## Hypothesis test

As mentioned in the methodology that the author would like to test every each of the factor that was identified in the keyword analysis and combining with the literature review, therefore to make the framework that was constructed in this paper academic sound proof, an statistical data analysis must be examined in order to make sure that this is an acceptable theory of knowledge for the context of sociological science and implementing in the area that where the knowledge is needed in the discipline. The author would be using the one sample t-test that invented by William Sealy Gosset, a chemist in an Irish brewery that published an article on statistics in *Biometrika* back in 1908 (Raju, 2005). Although, the author has acknowledge the statistical limitation in using the parametric test that was mention in the methodology and feels confident that the results in the test would be a statistical proof on which factors are relevant and contributes to the success in enabling customers to advance through the funnel sales process. There will be two test conducted to see whether the factor is statistically irrelevant (Test 1) or statistically higher relevant (Test 2). This was the result from using the Likert scale in the questionnaire (Likert, 1932), each factor was given each one question to ask the respondent on how they rate the situation that is relevant to them by answering on a five point scales, strongly irrelevant is given the value of 0, irrelevant is given the value of 1, moderate is given a value of 2, relevant is given the value of 3, and for strongly relevant is given is the value of 4 (Appendix B). Therefore, making 0 the lower value point and 4 the upper value point in our data samples, with moderate (2) as the deciding point to test for irrelevant. In the two test that will be conduct be determine in the mean population using the covered by the standard error mean of that factor, for Test 1; the factor must have a mean value that is below the upper limit of test value 2 for moderate plus the standard mean error of that factor sample population. And for Test 2; the factor must have the mean value that is above the lower limit of the value 3 for relevant minus the standard mean error of that factor sample population. This done to make that the test with the meet accurate reflection of the population mean and concept that is use here is called the *confidence interval* or the *confidence limit*. In simple terms is it will provide a probability distribution with an associated theoretical mean and standard deviation and providing that our data sample is 147 samples which is above the 30 samples restriction in using the sample mean in utilizing the parametric test.

All tests will be using the 95% confidence level that will determine the significant of the factor that will be tested. If the hypothesis is proven to be true then the decision would be to reject the hypothesis. And if the hypothesis is proven to be false then the decision would be to accept the hypothesis. The consequences are if reject in Test 1 the factor will statistically be classified as irrelevant (not relevant) and if reject in Test 2 the factor will statistically be classified as higher relevant (more than moderate).

*Test 1: testing for statistically irrelevant among factors
*

We will create a hypothesis testing for the factor that would be to prove if whether the factor is statistically classified as irrelevant in contributing to the success of the allowing customers to advance through the funnel sales process at the maximum efficient and companies should give the lowest priority for that factor.

H_{0}: µ ≤ 2, *statistically irrelevant*

H_{1}: µ > 2, *statistically not irrelevant*

Using 5% significant level, if sig (2 tailed) value ≥ 0.05, we **accept H _{0}** and contrary if sig (2 tailed) value < 0.05, we

**reject H**.

_{0}*Test 2: testing for statistically higher relevant among factors
*

The hypothesis test is created to test that factor would proven to be classified as statistically higher relevant in meaning that it would provide a higher contribution to the success of guiding customers through the funnel sales process with the most efficient when comparing with other factors that was introduced into the hypothesis testing and businesses should make that factor among the highest in priority when developing their customer oriented business strategy.

H_{0}: µ ≥ 3, *statistically higher relevant*

H_{1}: µ < 3, *statistically not higher irrelevant*

Again using 5% significant level, if sig (2 tailed) value ≥ 0.05, we **accept H _{0}** and contrary if sig (2 tailed) value < 0.05, we

**reject H**.

_{0}## Test results

In this following section we will explore the result of our hypothesis testing among all of factors that was identified in the keyword analysis approach from the software that was developed for this study and using the program software SPSS in calculating accurate value for us to interpret the statistical meaning of the sample population that was gathered through the online survey. The result in Table 4.7 to Table 4.12 shows the data that was calculated using the statistical software, for a factor to meet the requirement in testing for either Test 1 or Test 2 will be highlighted in red and bold font. Test 1 is the part of the table under “t-value = 2” header and for Test 2 is part of the table under “t-value = 3.0” header. All 33 factors were calculate their statistical values, among them 1 factor that meets the requirement in Test 1 for irrelevant and 11 factors that meets the requirement in Test 2 for higher relevant. Although, there are other factors that does not meet requirements for the one sample t-text hypothesis testing that the conclusion would to be relevant and that they was not subjected the irrelevant hypothesis testing.

**Table 4.7 One sample t-test – campaign management
**

Campaign management process in Table 4.7 has only and lonely factor that meet the requirement for Test 1 hypothesis testing and giving the sig (2-tailed) value of 0.704 which mean that we would be 29.6% confident that the “innovation” is not statistically classified as irrelevant and therefore we would still include innovation as factor that contribute the success in allowing customers to advance through the funnel sales process.

**Table 4.8 One sample t-test – lead management
**

Interestingly for all the factor that was structured into the lead management process evaluated by the developed software keyword analysis which shown the most literature published journal articles when comparing to other process, but in fact have resulted with all moderate ranking from our sample respondents. This maybe that research have made intensive studies in this particular area of the relationship marketing and that practitioner have implemented these factors into their business strategy. Therefore, the general consumer might feel that this is a common business practise among companies and none of them would stand out of the rest. But to be note of the consequences of not taking into consideration of these factors might lead to doom for that company.

**Table 4.9 One sample t-test – offer management
**

The last part of the customer acquisition period is the offer management, value is factor that meet the requirement for Test 2 and that the sig (2-tailed) value equals to 0.002 which is less than 0.05, we reject H_{0}. Therefore, it is statistically confidant to say that “value” is factor has higher relevant when considering with other factors and that has a higher contribute the success of allowing customers to advance through the funnel sales process with great efficient and more customers.

**Table 4.10 One sample t-test – contract management
**

The process where customer retention period begins is contract management and the statistical data could be seen in Table 4.10. The “credibility” and “transparency” where among the factor that meet the requirement of Test 2 for higher relevant, interestingly is see that transparency scored zero count for the keyword analysis but was included by the author subjective testing where the idea was drawn from literature review. The sig (2-tailed) value of the both factor where more than 0.05 and therefore the hypothesis was accepted, which mean that it is statistically safe to say that credibility and transparency does not have higher relevant to the contribution in allowing customers to efficiently move through the funnel sales process.

**Table 4.11 One sample t-test – complaint management
**

Complaint management is a place where “satisfaction” and “knowledgeable” has dominated the research studies among scholars but did not pass the Test 2 hypothesis testing. Three factors was identified to meet the requirement for Test 2 and only one factor had the sig (2-tailed) value less than 0.05 that is responsiveness and therefore we reject the hypothesis testing for this factor. In other words, responsiveness in solving the customer complaint has higher in priority where customers are evaluating the company and that this factor should be taken into higher consideration when comparing with other factors.

**Table 4.12 One sample t-test – service management
**

For the last process in the funnel sales process is the service management and where a factor identified by the developed program to contain the highest in keyword count which the author has mention before that he would like to determine whether scholars are investing their time in the right area of the discipline or not that is the “quality” factor. Hopefully that quality meets the requirement for Test 2 and also another factor which is “ability” has meet the requirement too. Ability did not pass the Test 2 hypothesis testing, but “quality” has pass the testing with confident level of 100% and therefore it is statistically safe to say that “quality” is among the factor that have higher relevant in contributing to the success in allowing customers to be retain and provide future opportunities for the company, this is has be proven that the investment of other scholars meeting the expectation of the general consumer.

Summarising the test results, from all of the 33 factors that we have identified by the computer software keyword analysis, we have statistically found that none of these factors are irrelevant and found that value, responsiveness, and quality is statistically highly relevant to the success that contributes to the efficiency and effective means of allowing customer to follow through the funnel sales process and re-entering again into the sales process for further future purchase. The author would like to say that the elaborateness of the usage of statistically terms in this hypothesis testing is that is term is there to show that the factor are subjected to a common widely acceptable method of analysis to determine whether the findings are to be proven correctly.