Basic user analytics

Who are anonymous customers? Is it time to change the assumptions of data analysis?

Over the years, internet marketing has developed a belief that only the user whose contact details we have is the only valuable contact. This was mainly due to the archaic model of marketing, where the basis for communication was offers sent by e-mail or SMS to contacts stored in the database.

With the rise of modern CDP platforms that allow collecting customer data as the 1st party and give the possibility of executing live scenarios, the definition of anonymity should change significantly. The user ID and cookie have become a pair that allows identification and personalization of communication on the website and, for example, in social networks in a much more effective business way.

Another archaism we have to face is the change of approach from the analysis of user sessions to the analysis of generated events. And in this case, modern tools that collect user behavior and give the opportunity to build action-reaction scenarios cut us off from analytics built on assumptions, not strong data.

This is the end of building foundations. Let's move on to basic analytics. Which are best to start with?

Division of users according to the channels through which we obtain their visits, and we can communicate with them individually: newsletter, web push, mobile push, sms, social media portal, etc.

Conversion from the recommendation is broken down into direct (purchase of the recommended product) and assisted (any purchase). When analyzing this data, it is important to use the possibility of building A/B segments and relate all results to the results of the control group.

Analysis of the abandoned cart broken down into individual stages: the number of visits with the cart to all, the number of converted carts to all carts, the number of abandoned carts to all carts and the number of recovered to abandoned.

Finally, the RFM/RFE analysis described in detail in previous inspirational newsletters. The model was used to create segments classifying users according to their purchasing potential. Although burdened with significant errors, it is still very useful for immediate user classification and execution of marketing scenarios.

Are you interested in this topic; do you want to learn how to use Synerise smarter? Join us at the next Inspiration Session!

(Un)lucky number

is the average conversion rate of a newsletter opt-in (for all types of consents collecting scenarios)

Use (this) Case

An old Chinese adage says...

"Each user leaves data, but not every CDP can use it."

~Yì píng pí jiu

Are you looking for an idea for new scenarios, do you want to improve existing ones, or do you need an impulse to know what and where to look for? The Inspirations newsletter is a supplement to the Synerise Inspirations Sessions prepared exclusively for Clients and Partners. In this open to everyone form, we invite you to the world of digital marketing in which AI plays the leading role.

Business Value Services Director, Dominik Krolikowski