Over the last decade, more and more companies are beginning to grasp the importance of customer engagement, and therefore have been conducting a lot of research in regard to how they can engage their customer to the most of their abilities. However, according to Emerald Insight, many businesses have been caught off guard by the enormous amount of data they gathered. Data mining, which is a process that can turn raw data into useful information by using software to look for patterns and relationships, can be a great solution for these overwhelmed companies (Investiopia, LLC.).
By using the data mining process, businesses can learn more about their customers, develop more effective marketing strategies as well as increase sales and decrease costs. Data mining is a broad and extensive process that can be used for many different aspects of companies in various sectors. However, for this blog, we will be focusing on three specific aspects for which data mining can be used, which are identifying market segments, database marketing and scoring.
The first thing you have to do in order to be successful is identifying market segments, in order to be able to target customers personally and individually (Bearson, Smith & Thearling, 1999). Data mining can be of great significance in order to successfully carry out this aspect, since it requires substantial data regarding potential customers and their buying behavior. When using data mining – the more data the better, since the process can find the useful information easily and can connect and detect the most important patterns and connections.
After finding the right information, the marketing team can use these results to create a targeted marketing campaign directed at the previously defined market segments. By using data mining in order to create the campaigns, marketers can alter and modify the campaign just right in order to connect it closely with the needs, wants, and behavioral patterns of their potential customers (Bearson, Smith & Thearling, 1999). In this aspect of data mining, it is important to ask yourself specific questions about your potential customers, such as ‘which potential customers are most likely to respond to a particular kind of offer?’.
Finally data mining can be used for scoring. In this aspect, data mining can be used to build models by using customer data to predict future customer behavior. A ‘score’ can indicate the likelihood of a potential customer’s behavior (Bearson, Smith & Thearling, 1999). With regard to a DMO, this information can be very important in terms of who to target with which offer. A DMO can, for example, target specific customers with specific offers for a type of city or attraction a potential customer is eager to see.
Berson, A., Smith, S. & Thearling, K. (1999). Building Data Mining Applications for CRM. McGraw-Hill Companies (December 22).
Peelen, E. & Beltman, R. (2013). Customer Relationship Management. United Kingdom: Pearson Education Limited.