 18 and 25. They are mostly students or high school education degree. Most of them are single and have no family responsibilities; hence, job turnover rate is very high in promoter staff. Their base salary is on average level around 350-400 USD and they are open to work hard to get more benefit. They also have good technology knowledge and interest.
We thought that sales incentives for promoters are important to get better results in this competitive environment. The main purpose of this study is to examine promoter incentive affect to the smartphone sales in technology chain stores in Turkey.
We also try to examine global smartphone market and Turkey’s smartphone market initially for the sake of general conditions. We deal with brands status, market share, channels breakdown, and technology superstores status in Turkey smartphone market. We have elaborated general literature about motivation and incentive systems for the sales staff and their motivation factors. Finally, we tried to show how sales person’s incentive system affects smartphone sales in technology stores. Whether there is any difference between general incentives and how this system works. We want to reveal this incentive affect case in Teknosa (Biggest Technology chain store in Turkey) with a causal research design. We also want to verify that sales incentive is still one of the important factors for sales performance on these technology chain stores in Turkey.
Smartphone market status in Global and Turkey
Mobile phones have become excellent devices with many functions much like a computer; phone and other tools and apps with the smart phones entered the market. It became possible to use smartphone as computer in everywhere, and this situation increased the usage rate of mobile phone rapidly and instantly for the end consumer. This is also an opportunity to the users to reach the internet and most of the abilities of computers in hand all around the world.
According to Deloitte report which contains a mobile consumer survey in 14 developed markets between May and July of 2014 found the replacement cycle for smartphones was about 12 months, shorter than tablets, laptops, and TVs. Consumer purchase intention for next 12 months is 32% in smartphone as highest number among all other devices . In Q4 2015 global smartphone shipments became more than 1.4 billion units which means the market is hitted the record (Figure 1).
Smartphones are multifunctional devices and include many features in one device. People are not sensitive about price and are ready to buy all in one device with high price. Smartphone is also a high tech and expensive product and has many technological features that most of people need assistance to be able to use it properly. Most of the people consider recommendations while purchasing technology products due to the lack of personal experience about this new technology.
According to Statista the number of smartphones sold to end users has increased worldwide from 2007 to 2014. In 2008, 139.29 million smartphones were sold worldwide. In the third quarter of 2011, 52.5% of all smartphones sold to end users were phones with the android operating system.
In 2013, the number of smartphones sold to consumers stood at over 969 million units, an increase of over 50% on the Figure 2 from 2011. This means that almost 20% of the world’s total population owned a smart device in 2013, a figure that is expected to increase to 34% by 2017. In the same year smartphone penetration is set to reach 62.2% in North America and 65.8% in Western Europe. This is a large rise in the 29.3% of people in North America and 22.7% of Western Europeans who had smartphones in 2011.
In the United States alone, sales of smartphones are projected to be worth over 40 billion U.S. dollars in 2014, an increase from 18 billion dollars in 2010. By 2017, it is forecast that almost 80% of all mobile users in the United States will own a smartphone, an increase from the 26.9% of mobile users in 2010. The Chinese smartphone market is also on the rise with over 538 million units of smartphones forecast to be sold in 2016. This is a huge increase on the 80 million that were sold in 2011 .
In 2015, market is growth 25% and reached to 12 million units. Smartphone sales quantity is around 1 million unit/ monthly in Turkey (Figure 3). Turkey is a potential market for Smartphone companies; almost all players of global companies like Apple, Samsung, LG, Sony and HTC are facing harsh competition in Turkish market. Apple and Samsung are dominating market with 40% and 31% market share respectively. Hence, competition getting tough between rest of the brands (LG, Sony, HTC, General mobile, Huawei etc.). However Turkish customers’ behavior makes Turkish market more difficult for small brands. As Akkucuk mention Turkish customers say they will keep purchasing from their smartphone brand even if its price be higher than that of competitors which again illuminates that they are highly loyal to their smartphone brands. It means you are not able to compete with pricing strategy in Turkey. Competition also getting tough in global as well. Because market grow rate is decreasing comparing to previous years. Growth rate decreased from 28% to 10 % as in Figure 3. Because of the current market competition status, sales activities and field sales strategies is getting very critical to increase sales and market share in potential Turkish market (Figure 4).
If we analyze the Turkey’s smartphone sales channel status according to Figure 5, operator channel (Turkcell, Vodafone, Avea and mix shops) share is around 65% and Technology superstores (Teknosa, Medimarkt, Vatan, Bimeks etc) share is around 25%. Rest of the share, 10% which is mass merchandising channel (Carrefour, Metro, Online seller etc) and Electronic trade channel (Samsung shop, LG shop, Sony shop, Arcelik etc). TCR (Telecom Chain Retailer) Operator channel has around 3400 (Turkcell TIM, Vodafone shop, Avea shop) and 8900 Mix shops, total around 12.300 shops. Due to its huge number of shops, it is very difficult to make sales activity and touch them in a short period. Operator channel is suitable for long-term investment.
TSS (Technology Super Store) Channel has around 600 stores and Teknosa is the biggest chain in TSS channel. Teknosa belong to one of the biggest holding group, Sabancı Holding. Teknosa market share is around 40% in TSS channel and monthly smartphone sales quantity of Teknosa is around 90.000 Units in 280 stores in Turkey. TSS channels are fast moving and responding channels comparing to operator channels. Hence TSS channel is suitable for short term investment due to fast responding and resulting channel. The one of the key factor to influence consumer preference is sales person recommendation in these stores. Because of that reason most of the famous and big brands are locating their own sales staff (sales promoters) in TSS stores to catch and effect customer purchase preference for their products in shops. We want to analyze the sales promoter staff’s motivation factors for the brand’s sales performance.
The summary Table 1 of Literature review for motivation is below:
|Sl. no.||Dimension||Author(s)||No. of citation|
|1.||Training||Commeiras et al. (2013); Panagiotakopoulos (2013); Williams (2013); Lazazzara and Bombelli (2011); Gegenfurtner et al. (2009); Gegenfurtner et al. (2009); Noe (2009); Rowold (2007); Bell and Ford (2007); Klein et al. (2006); Tai (2006); Chiaburu and Tekleab (2005); Kontoghiorghes (2004); Tsai and Tai (2003); Tharenou (2001); Kirkpatrick (2000);Colquitt et al.(2000); Seyler et al. (1998); Kirkpatrick (1996); Facteau et al.(1995); Cannon-Bowers et al. (1995); Whitehill and McDonald (1993); Clark et al. (1993); Mathieu et al. (1992); Baldwin et al. (1991).||25|
|2.||Monetary incentives||Beretti et al. (2013); Panagiotakopoulos (2013); Aguinis et al. (2013); Szczepanowski et al. (2013); Schultz and Brabender (2013); Pouliakas (2010); Feldman and Lobel (2010); Park (2010); Jain et al. (2007); Rose et al. (2007); Zhang and Wu (2004); Linder (1998); Leung et al. (1996); Nelson (1996); Rowley (1996a, b); Kovach (1995).||16|
|3.||Job transfer||Azizi and Liang (2013); Swift and Hwang (2013); Asensio-Cuesta et al. (2012); Casad (2012); Datta and Eriksson (2012); Eguchi (2004); Zhang and Wu (2004); Cosgel and Miceli (1999); Cheng and Brown (1998); Ichniowski et al. (1997).||10|
|4.||Job satisfaction||Pantouvakis and Bouranta (2013); Pravin and Kabir (2011); Wickramasinghe (2009); Kaliski (2007); Saari and Judge (2004); Williams et al. (2003); Bussing et al. (1999); George and Jones (1997).||8|
|5.||Promotion||Steidle et al. (2013); Koch and Nafziger (2012); García et al. (2012); Jung and Kim (2012); Syed et al. (2012) Pravin and Kabir (2011); Lindner (1998); Kovach (1995).||8|
|6.||Working conditions||Cheng et al. (2013); Jung and Kim (2012); Pravin and Kabir (2011); Dundar et al. (2007); Lindner (1998); Kovach (1995).||6|
|7.||Achievement||Hunter et al. (2012); Sarkar and Huang (2012); Satyawadi and Ghosh (2012); Yang and Islam (2012); Muchiri et al. (2012).||5|
|8.||Appreciation||Mahazril et al. (2012); Kingira and Mescib (2010); Lindner (1998); Nelson (1996); Kovach (1995).||5|
|9.||Recognition||Candi et al. (2013); Barton and Ambrosini (2013); Mahazril et al. (2012); Javernick-Will (2012).||4|
|10.||Job security||Yamamoto (2013); Pravin and Kabir (2011); Zhang and Wu (2004); Cheng and Brown (1998).||4|
|11.||Social opportunities||Harvey (2013); Panagiotakopoulos (2013); Kingira and Mescib (2010); Rowley (1996a, b).||4|
Table 1: Motivation dimensions.
On that dimensions we focus on monetary incentives and made explanatory research for high technology products smartphone in our study.
As summarized by Park, monetary incentive acts as a stimulus for greater action and inculcates zeal and enthusiasm toward work; it helps an employee in recognition of achievement . Likewise, Beretti et al. discussed that monetary incentives used to build a positive environment and maintain a job interest, which is consistent among the employee and offer a spur or zeal in the employees for better performance. For reason, monetary incentive motivate employees and enhance commitment in work performance, and psychologically satisfy a person and leads to job satisfaction, and shape the behavior or outlook of subordinate toward work in the organization .
Sales promotions and motivation of the sales person
Sales promotions, service quality are important factors for the sales. These promotions and types are changing time to time according the product/service features. Sales promotions have one of the strongest impacts on short-term consumption behavior within the retail marketing mix. Sales promotions are beneficial to retailers in several aspects: First, promotional variables such as in-store display and ‘‘two-for-one’’ are often used to trigger unplanned purchases. Second, sales promotions encourage consumers to purchase no promoted merchandise. Finally, sales promotions accelerate the number of shopping trips to the store .
Beside the sales promotions, retailers are focusing on providing excellence in service quality.
Qualified sales people and qualified service and sales promotions are becoming more important to technology stores like the other businesses.
Service quality depends strongly on the attitude and behavior of retail salespeople. As customer contact personnel, they are responsible for putting strategy into operation in their encounters with customers in retail outlets .
According to Rackham and De Vincintis sales people are not only communicate value but also must create it. Blockeretal similarly emphasized the importance of the sales force in relationship marketing and its contribution in generating value for the seller and the customer. Building relationships with customers is thought to increase customer satisfaction and loyalty, increase the amount of favorable word of mouth they exhibit and increase purchases, and having a positive relationship contributes to positive relationship outcomes such as trust and trust in the retail salesperson should lead to customer commitment to the consumers who maintain salesperson relationships do so to fulfill certain desires or needs by obtaining benefits from these relationship .
Relationship marketing is typically described as being oriented toward a long time horizon in contrast to the short-term orientation that existed in marketing before 1983. Berry and Parasuraman hold that relationship marketing consists of attracting, developing, and retaining customers. Morgan and Hunt refer to it as all activities directed toward establishing, developing, and maintaining successful relational exchanges. According to Grijnroos, the objective of relationship marketing is not only to acquire customers but to keep them as well. Moreover, in this “new philosophy,” customer satisfaction becomes the responsibility of everyone in the organization. People in other departments must share the responsibility of dealing with customers. Hence, the concept becomes instrumental in coordinating the activities of all departments, with the marketing function playing a pivotal role in the success of the firm .
Theodore Levitt , made the point that “consumer don’t buy products, they buy benefits” with an example “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” This simple idea has been the platform for success for companies as diverse as Procter & Gamble, Amazon and Rolls – Royce. When marketers do this, they often solve the wrong problems, improving their products in ways that are irrelavent to their customer needs .
Purchasing choices and motivated sales person effect
Retail sales people performance -in shop- is important tool to create value for consumer and match the provided service or product with consumer needs. From a marketing point of view, two main distinctions are made regarding the concept of value: value of goods and services and value of buyer–seller relationships. The first research stream is strongly linked to the monetary aspect of value. Anderson and Narus define value as “the worth in monetary terms of the technical, economic, service, and social benefits a customer company receives in exchange for the price it pays for a market offering” (1998: 54). The second research stream on buyer–supplier relationships takes a less measurable approach where value is seen as reputation, relationship quality, trust, customer satisfaction and customer retention . Consumers are often influenced by the purchase choices of others when they make their own purchase choices .
As Román and Iacobucci indicate, there is no bestway to sell; rather, salespeople must adapt to the situation and the customer. According to Weitz, and Sujan's seminal “adaptive selling” framework, salespeople must gather information and then tailor their sales presentation to fit each customer. Anglin, Stoltman, and Gentry added that salespeople must observe their customers' reactions and then make real-time modifications to their sales presentations. Studies on adaptive selling have frequently focused on the characteristics of the salesperson and his or her sales performance or sales effectiveness. While retail employees are responsible for a wide variety of tasks, their ability to sell effectively is certainly one of the most important. As a result, retailing researchers and managers are highly interested in understanding the major controllable factors associated with increased employee sales performance .
Sales employees are important contributors to the financial performance of many businesses. A common mechanism managers use to bolster salespeople performance is incentive compensation programs. These programs provide sales employees with the opportunity to earn rewards based on their sales performance. Incentive compensation programs also build a mutually beneficial relationship between the company and the salespeople which makes alignment of the organization’s goals with the salespeople’s goals . Compensation mechanisms can be powerful incentives in linking performance to rewards. Compensation systems that reward people directly based on how well they perform their jobs are known as pay-forperformance plans. These may take such forms as “commission plans” used for sales personnel, “piece-rate systems” used for factory workers and field hands, and “incentive stock option (ISO) plans” for executives and other employees. However, rewards linked to performance need not be monetary. Symbolic and verbal forms of recognition for good performance can be very effective as well .
Despite the most of the research supports that financial compensation increase sales people performance; some of study claims that; financial compensation is not only factor to increase performance of sales people.
Motivating employees is essential for any organization aspiring to succeed. However, the process of motivating is not a straightforward one due to the diversity of individual’s needs. The task has been made even more difficult by the fact that personalized needs have altered in recent years. For instance, in many circumstances financial compensation is not considered as the main motivational factor of employees . In our research, we will not consider other factors for sales people motivation; we will only focus financial support affect (incentive system) to sales people performance.
Incentive is an individual psychological process, which inspire, guide, maintain and regulate an individual to achieve an established goal through effective self-regulation under the effect of the external stimulation. From 1950s, incentive theory was booming increasingly. The theory includes Maslow's hierarchy of needs theory, Herzberg's Two-Factor Theory , Skinner's Reinforcement Theory , Drucker’s Management by Objectives  and the Adams’ Equity Theory. Some Western scholars have gradually formed a number of supplementary and complementary theories on the basis of the above-mentioned theories. Lawler’s Expectation Theory brought up the opinion that money could only motivate staff in the following three conditions: first, the sum of money itself was huge enough to be tempting; second, the staff could get the expected money after they had finished their work. Third, the staff improved their work performance through their own efforts. Dweck believed that goal orientation was quite stable variables, which were significantly associated with the incentive methods to reflect the individual differences. Western scholars believe that monotonous work will make employees experience depression and frustration, and even seriously affect their physical health and work efficiency. On the contrary, work enrichment may allow employees to feel comfortable so as to increase work efficiency.
People are pulled toward behaviors that offer positive incentives and pushed away from behaviors associated with negative incentives. In other words, differences in behavior from one person to another or from one situation to another can be traced to the incentives available and the value a person places on those incentives at the time .
Building on the base established by drive theories, incentive theories emerged in the 1940s and 1950s. Incentive theories proposed that behavior is motivated by the "pull" of external goals, such as rewards, money, or recognition. It's easy to think of many situations in which a particular goal, such as a promotion at work, can serve as an external incentive that helps activate particular behaviors .
The incentive theory suggests that people are motivated to do things because of external rewards. For example, you might be motivated to go to work each day for the monetary reward of being paid. Behavioral learning concepts such as association and reinforcement play an important role in this theory of motivation.
This theory shares some similarities with the behaviorist concept of operant conditioning. In operant conditioning, behaviors are learned by forming associations with outcomes. Reinforcement strengthens a behavior while punishment weakens it.
While incentive theory is similar, it instead proposes that people intentionally pursue certain courses of action in order to gain rewards. The greater the perceived rewards, the more strongly people are motivated to pursue those reinforcements .
This study could be linked to Expectancy Theory due to propose to examine the importance of sales person incentive.
Expectancy theory is about the mental processes regarding choice, or choosing. It explains the processes that an individual undergoes to make choices. In the study of organizational behavior, expectancy theory is a motivation theory first proposed by Vroom. "This theory emphasizes the needs for organizations to relate rewards directly to performance and to ensure that the rewards provided are those rewards deserved and wanted by the recipients." .
According to this theory, individuals ask themselves three questions. The first question is whether the person believes that high levels of effort will lead to outcomes of interest, such as performance or success. This perception is labeled expectancy. The second question is the degree to which the person believes that performance is related to subsequent outcomes, such as rewards. This perception is labeled instrumentality. Finally, individuals are also concerned about the value of the rewards awaiting them as a result of performance. The anticipated satisfaction that will result from an outcome is labeled valence .
Expectancy theory is based on four assumptions. One assumption is that people join organizations with expectations about their needs, motivations, and experiences. These influence how individuals react to the organization. A second assumption is that an individual’s behavior is a result of conscious choice. That is, people are free to choose those behaviors suggested by their own expectancy calculations. A third assumption is that people want different things from the organization (e.g., good salary, job security, advancement, and challenge). A fourth assumption is that people will choose among alternatives to optimize outcomes for them personally. The expectancy theory based on these assumptions has three key elements: expectancy, instrumentality, and valence as stated before. A person is motivated to the degree that he or she believes that (a) effort will lead to acceptable performance (expectancy), (b) performance will be rewarded (instrumentality), and (c) the value of the rewards is highly positive (valence) (Figure 6).
Vroom suggests that motivation, expectancy, instrumentality, and valence are related to one another by the equation Motivation= Expectancy x Instrumentality x Valence. The multiplier effect in the equation is significant. It means that higher levels of motivation will result when expectancy, instrumentality, and valence are all high than when they are all low.
Vroom’s expectancy theory differs from the content theories of Maslow, Alderfer, Herzberg, and McClelland in that Vroom’s expectancy theory does not provide suggestions on what motivates organization members. Instead, Vroom’s theory provides a process of cognitive variables that reflects individual differences in work motivation
Lawler has developed an expectancy model of behavior the model also argues that job behavior is a joint function of ability, role perceptions and motivation. Maier has defined behavior as a result of the multiplicative interaction of motivation and ability. LaMer and Porter added the concept of role perceptions, defined as "the kinds of activities and behavior the individual feels he should engage in to perform his job successfully (p. 130)" .
Expectancy theory has evolved in recent years as a basic paradigm for the study of human attitudes and behavior in work and organizational settings. A number of expectancy-type models have been stated, and they have been frequently used as theoretical and operational definitions of motivation. Although the exact form of the expectancy models described by different writers has varied considerably, most of these variations have been due more to differences in terminology than to conceptual disagreements.
According to Venkatesh  Porter and Lawler came up with a comprehensive theory of motivation, combining the various aspects that we have so far been discussing and using two additional variables in their model. Although most parts are based on the Vroom’s expectancy model Porter and Lawler’s new model is a more complete model of motivation. This multi variety model has been practically applied to managers which explain the relationship that exists between job attitudes and job performance.
This model is based on four basic assumptions about behaviors:
(i) It is a multi variate model. According to this model, personal behavior is determined by a combination of factors in the individual and his/her environment.
(ii) Individuals are assumed to be rational human beings who make conscious decisions about their behaviour in the organizations.
(iii) Individual’s needs, desires and goals are diverse.
(iv) Individuals decide between alternate behaviors and such decided behavior will lead to a desired outcome on the basis of their expectations.
Porter and Lawler used Vroom’s expectancy theory as a foundation to develop their expectancy model. Similar to Vroom’s theory, Porter and Lawler concluded that a person’s motivation to complete a task is affected by the reward they expect to receive for completing the task. However Porter and Lawler introduced additional aspects to the expectancy theory. The Porter-Lawler theory stresses intrinsic and extrinsic rewards, task requirements and ability, and the perceived fairness of rewards .
Porter and Lawler model has definitely made a significant contribution to the better understanding of work motivation and the relationship between performance and satisfaction.
Even then, to date, it has not made much impact on the actual practice of human resource management. In this model there are two significant things stated by Venkatesh these are appropriate reward association with the performance and rewards dispensed should have a value on the employee side that we have trying to search from the actual reward system. In our research, we try to make actual practice for reward system impact to employee satisfaction level and work performance accordingly.
We consider only extrinsic reward in our model and our restrictions are Value of Reward, Effort and Performance of employee satisfaction. Our assumption is; other factors of sales result -reputation, relationship quality, trust, customer satisfaction and customer retention- are constant [32-34].
Right sales actions are getting critical for companies due to the smartphone market are getting important and competitive. Our aim is to find out if sales person performance increases with an incentive for selling smartphone products in Technology super stores. In this manner we believe this research will also help smartphone companies in case of planning sales activities and strategies in future.
We have made this research in selected 30 Teknosa stores in different cities in Turkey, which have one of the selected big brand’s promoters. Teknosa is the biggest technology chain store in Turkey and has 40% market share in Technology stores channel. Other chain stores are Medimarkt, Vatan and Bimeks. Teknosa customer segment is mid-high and has biggest coverage with almost 280 shops. In Teknosa first 30 shops are covering almost 40% of sales and they have highest consumer traffic. Hence, we can say that we will be able to make enough sampling with our selected 30 shops, which are biggest technology shops and have highest consumer traffic technology stores in Turkey [35-38].
The list is selected Teknosa shops are shown Table 2.
|1||ADANA SABANCI İŞ MERKEZİ EXXTRA|
|2||İZMİT GEBZE CENTER EXXTRA|
|3||İSTANBUL KADIKÖY TEPE NAUTILUS EXXTRA|
|4||İSTANBUL MALTEPE CARREFOURSA EXXTRA|
|5||GAZİANTEP SANKOPARK EXXTRA|
|6||MERSİN FORUM EXTRA|
|7||BURSA CARREFOURSA EXTRA|
|8||İSTANBUL EYÜP VIALAND EXXTRA|
|9||TEKİRDAĞ TEKİRA EXTRA|
|10||ANTALYA KEPEZ ÖZDİLEK EXXTRA|
|11||TRABZON FORUM EXTRA|
|12||İZMİR FORUM BORNOVA EXTRA|
|13||İSTANBUL MARMARA FORUM EXXTRA|
|14||İSTANBUL ŞİŞLİ CEVAHİR EXXTRA|
|15||ADANA OPTIMUM YENİ|
|16||BURSA KENT MEYDANI EXXTRA|
|17||İSTANBUL MARMARA PARK|
|18||ANKARA NATA VEGA EXTRA|
|19||İSTANBUL FORUM EXXTRA|
|20||TEKİRDAĞ ÇORLU ORION|
|21||İSTANBUL SEFAKÖY ARMONİPARK OUTLET EXTRA|
|22||ANTALYA MARKANTALYA EXXTRA|
|23||ANTALYA TERRACİTY EXXTRA|
|24||ANKARA ANKAMALL EXTRA|
|25||ANKARA ANKAMALL 2 EXTRA|
|26||ADANA M1 EXXTRA|
|27||İZMİT OUTLET CENTER EXTRA|
|28||İSTANBUL PENDİK NEO EXTRA|
|29||İZMİR GAZİEMİR OPTIMUM|
|30||İZMİR KARŞIYAKA KEMALPAŞA CADDESİ|
Table 2: Teknosa Shop List.
We compared the sales in 2 months between March 2016 - April 2016, first month there was no extra promoter incentive and second month we started extra promoter incentive programme for selected product.
With this research we also want to measure the impact of sales person recommendation affect to customer purchase decision. Hypotheses for this research is following
H1. Sales person recommendation affects customer purchase decision
H2. Sales person incentive system effect sales person performance
Our research type is causal research. We set out our casual research from the following assumptions: “If there is a dealer incentive in technology superstores it affects sales performance and if there is sales person recommendation this affects the consumer purchase decision and sales of a product”. We want to measure the impact of dealer incentive in sales results.
Data source is the secondary data which taken from Teknosa and Smartphone Company’s sales records database during the research period (2 months between March 2016 - April 2016) (Figure 7).
Our limitation of this research is only financial incentive which comes from the dealer side has taken into consideration and no other affects such as competitor’s in store marketing status, competitor’s promotion status, seasonal purchasing status, Chain store’s marketing activities have not addressed (ATL & BTL).
Additionally, our research measured promoter’s performance only certain period and only certain technology superstores.
We have measured 30 Teknosa shop’s sales quantity of selected brand, with comparing without incentive and with incentive period. Incentive amount is applied as 24 TL per product. 24 TL almost equal to 12 USD and promoters average monthly fix salary is around 400 USD.
To be able to measure incentive affect correctly, selected brand’s in store marketing and other promotional conditions is not changed and kept in same status during the measurement period (Table 3).
|Shop name||Sales Quantity for Model A|
|March 2016||April 2016|
Table 3: Promoter performance comparison table.
As a result, we observed that incentive has positive affect to sales increase in Teknosa retail shops. Average increase rate of 30 shops is 475%. Sales have boomed with these incentives in these technology stores with the dealer incentives. Hence, we can accept our hypothesis as sales incentive has positive correlation with dealer recommendation and sales performance.
Smartphone market is very competitive and companies looking for a way to increase their sales in Turkey. All companies are using many competition tools in marketing and sales area. Allocating the brand sales staff (Promoters) in stores is one of popular way for sales action. Improving the motivation and sales performance of promoter is always become an important question for companies. Because promoter investment is expensive and ROI is very important for effective budget planning. In our research, we have reviewed smartphone market status and sales channel status to better understanding the market and analyzing the incentive affect results. With this research we have analyzed sales person (promoters) recommendation is effective to customer purchase behavior and financial sales incentive per product has an effect to sales person performance in Technology superstores in Turkey’s smartphone market. We took only one sales staff motivation factor examined in literature review with expectancy theory, which matches with our research. Our research result has supported expectancy theory about staff motivation factors. We have used causal research model that we want to check output value (sales result) with changing input value (sales incentive).
The main question is if financial promotions are efficient to increase sales in a specific channel given by the smartphone dealer, which is named as “Promoter incentive.” If this kind of incentive works for increasing sales in the Turkish smartphone market, all brands may consider this way as a sales activity and make budget planning according to promoter sales incentive per product. In our study, we have compared non incentive-applied month and incentive-applied month sales performance of top 30 stores. Result showed that incentive is increased the sales performance almost 5 times (475%). Our study shows that promoter incentive is very effective way in technology superstores due to recommendation and taking care of consumer of promoters in the technology super stores resulting positively. In addition, we can say that incentive for promoters is very effective way to increase sales person’s motivation and sales performance. As mentioned in introduction section, promoters are 18-25 aged people and they have average level of income. If promoters are increasing their income, their motivation will increase and job turnover will decrease accordingly.
This study also support that sales person- consumer relationship is important for sales performance, especially in face-to-face sales field. Sales person’s recommendation is very important for technology products and most of people looking for advice from expert for buying new technology product like smartphone.
Further research can be for budget planning with considering promoter incentive while defining new product price or find answer about product price and incentive budget; whether incentive amount should add product price and apply incentive or discount the incentive amount from product price and selling product without incentives or other incentive effects could also be observed.