Table 4 1: Customers’ Churn alternatives and total weight
Related Figures (7)
Table 2.1: List of related literature about customer churn From the foregoing reviews, empirical and theoretical framework, it has been revealed that, attributes as well as predict the customers churn and retention in the Nigeria telecommunication industry. The drivers of customer churn and retention were taken from both literature and preliminary interviews granted by the users/subscribers of mobile networks in Nigeria. These were presented for the respondents to make a pairwise comparison regarding the extent to which each of the driver in comparison to its pairs could motivate subscribers on churning or retention decisions. The evaluation process was able to assess if the actual service of the particular driver or attribute meets the expectation of the customer, which was used to determine customer satisfaction or dissatisfaction as the case may be. The implication of the decision taken by majority of the subscribers subsequently determines what happens to service provider/ network operators. Churn decisions will bring about less revenue, less profit and referral or bad mouth, which is the cheapest advertisement for the company with negative implication. It is the cheapest, because the companies do not pay for it, yet it affects their image and reputation and ultimately reduces its market share in the long run. On the other hand, if majority of the subscribers retain the network, it will increase revenue, and profit, reduce cost of undirected market activities, increase the market share and leads to greater referral with positive implication on the firm. A consequence of this is that subscribers who retain a network will encourage others to be on the same platform without been paid directly by the telecommunication operator to do so. From the above illustration, all the complex interaction that exists in the decision of subscribers whether to switch from their current service provider by comparing the expected future benefit against the other factors or drivers ultimately determines the industry’s performance. Thus, figure 2.1 shows the pictorial representation of the conceptual framework. The AHP procedure involves pairwise comparisons among n elements in each level lead to an approximation of each a; = w/w, which is the ratio of the weight of element i to element 7. The estimated weight vector w is found by solving the following eigenvector problem: Aw = Amaxw, where the matrix A consists of aj *s, and Amax is the principal eigenvalue of A. If there is no inconsistency between a pair of elements, then a, is equal to 1/ aj for any i and j. The result is that Ama = mand we have, Aw = nw, where n is the number of elements in each row. Written out more completely, this matrix equation takes the form: To calculate the w vector (also called the eigenvector), each column of A is first normalized and then averaged over its rows. This vector is used to find the relative importance of each element. Observe that since small changes in a; imply a small change in max, the deviation of the latter from n (the number of elements in a row) is a measure of consistency. The consistency ratio (CR) is given by (Amax-1)/(n-1), which is the variance of the error incurred in estimating the matrix A. If the inconsistency becomes more than 10%, the problems and judgments must be reinvestigated and revised (Saaty, 1980). Table 4. 2: Customer retention alternatives and total weight Where, decision criteria and decision alternatives are independent events to one another. Owing to independent relationship that exists between criteria and alternatives in AHP, the above formula holds and total weight for retention alternative is computed and presented in table 4.2. The bar chart in figure 4.1 shows the total weight of customer churn. What motivates a customer to churn most is a network provider with high cost of data/internet plan. Even when such plan has sufficient data for the use of customer per period, with priority value (pr = 0.1376), high cost data plan allows customers to turn to competitors. For service provider to minimize churn rate, especially for people in academic environment, there must be a sufficient data at reasonable competitive cost. Another factor that customer considered to churn from a network is difficulties in making calls or sending messages to same network. It can frustrate customers who have sufficient telecom credit and send a message either by voice or text and they are told by the network provider that their message is unable to deliver due to insufficient telecom credit. Next on the alternatives that customer considered in their churn decision is frequently receiving unsolicited irrelevant text messages from service providers. Sometimes, this may even be unbearable if customer does not have any benefit from them. In the same vein, service providers can notify customers of new service attributes which may be irrelevant to the immediate telecommunication needs of subscribers. As such, service provider should identify the communication need o different groups of subscribers in order to meet them. Other alternatives that equally drives customer churn are short-change on service charge with priority 0.0851 and this is followed by charging customer for service not used. Network operator should realize that, customers are rational human beings who consider value for money and are transitive in their comparison of what they get and what they give. Therefore, service providers should ensure fair and just billing system in order to minimize customer churn. Other factors which influence churn Figure 4.2. Horizontal bar chart for total weight of customers retention alternatives
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