Manage-men-t of People Mix: An Essential criteria for Technical Education

 

Mahajan P.T.^1*, Golahit S.B. ²

¹Research Scholar and Registrar, R. C. Patel Institute of Technology, Shirpur, Maharashtra, India

²Head, Department of Economics, SPDM College, Shirpur, Maharashtra, India

 

ABSTRACT:

Purpose: There is a rapid growth of technical education in last decade in terms of the no. of institutes and intake capacity in India but with improper and non-directional development. As per AICTE reports, there is noticeable gap in between the actual no. of enrollments and intake capacity of these institutes. In the year 2015-16, 46% of seats were vacant in Technical Education in India. Segmentation and ‘People’ factor of service mix is very important aspects in education services. The purpose of this paper is to highlight the Manage-Men-T; Management of People through Technology for selecting Technical Education Institute. And their influence on diversity; geographical and demographical factors of students in selecting technical educational institute.

Design methodology: A qualitative research was conducted with a survey of students those who are presently enrolled (pre-students) and those who have completed their study (post-students) belonging to the institutes offering technical education situated in Khandesh region of India and affiliated to the North Maharashtra University, Jalgaon.

Findings: The study found that geographical and demographical factors of students are highly related with the people mix in selection of technical educational institute.

Research limitations: The survey is limited to the students of technical education belonging to North Maharashtra University, Jalgaon and located in Khandesh region of India.

Practical implications: Several studies have revealed that the marketing segmentation of technical education will be better developed if we consider geographical and demographical factors and then implementing people mix. It is found that there are some People mix - influencers - related to the institute and previous schools along with peoples associated with the students that are associated with geographical and demographical factors. So, it is useful to consider this association rather than considering only traditional factors. This article provides empirical support for the importance of such factors and their effect on educational choices. Different communication strategies of people mix can be used based on geographical and demographical factors which will proceed to not only growth but development of technical education in proper direction also. The paper represents new form of geographical and demographical factors with various people mix of educational service, that together affects students’ decision in selecting their technical educational institute.

 

 

 

INTRODUCTION:

As technical education (TE) in India is turning more competitive, it has become necessary for TE institutions to engage in strategic marketing. More than promotional activities, strategic marketing involves to draw students toward the institution; it should also include market segmentation and positioning [1]. The reason why segmentation is important and timely is that universities and institutes are currently struggling with how to best serve their learners in the face of declining financial resources, increased calls for accountability by Government, increasing competition among institutions and more discerning students, particularly those referred to as the ‘millennials’ [2]. While some prospective students share similar characteristics but most of them are not similar as per gender, age, geographical location, parent’s income etc. Students with similar characteristics can be grouped and can be yielded for definable segments. Lewis and Smith observed that every college and university has a mission but very few fully identify who they serve [3].

 

Customers of educational services are classified as Internal customers; students, staff and management and External customers such as parents, other schools and colleges, alumni and community [4].The institute searching process is a long one. McDonough (2004) stated that the transition/searching process begins during the middle school years. Students begin to develop college awareness and ideas of academic aspirations. During 10^th(SSC) and 12^th (HSC) students began looking for schools that meet their needs socially and academically (McDonough 2004).After searching internal sources, if the student realizes that the information gathered is not enough to base on and decide, external sources of information are considered. People Factor such as; Parents, Brother and Sisters, Relatives, Friends/Peer, Current and Post students of institute, previous School/Coaching Teachers, Staff and Management People of Institute, act as a reference group for the pre-students (prospective students) to take their decision on institute selection. Reference Group is the group to which the individual relates or aspires to relate himself or herself psychologically and a source for framing his or her experiences, perceptions, cognition, and ideas of self. Robert K. Merton hypothesized that individuals compare themselves with reference groups of people who occupy the social role to which the individual aspires [5]. There are several people who influence a student’s institute decision, but their degree of impact on students varies from school to school [6].

 

SEGMENTATION

Two broad groups of variables are used to segment customer market; Geographic and Demographic segmentation as these are measurable, substantial, accessible, differential and actionable. Geographic segmentation calls for dividing the students prospective market into different geographical units such as urban/rural, state and distances of their native place from institute etc. In demographic segmentation, the prospective students are divided as per the variable like; age, gender, parent’s income, parent’s occupation and qualification. Demographic variables are the most popular bases for distinguishing customer’s groups [7]

People factor of Service Mix

The tradition four Ps marketing approaches work well for goods but additional elements require attention in service business; People, Physical Evidence and Process. Because most services are provided by the people and experienced by the people by their motivation and behavioral characteristics, they make a huge difference in customer satisfaction. This is the main principle of service management; ‘By the people for the people’.

 

Parents:

The home setting is a particularly rich and ongoing source of information for college-educated families [8].The collision between the worlds of institute and of home and family must be understood by institutions as lower-income students become more prevalent [9]. Many studies have connected parent support and encouragement to institute plans [10]. Parents are main source of financial aspects; however, their support is determined by the education level. When parents lack firsthand “institute knowledge” and have limited financial and social resources, they consequently have a lessened capacity to facilitate institute planning [11]. According to Hossler, Schmit and Vesper (1999), parental support was a key factor in influencing students' aspirations to go onto college. Typically, students whose parents did not attend college/institute graduation find it more difficult to address the issues related to choose, chances, and application needs when it comes to college. Typically, these students begin thinking about institute much later than do students who have parents and family members who have attended higher education institutions.

 

Brothers and Sisters:

When parents are not educated or unknown about the institutes, the supporting information is provided by the siblings. However, graduate elder siblings or undergoing graduate siblings have a major role in the decision of selection. In rural area where the parents are uneducated and are unable to provide information, elder siblings play a vital role even; they become a financial source for the pre-students if they are employed.

 

Relatives:

Relatives are contacted, particularly those are residing in urban area, as they supposed to have more knowledge on the institutes and programs. Students contact their relatives for getting information on cost involved in the related education and for knowing number of colleges/institutes available in the urban area and compare them with the budget.

 

Friends / Peer:

If students are exposed to other individuals such as friends, who have studied in that institute, students will often rely on those individual for their valuable guidance on campus life, infrastructure, teaching methodology, examination pattern etc. A peer group of friends, is both a social group and a primary group of people who have similar interests, age, background, or social status. They prefer to talk about school and their careers with their parents and other interpersonal relationships with their peers[12]. Peer influence is dependent upon variables of friendship closeness, high school track placement, race, and gender composition of the relationship [13]. Intuition reinforces the finding that peers who are academically-oriented are an asset for career aspirations [14]. Peer influence for these youths appears to be the most influential factor in the decision about institute [15]. But if those peer effects are asymmetric so that students at different levels of behavior or characteristics are influenced differently by their interaction with others, then peer effects introduce an issue of economic efficiency, too. Taylor (1992) is of the belief that friends' advice is the major source of information influencing students' choice of tertiary educational institutions.

 

School / Coaching teacher:

Students do report the desire for a quality high school counselor who might guide them through a process that seems daunting, complicated and time-consuming [16]. School counsellor can increase the confidence of families who may otherwise shy away from the institute. Parents' discussions with counselors are a significant step toward in making institute decision, which highlights the benefits of cultivating early positive parent-counselor relationships [17]. Students who do not have family members who have attended institute often look towards the school as their main support. The school creates the environment closest to the institute setting for these students. School and coaching teachers act as a career advisor.

 

Staff of Institute:

While there are undoubtedly numerous factors that influence to enter the technical education, the relationships built during formal and informal counselling exercises adopted by the institute can affect personal decisions. Counseling by institute staff is necessary for students when preparing for institute, as they are the measures of service delivery. "We know that counselors influence students' aspirations, plans, enrollments, and financial aid knowledge. Meeting frequently with a counselor increases a student's chance of enrolling in a four-year institute, and if students, parents, and counselors work together and communicate clearly, students' chances of enrolling in college significantly increase". An institution's own members of staff, through telephone conversations and email correspondences to prospective students, also play a major role in influencing student choice decision.

 

Management of Institute:

Management people are the in-direct source of influencers. These people are the main service providers in the education services. Here, pre-students may not approach management people, however, pre-students have a perceived value or an image for the management and brand of the institute. Management people communicate their culture, style and brand through their publications, sponsored programs, paid and non-paid sources of advertisements and social events. Pasternak (2005) pointed out that the information given by the management through institution's own printed materials is also very influential in student choice process. Despite numerous sources of information, there is still a general lack of adequate information for prospective students and their parents to make meaningful comparisons among universities offering the same or similar academic program, due to poor and less informative and promotional materials designed by the managements of educational institutions.

 

Current-students (Prospective Students):

Current-students are the real experience holder of the service which is offered by the institute as they are currently in touch with the service and facilities of the institute. They are the real word of mouth for the institute as well as for the pre-students. But, their positive message delivered to the pre-student will depend on the type of experience they are receiving. However, families reveal a growing trend in which current-students commonly identify parental encouragement as a primary reason for deciding selection of institute[18]. Pre-student approaches current-students to update recent information regarding the institute as all other resources may provide old information regarding the institute. Again, they may verify the information provided by the other resources with the current-students. Pre-students often associate themselves with other individuals who have experienced the same cultural and social experiences and compare their institute going behaviors with those who are attending institute now.

 

Alumni (Post-Students):

Alumni are the finished product of the educational institutes. They had experienced a service and are in the perfect position to tell the value of that service in the present market. Alumni share common characteristics and interest with the pre-students. Pre-students take information from the Alumni for the future scope and value of educational program provided by the institute. However, opinion and the information provided may be different from alumni to alumni depending on the services and the level of satisfaction the alumni received from institute. 

 

Pre-Student themselves:

Pre-students take their decision mostly after collecting all information from all available sources and compares them with their personal factors. Most pre-students after collecting primary information from school teachers, friends, family prefer to visit directly to the concerned institute to verify physical evidence. They interact with administrative staff as well as faculty of the institute on academic or financial aspects. Pre-students look for institute settings that are consistent with their own environment and culture. Most of time, pre-student himself is not capable of taking decision without making a contact with the network of information sources. They make coalition, a temporary alliance to get this information. Coalition is defined as a group of an interacting group of individuals, deliberately constructed, independent of the formal structure, lacking its own internal formal structure, consisting of mutually perceived membership, issue oriented, focused on a goal or goals external to the coalition and requiring concerted member action.

 

Conceptual Model – Segmentation Vs People mix on selection process

 

Fig. 1: Conceptual Model on Segmentation Vs People mix on selection process; adopted and modified from Riley - A buyer’s decision-making process, 2012

 

 

OBJECTIVE AND RESEARCH METHODOLOGY:

The objective of this research was to find out people’s influence, which is a referred group for a student, on the geographic and demographic characteristics in selection of technical educational institute for a student.  A qualitative research through a survey was made. It comprised of a structured questionnaire sent through e-mail to the current-students enrolled and passed-out students (alumni) belonging to the technical institutes affiliated to North Maharashtra University. Sample size (n) was calculated at 95% Confidence Level for which Standard Normal Variate (Z) is 1.96 and at Standard Error (e) of 0.03 by  ; where n = Sample Size to be used for this study, N = unknown population, p = Estimated Portion of Population N. For p = 90%, ‘n’comes out to be 553. However, sample size of 649 was selected by quota sampling from technical institutes offering different programs in engineering, pharmacy and management and different students (Current as well Post-students) based on their location of native place, gender, father’s qualification, occupation and income and technical educational program. The questionnaire comprised of geographic and demographic factors of students with questions measuring influencers impact on the selection of technical institute on a scale ranging from 0 to 5, where value zero, was no influence at all and value five, was most influence. The characteristics of the sample are described as below;

 

By Gender

Male:	443
Female:	206

 

By Father’s Occupation Sector

Education Sector:	111
Non-Educational Sector:	538

 

By Parent’s Income

Below 1 lac	388
1-3 lacs	101
3-6 lacs	125
Above 6 lacs	35

 

By Technical Educational Program

Engineering	480
Pharmacy	112
Management	57

By Native Place

District:	159
Taluka:	277
Village:	213

 

By Institute’s location from Native Place

0 Km:	116
0-50 Kms:	157
50-100 Kms:	193
100-200 Kms:	121
Above 200 Kms:	62

 

Hypothesis:

H1:         Geographic and Demographic factors are associated with the People mix (influencers) for selecting technical educational institutes.

 

 

DATA INTERPRETATION AND FINDINGS:

Effect of gender on the influencers:

Table 1: Chi-square Test for Association performed with Minitab17: Gender Vs Impact of Influencers; Mean of responses received for the influencers gender-wise

Gender	Parents	Sibl-ings	Rela-tives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students them-selves
Chi-Square Test for association	0.023	0.024	0.328	0.402	0.179	0.224	0.681	0.312	0.000	0.499
Male	5.7	4.3	4	4.4	4	3.7	3.5	4.2	6.2	6.9
Female	6.1	5.3	4.2	4.8	4.6	4.2	3.7	4.9	7.2	7.2

Figures in bold are significant at 0.05. (p<0.05; confidence level 95%)

 

Table 1 shows the gender-wise responses of the students on influencers’ impact in the selection of technical educational institute. The calculated chi-square value for contingency table for Male and Female and responses on the influencer ‘Parents’ is p=0.023 which is significant at 0.05 i.e. p is <0.05.Based on this chi–square test we accept H1 and can conclude that there is difference between male and female in accepting ‘Parents’ as an influencer in selecting technical educational institute. Female responses (Mean= 6.1) are higher that the male responses (Mean= 5.7) which suggest that female students have more impact of ‘Parents’ influencers on selecting technical educational institutes than male students. Similarly, we can say that female students have more impact of ‘Management People’ and ‘Siblings’ influencers on selecting technical educational institutes than male students.

 

However, based on chi-square test, there is no difference in gender (male and female) on the impact of ‘Relatives’, ‘Peer/friends’, ‘Current-students’, ‘Alumni’, ‘Previous teachers’, Institute Staff’ and ‘Pre-students themselves’ where p value is >0.05. We reject H1 for this cases.

 

Female students have impact of all influences greater than the male students on their decision of selection for technical educational institute.

 

Effect of Native Place on Influencers –

Table 2: Chi-square Test for Association performed with Minitab17: Native Place Vs Impact of Influencers; Mean of responses received for the influencers based on native place

Native Place	Parents	Sibl-ings	Relatives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students themselves
Chi-Square Test for association	0.318	0.022	0.221	0.007	0.006	0.067	0.019	0.491	0.169	0.039
Belonging to District	3.9	2.7	2.5	2.6	2.3	2.3	1.8	3	4.3	4.5
Belonging to Taluka	4.4	3.4	2.9	3.3	3	2.8	2.7	3.1	4.7	4.9
Belonging to Village	3.9	3.3	2.9	3.4	3.2	2.9	2.6	3	4.5	4.9

Figures in bold are significant at 0.05. (p<0.05; confidence level 95%)

 

Table 2 shows the responses based on students’ native place on influencers’ impact in the selection of technical educational institute. The calculated chi-square value for contingency table for native place -District, Taluka, Village and responses on the ‘Siblings’ influencer is p=0.022 which is significant at 0.05 i.e. p is <0.05.Based on this chi–square test we accept H1 and can conclude that there is difference between students residing inDistrict, Taluka, Village in accepting ‘Siblings’ as an influencer for selection of technical educational institute. Taluka and Village students’ responses (Mean= 3.4 and 3.3) are higher that the District students’ responses (Mean= 2.7) which suggest that Taluka and Village students have more impact of ‘Siblings’ influencers on selecting technical educational institutes than District students. Similarly, we can say that there is difference in District, Taluka and Village students in accepting impact of influencers; ‘Peer/Friends’, ‘Current-students’ ‘Previous teachers’ and ‘Pre-students themselves’ with p=0.007, p=0.006, p=0.019 and p=0.039 respectively, which is significant at 0.05 as p<0.05.

 

However, based on chi-square test, there is no difference in District, Taluka, Village students on the impact of ‘Parents’, ‘Relatives’, ‘Alumni’, Institute Staff’ and ‘Management People’ where p value is >0.05. We reject H1 for this cases.

 

Effect of Parents Occupation Sector on Influencers -

Table 3 shows the responses based on parents’ occupation sector on influencers’ impact in the selection of technical educational institute. The calculated chi-square value for contingency table for parents belonging to education sector and non-educational sector and responses on the all influencers is >0.05. Based on chi–square test we reject H1 and can conclude that there is no difference between students whose parents belonging to education sector and non-educational sector in accepting the impact of all influencers for selection of technical educational institute.

 

Table 3: Chi-square Test for Association performed with Minitab17: Parents Occupation Sector Vs Impact of Influencers; Mean of responses received for the influencers based on students’ parent occupation sector

Parents Occupation Sector	Parents	Siblings	Relatives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students themselves
Chi-Square Test for association	0.168	0.196	0.138	0.723	0.053	0.364	0.709	0.075	0.466	0.719
Parents belonging to education sector	6.4	4.7	4.16	4.8	4.6	4.2	3.6	4.4	6.6	7.1
Parents belongs to non-education sector	5.9	4.7	4.15	4.6	4.2	3.9	3.6	4.5	6.6	7

 

Effect of Parents Income on Influencers –

Table 4: Chi-square Test for Association performed with Minitab17: Parents income Vs Impact of Influencers; Mean of responses received for the influencers based on students’ parents’ income

Parents Income	Parents	Siblings	Relatives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students themselves
Chi-Square Test for association	0.288	0.317	0.169	0.306	0.611	0.750	0.240	0.606	0.177	0.128
<1 lac	3.1	2.5	2.2	2.4	2.3	2.1	1.9	2.4	3.5	3.7
1-3 lacs	2.9	2.2	1.7	2.3	1.8	1.7	1.6	2.1	3.2	3.4
3-6 lacs	3.4	2.6	2.5	2.4	2.3	2.3	1.9	2.4	3.2	3.6
>6 lacs	3.4	1.9	1.8	2.2	2.1	1.9	1.3	2.4	3.3	3.8

 

Table 4 shows the responses based on parents’ incomes on influencers’ impact in the selection of technical educational institute. The calculated chi-square value for contingency table for parents’ income group on the all influencers is >0.05 for all groups of income. Based on chi–square test we reject H1.and can conclude that there is no difference between students whose parents’ income belonging to various income groups in accepting the impact of all influencers for selection of technical educational institute.

 

Effect of Technical Program on Influencers –

Table 5 shows the responses based on technical program in which the students are admitted with the impact of influencers in the selection of technical educational institute. The calculated chi-square value for contingency table for technical program in which the students are admitted and responses on the ‘Siblings’ influencer is p=0.022 which is significant at 0.05 i.e. p is <0.05.Based on this chi–square test we accept H1 and can conclude that there is difference between students admitted in various technical programs; engineering, management and pharmacy in accepting ‘Siblings’ as an influencer for selection of technical educational institute. Responses of students admitted in Management and Pharmacy are (Mean= 3.8 and 3.2) are higher that the responses of students admitted in engineering (Mean= 2.8) which suggest that management and pharmacy students have more impact of ‘Siblings’ influencers on selecting technical educational institutes than engineering students. Similarly, we can say that there is difference in engineering, management and pharmacy students in accepting impact of influencers; ‘Relatives’, ‘Alumni’ ‘Institute Staff’, ‘Management People and ‘Pre-students themselves’ with p=0.024, p=0.006, p=0.005, p=0.002 and p=0.017 respectively, which is significant at 0.05 as p<0.05.

 

Table 5: Chi-square Test for Association performed with Minitab17: Choice of technical Program Vs Impact of Influencers; Mean of responses received for the influencers based on admitted technical program

Technical Program	Parents	Siblings	Relatives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students themselves
Chi-Square Test for association	0.178	0.022	0.024	0.083	0.136	0.006	0.557	0.005	0.002	0.017
Engineering	3.7	2.8	2.5	2.8	2.6	2.4	2.1	2.8	4	4.4
Management	4.3	3.8	2.9	3.6	2.9	2.7	2.4	3.7	5.1	5
Pharmacy	4	3.2	2.9	3	3.1	2.8	2.7	2.7	4.5	4.6

Figures in bold are significant at 0.05. (p<0.05; confidence level 95%)

 

However, based on chi-square test, there is no difference between the students admitted in engineering, management and pharmacy on the impact of ‘Parents’ (p=0.178), ‘Peer/Friends’ (p=0.083), ‘Current-students’ (p=0.136) and ‘Previous teachers’ (p=0.557)where p value is >0.05. We reject H1 for these cases.

 

Effect of distance of institute from native place on Influencers –

Table 6 shows the responses based on distance of institute from students’ native place with the impact of influencers in the selection of technical educational institute. The calculated chi-square value for contingency table for the distance of institute from students’ native place and responses on the ‘Siblings’ influencer is p=0.043 which is significant at 0.05 i.e. p is <0.05.Based on this chi–square test we accept H1 and can conclude that there is difference between students whose differ in distance of the institute from their native place in accepting ‘Siblings’ as an influencer for selection of technical educational institute. Responses of students who study in local institutes, institutes placed in between 0-50 kms with Mean= 2.3 and 2, respectively, are higher than the responses of students admitted in the institutes placed >50 kms away from native place. This reflects that the students studying in the institutes which is within 50 kms from their native place have more impact of ‘Siblings’ influencers on selecting technical educational institutes than engineering students. Similarly, we can say that ‘Previous teachers’, ‘Institute staff’, ‘Management People and ‘Pre-students themselves’ with p=0.017, p=0.012, p=0.014, and p=0.038 respectively, which is significant at 0.05 as p<0.05, have more impact on the students who differs in the distance of their institute from their native place in selecting technical educational institute.

 

Table 6: Chi-square Test for Association performed with Minitab17: distance of institute from native place Vs Impact of Influencers; Mean of responses received for the influencers based on native place 

Distance of Institute from Native Place	Parents	Siblings	Relatives	Peer/ Friends	Current-students	Alumni	Previous Teachers	Institute Staff	Management People	Pre-students themselves
Chi-Square Test for association	0.427	0.043	0.762	0.184	0.673	0.376	0.017	0.012	0.014	0.038
0 Kms	2.8	2.3	1.8	2	2	1.8	1.7	2.1	2.9	3.1
0-50 Kms	2.3	2	1.6	2	1.8	1.7	1.4	2	2.6	2.9
50-100 kms	2.4	1.8	1.6	1.7	1.7	1.5	1.4	1.8	2.5	2.7
100-200 Kms	2.4	1.9	1.7	1.9	1.5	1.4	1.4	1.4	2.8	2.7
> 200 Kms	2.4	1.6	1.6	1.7	1.6	1.5	1.4	1.7	2.6	2.9

Figures in bold are significant at 0.05. (p<0.05; confidence level 95%)

 

However, based on chi-square test, there is no difference between the students who varies in the distance of institute and native place on the impact of ‘Parents’ (p=0.427), ‘Relatives’ (p=0.762), ‘Peer/Friends’ (p=0.184), ‘Current-students’ (p=0.673), and ‘Alumni’ (p=0.376),where p value is >0.05. We reject H1 for this cases.

 

SUMMARY OF FINDINGS AND MARKETING STRATEGIES:

It is important to know institute’s strongest influencers, so that the institute can create a communication strategy that incorporates them into the outreach process. It seems from above survey that ‘Parents’ as an influencer is having an impact on gender. Female students are more likely to consider parents’ decision than male students in selecting their technical educational institute. Siblings of students belonging Village and Taluka place suggest them in selecting technical programs and selecting an institute based on the distance of the institute from their native place. Relatives of students are also helpful in selecting type technical program. Alumni and Friends/Peer of students who belongs to village and taluka also have an influence on selection. Institutes must sure that it has an appropriate communication channels set up with the parents, siblings, relatives and friends through education exhibitions, print publications, social media involvement, digital advertisement, career counselling programs. Alumni and Current-student’s relationship are the assets without cost for the institutes in term of ‘word of mouth’ because their communication is based on true experience of the service. Social media (engagement through Facebook pages, LinkedIn) is an important part of alumni, current-students and pre-students’ engagement. It’s a means to stay connected for long way and forever. Institutes’ staff can share institute’s strategic value messages when they have conversations with prospective students and alumni. Even staff can visit schools and colleges for delivering seminars on career counselling, technical educational awareness. They can further develop relationships with the school teachers. Current-students should be provided with valued based services like supporting, operating and extension activities. Current-students and alumni are the real assets for the institutes without cost. Effective bonding with them will create a free ‘word of mouth’ for the institutes.

 

CONCLUSIONS:

Marketing is most effective when its message is tailored to the audience the institute wants to reach. This method of refining specific groups with a message that is clear and useful to the recipients is called targeted marketing by segmentation.Knowing students based on their geographic and demographic factors can be a powerful strategy for developing technical institutes that can mobilize a management of institute to transform. By determining these targeted audiences, institute can predict the desired behavior. It provides a point of convergence for service providers, service receivers and planners. It is the strategic rearrangement of services, governance and communications which improves staff and management people’s morale and reputation ofthe institutes by increased enrollments.

 

In educational services, ‘People Mix’ plays a vital role as ‘People’ here are the service providers (management people, staff) as well as service receivers (students). In today’s scenario where technical education is gaining it’s important due to its vital contribution towards economic growth of the country, it is important for the technical institutes to whom to serve and when, where and how? At the same time, institutes should know what sources students and the influencers are using to search institutes.Without guidance from a friend, teacher or a family member, many students fear to take decision at their own, even if they decide to take at their own, they end up with the same setting.

 

There should not be just links and clicks, institute must look for relationship with these influencers.  Relationship building though, is a toughest job, as meeting people face to face and having a cup of coffee with them might be tougher, but with today’s technology sources the world might be not enough to build relationship. The institutes must identify the tools to connect and re-connect the influencers. All influencers are needed to work to explore all possible avenues towards the growth and development of technical education by motivating the prospective students towards technical education. However, the institutes those who will act a lubricant for relationships will only survive, after all ‘for the people by the people’ cannot run without bonds and relationships.

 

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