論文代寫價格-數據庫營銷技術的應用。根據福布斯等人(2016)的研究，有幾種應用與直接營銷和數據庫營銷相關。現代顧客期望溝通在本質上是高度重要和個性化的。任何看起來具有一般性展望的信息都將被客戶跳過(Forbes et al.， 2016)。數據庫營銷技術可以為公司提供關於客戶需求的信息。這可以稱為建立成功的營銷活動的基礎。數據庫營銷的幾種應用在當今世界是顯而易見的。組織也有不同的方法來使用這種技術。
The first application can be seen when organizations want to listen to the customer. Through leveraging various sources of external data such as social media, alerts from company news, employee changes, marketers become capable of pinpointing the most suitable organizations that can be targeted for their next campaign of marketing (DeSoto et al., 2016). Other points of data are inclusive of information on socio-demographic characteristics, preferences of product and digitalized behaviour. These can be collected for creating a complete picture of the customer.
Other application which can be evident is to communicate in the relevant manner. This application is crucial as communication of the most relevant requirements and information enables sustaining the customers on the whole. Through a complete customer profile development, this form of marketing allows organizations to develop capabilities of delivering the correct information at the correct time to the correct individual (Reis et al., 2015). Real time sources of data can be analysed from different platforms such as the social media. The marketers of this marketing form can lock over opportunities once they come up. Then it would become possible to deliver most intelligent communication of marketing which is also well targeted.
Another application becomes possible when organizations want to ensure that their customers are retained, for which the customer retention offers are utilized in order to achieve the objectives. This form of marketing helps organizations enhance their rates of retention as well as loyalty through most personal offers of retention being offered (De Bock, 2016). This also takes into consideration the factors of an individual customers account such as their behaviour digitally and web based transactions along with data location and socio-demographics.
The above mentioned are broad applications of database marketing. In order to provide specific applications, the following is provided:
To calculate the lifetime value of a customer (CLTV): this is a model of prediction which is utilized under marketing (Wedel and Kannan, 2016). It can be used for estimating individual customer’s lifetime relationship worth to the organization. The model accuracy as well as the involved calculations with time has gained accuracy as the database marketing methods themselves have enhanced.
Analysis of recency, frequency and monetary: this is a database marketing method which is utilized for calculating the most essential customers for a business depending upon several factors (Chang and Zhang, 2016). For example, the recent customer purchases, frequency of purchase and the money spend can be taken into consideration. The theory responsible for driving this marketing paradigms utilization is that most of the business comes from only 20 percent customers for an organization (De Bock, 2016). This further allows the direct marketer efforts to be targeted specifically to those customers who are the best and most profitable to the company (Lewis et al., 2015). In turn, this provides direct marketers efforts to be targeted specifically to the best customers. Like CLTV, again, this technique’s accuracy has improvised in the same way as database marketing.
Another application is the customer communication model: this is an example of the way in which the use of database marketing helps in improving communication to the customer inclusive of making use of data for personalizing the correspondence. This not only makes it easy for building up a rapport and henceforth enhance increasing customer retention but also sales and loyalty as well (Reis et al., 2015). Despite the spam perceptions, email has been an important weapon of ancillary nature within the database marketer’s toolkit. It allows providing the medium by which instant communication is possible with consumers.
Use of analytical software: in an increasing manner, businesses require monitoring the behaviour of their customers across several channels of retail including web interfaces, mobile based applications and social media (Risselada et al., 2014). The use of analytical software in combination with databases of companies can be utilized for synthesising such data in an easy manner and result in producing instant reports which can help in defining marketing strategies of company.
Loyalty programs: it becomes possible through database marketing for organizations to consider launching their programmes for loyalty as they are able to store information over their history of sales (Tiago and Verissimo, 2014). This permits the companies to demonstrate engagement as well as reward customer loyalty in turn, which can motivate the consumers to choose a business over another one.
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