Tuesday, April 14, 2015

MicroTargeting and Campaign Management part I.

Every day I try to focus on different topics while surfing on the Internet. The topics I choose are depending on various aspects but one of them is fitness for a particular work I am currently involved in. Today's selection process was very quick, I got an invitation for workshop about MicroTargeting and Campaign Management in companies, so we can compare today's post to Twitter's (yes, again) follower hunting.

This article has continuation, click on Read more button below ;)

There are three basic steps in Campaign management. First of all, what is Campaing Management?
Is is solution that uses customers' data, filter them and for (mostly) sale purposes ensures delivery of customized message in various forms.

Let's say you provide your personal data to your bank, telecommunication operator, or similar huge company with many customers. In more decent cases you sign an agreement with them by which you agree they can process our data for own purposes. That means inserting your data to a database and also using them for analysis and consequential prediction of your behavior and offering you customized list of products you may like.

The three steps of microtargeting are
  • Collect data about customers or any parties (Well, this was step zero)
  • Collect them more and more, to get so much data that you can analyse it and predict their future behavior
  • Group your cusomers into several groups and choose which products fits the best to every group
  • Customize messages and offers using age, sex, country etc
There are multiple ways of targeting people, using SMS, calls, e-mails, mails. However, I am curious how can be campaign management used in some companies that offer only one product (therefore they can not customize their offer in regard to specific customer)...

In the next part of MicroTargeting and Campaign Management story I will introduce you a tool for CM, how are these campaigns created and how do analyzed data about customer look like.