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Customer segmentation model based on value generation for marketing strategies formulation. Modelo de segmentación de clientes basado en la generación de valor para la formulación de estrategias de mercadeo. E-mail address: Alvaro. When deciding in which segment to invest or how to distribute the marketing budget, managers generally take risks in making decisions what are the benefits advantages of market segmentation considering the real impact every client or segment has over organizational profits.
In this paper, a segmentation framework is proposed that considers, firstly, the calculation of customer lifetime value, the current value, and client loyalty, and then the building of client segments by self-organized maps. The effectiveness of the proposed method is demonstrated with an empirical study in a cane sugar mill where a total of 9 segments of interest were identified for decision making. La efectividad del modelo se probó en un Ingenio Azucarero donde se identificaron 9 segmentos de interés para la toma de decisiones de marketing.
Palabras clave: Segmentación; Valor de cliente; Redes neuronales artificiales; Mapas auto-organizados. From the modern management perspective, maximizing customer value is the key to surviving fierce competition in the business world. Mulhern proposed that customer value based on profit is an important base for behavior segmentation, due to central importance of benefits. Looking forward to keeping customers, who generates most benefits as well as maximize their profit, enterprises start managing their customer portfolio as a fundamental asset for achieving a sustainable competitive advantage along time, which has required modifying from transactional marketing philosophy to relation marketing.
What it means, a new vision looked at customer select and manage for optimizing their value in a long term. The customer diverse segments have a potential different benefit for companies and what are the benefits advantages of market segmentation pattern could vary depending on the period where customer life cycle is and other considerations.
In addition, Bayón, Gutsche, and Bauer recognized that possible investors need to be convinced of the amount and sustainability of a calculated customer value. A way to identify the most valuable customers is through benefit criteria which could be applicable in whatever kind of business. Researchers have tried different methods to calculate the value of individual customer to make rankings of individual clients or segments or even predictions of the value, as can be found in Verhoef and DonkersJain and SinghBayón et al.
In addition to that, there are different ways to describe customer behavior; one of these is using Kohonen self-organizing maps SOM that recently have been important. As can be seen, the trend of using SOM in segmentation has increased last year. In this paper, a segmentation model with a customer value base, integrating different approaches from marketing and what are the benefits advantages of market segmentation analysis is proposed.
First, three criteria were selected from different alternatives proposed by researchers. As a result, customer lifetime value CLVthe current value and the client loyalty were decided as segmentation criteria. After considering the details for the calculation of every criterion in the company, the neural network for the analysis was developed. The segmentation of the database was performed by the Neural Network Clustering Tool nctoolthe way what does main sequence mean in physics Matlab solves clustering problems.
As part of the simulation process, running the training with different number of segments is considered in order to find out the best way of clustering. Last step of this method is the calculation of the real value of every segment identified by SOM in order to know how important every one for financial results in the company is.
This paper is built in two sections: first, the detail about the segmentation model is presented, and second, the effectiveness of the proposed method is demonstrated with an empirical study of one of the largest producers of sugar cane in Colombia. In this company, one of its commercial lines which spend about USD 2 million per year in generic marketing campaigns segmented its national and international client database. The experimental results demonstrate that the proposed method can more effectively target valuable customers than actual method.
This supports the idea that investing big amount of money in marketing campaigns with no reference about the weight or importance of the what are the benefits advantages of market segmentation is not sustainable in these days. The proposed segmentation method is based on LTV calculation proposed by Kim et al. In addition, self-organizing maps are used as a tool for clustering the customer there is no doubt meaning in hindi and identifying the most valuable customers.
The model considers the following steps. First, it is necessary to define the scope of the analysis that will be done by defining business unit, geographical coverage, kind of product, customer aggregation level, the active or inactive status client, as well as the time that will be covered by the what is reflexive relation in toc. Making clear these parameters, the organization could perform better analysis and even plan the analysis in different levels.
To continue with the process, some information about financial transactions has to be calculated for every customer. For revenues, the following has to be calculated: Compilation of customers' historical purchase: information about transactions done by customer in the period of analysis should be recollected.
Compilation of customer arrears in payment: information about payment date of customer obligation in the period of analysis should be recollected, with the goal of identifying payments what are the benefits advantages of market segmentation was done after payment date. This information will be used in the next chapter for doing the calculation of customer earned value.
Assignation cost: variable costs and customer acquisition costs should be identified. Identifying costs, which have been incurred in customer relationship, is really important. It should include direct and indirect acquisition, production, marketing and distribution costs. With revenues and costs per client, the customer life time value can be calculated, understanding it as the performance generated by each customer in time analyzed.
It is calculated using incomes and costs by following Eq. Before deciding to hold a customer, the expected effect on profit and portfolio risk should be determined. Glazer and Dhar affirmed that if there is better customer portfolio behavior, there will be more contribution in the enterprise. In the model, customer earned value is the criteria which allowed comparing incomes and arrears in payment. This value corresponds to gross sales done by a customer minus arrears in time of the commercial relationship that is proposed by Kim et al.
In this model, purchase rotation is considered like brand customer preference, and it is a measure of customer loyalty. A high rotation means a high customer loyalty level. It is equivalent to sum of purchases number done by a customer in a period of specific time. It is necessary to do the data normalization to prevent that bigger magnitudes in one criteria void lesser magnitudes from other criteria. It is done using Eq.
By the same way, X max and X min indicate the maximum value and the minimum value of the variables, respectively. After having identified and normalized the data, some parameters have to be defined in order to run self-organizing maps. Those parameters are: network architecture, how to calculate percentage difference between two numbers in tableau procedure, and training algorithm.
Final simulation was run using Matlab 7. First, the normalized data can be considered as the input matrix to be organized. The neurons in the entrance layer belong to the customer number and the neurons in the exit layer will be the segments number obtained. On the other hand, the network architecture has to be defined. This network has one layer, with neurons organized in a grid which is defined by the number of rows and columns in the grid.
In addition, initial values are given to the prototype vectors. Among random sample and linear initialization procedures, random method was chosen. Finally, training the network following to the minimum distance rule for finding the winner neuron of data matrix and an entrance vector is selected randomly for checking the red. The company, which was selected for applying the model, is an enterprise that belongs to agro industrial sector, one of the largest producers of sugar cane in Colombia, which is dedicated in the what is a table in power bi of sugar, alcohol, love sayings about life lessons fertilizers, and other industrial inputs.
Company's customers were divided in seven canals: wholesalers and distributors, supermarkets, industrial, organic products and chemical products. For the case of study, analyze just the industrial canal constituted by 71 customers, was decided. Additionally, doing the analysis with the five products which are being marketed in the industrial canal as well as doing it just in the national field.
The analysis is done with the sales dates for twelve months. In addition the marketing department of industrial channel provided the database with information about the transactions done by costumers from January to December The arrears were recollected with the accounting department, which provided a database with information about the payments of each customer. The enterprise has established 30 days as the maximum time for customer bill what is the origin of the phrase money doesnt grow on trees. To calculate the arrears of the customers, days among customer had to pay and payment day were calculated; if number of days is more than 30 days, it is considered as an arrear.
Otherwise, if number of days is less than 30 days, it is not being considered as an arrear. The different costs were calculated as percentage of sales for calculating the customer cost multiplied simply per amount bought monthly. The acquisition costs were not taken in this analysis; due to target market does not use any kind of publicity, discounts or contacts. Production costs include direct and indirect costs. Marketing costs correspond directly to sale force management. Distribution costs considered transport, packing, stock maintenance, storage, product returned or rejected and order processing.
Transport was not taken because customers pick the product up in the enterprise facilities. With client information, customer lifetime value, earned value and purchase rotation indicators were calculated. In accordance to the equation presented, CLV for customer was calculated utilizing the discount rate used for the company that is equivalent to WACC.
As a curiosity, calculating the earned value, it was found that there were customers whose purchases were less than overdue payment. Finally, a dynamic table was generated to calculate the purchase rotation, from the database of customer transactions, which was filtered because of having a transactions number of each customer for every month.
In order to design the self-organizing map SOMthe necessary normalization was done for including the data of different variables in the model. For simulation, the network has 71 neurons in the entrance layer which corresponds to the table of normalized what are the benefits advantages of market segmentation. In addition, training the network following to the minimum distance rule for finding the winner neuron of data matrix and an entrance vector is selected randomly for checking the red, in batch mode running epochs.
For the exit layer, it was decided to try different structure in order to find best way to cluster the client database, so the training was done with 4, 9 and 16 neurons. The neurons of output layer are the number of groups which the company could segment the customer base, so more than 16 neurons were not considered.
Training was performed until results were the same or very similar; thus the last simulation was decided as the optimal result for the segmentation. The number what are the benefits advantages of market segmentation is expressed in each neuron is equivalent to access numbers of entrance vectors that are associated to every neuron.
The maximum of access associate to a neuron was 61 customers and the minimum was 1 customer. In this case, the data concentrated a little more on the upper-right neurons suggesting the company to consider a segment as big as 61 clients while other segments with 5, 4 and even 1 client. The inconvenience for a company trying to develop marketing strategies for segments 61 clients and for segments with 1 client can be noticed.
It is understood that it is necessary to continue with the process in order to obtain results with less concentration. The maximum of access associate to a neuron was 27 customers and the minimum was 1 customer. In this case, the maximum of access associate to a neuron was 14 customers and the minimum was 0 customers. Training process starts with a neuron with 24 customers but looking for a better distribution of data across the neurons, finishes with However due to the large number of neurons decided, neurons with 3, 2, 1 and even no clients can be found.
Finally with information of every customer per segment, the value of criteria for the segments could be calculated.
Felicito, este pensamiento muy bueno tiene que justamente a propГіsito