Development of a Mobile Personalized Marketing System Essay

Subject: Building a Mobile Personalized Marketing system using multidimensional data 

Date: April 7, 2020

Summary:

Mobile personalized marketing (MPM) can make mobile marketing more personalized. To personalize the content, you need to capture information about the customer in more detail. The proposed work focuses on increasing the number of dimensional combinations per event through user contexts and activities. Personalized marketing refers to positioning customers according to their interest in products or services.

Discussion:

Personalization can achieve in by many specific ways, for example: tracking each geographic location with a GPS. This information will enable advertisers to make accurate decisions about the preferences of individual users, which is essential in our case.

There are two main modules, the first one the user logs in with the login ID, and the AD will push to the application home page. The data that is useful for predicting customer activity is location, time, date, weather, and month, and pushing ads to users based on these dimensions. However, the second one shows that the ads pushed are analyzed based on the user usage of the ads. You can analyze a user's level of interest through a clickstream. Users are only expected to use push ads if they are interested in a particular product. I think these are very interesting and personal.

The components of a mobile personalized marketing system are user location tracking, fuzzy clustering, prediction engine, and data analysis. The primary goal of individual marketing is to push relevant ads in a personalized manner by identifying customer activities from multiple environments.

Conclusion:

In this work, we discuss customer activities that discover important, rules-based sequential patterns from multiple context and action events. These enhances the predictability of a user's preferred product or service. This work opens up some promising developments for future research into mobile personalized marketing. In the future, you can further increase the number of dimensions for sequential pattern mining.

Memo to Professor Nicholas

Page 2

March 29, 2020

J. J. Barathi, G. Kavitha and M. M. Imran, "Building a Mobile Personalized Marketing system using multidimensional data," 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), Chennai, 2015, pp. 133-137.