CCC-model-basic
Planning
Organizations increasingly respond to the user in real time. The abandoned shopping cart email is a good example of this. However, there are also companies where little attention is paid to the day, time, A/B testing or the repetition frequency of an action.
Internal coordination is therefore (again) important. Can the newsletter, service email and abandoned cart email be sent on the same day? Or does the content clash with each other? Or is the customer overloaded with information? What gets priority? And why?
Recipient
Segmentations, personas and customer journey
Every organization has a target group. This is divided in a 'classic' way via demographic and socio-economic factors, and made tangible by means of personas . Each person within the target group is also given a place in the customer journey . In itself, this is all fine. But still. According to The Segment of One (pdf) by NGData, such segmentations lead to Prince Charles and Ozzy Ozbourne ending up in the same box. Classic segmentation is therefore too limited.
Historical behavior
But fortunately: there is data! People read, watch, click and buy. Organizations can register this behavior, interpret it and use it for marketing activities. The tools I mentioned in the sender canada telegram data section help with this. Provided they are set up properly of course.
The challenge with data and tools lies in two things. One: in storing and filtering (reliable) data. And two: in selecting and setting up relevant tools for the KPIs defined by your organization.
A personal example of what successful data usage can lead to is an email from Coolblue. One evening I was looking at some Samsung smartphones. Two days later I received an email: “Still happy with your LG Nexus? Check out our new smartphones”. It turned out that Coolblue had linked my purchase from two years ago (!) to my current search behavior. Well done, because indeed: I was not that happy with my LG Nexus 5X anymore…
coolblue mail
Values, goals, dreams, wishes and needs
Through data you can respond smartly to what customers do, but it usually does not answer the question why customers do that. By discovering the deeper customer motivation, you come closer to your customer needs.