Multi-Channel Marketing Attribution with Markov

Multi-Channel Marketing Attribution with Markov

How Cloudera uses Markov models to solve the multi-channel attribution problem. Marketer’s guide to data-driven marketing attribution.

An edited version of this article was first published on ClickZ: Marketer’s guide to data-driven marketing attribution.

Marketing attribution is a way of measuring the value of the campaigns and channels that are reaching your potential customers. The point in time when a potential customer interacts with a campaign is called a touchpoint, and a collection of touchpoints forms a buyer journey. Marketers use the results of an attribution model to understand what touchpoints have the most influence on successful buyer journeys, so that they can make more informed decisions on how to optimise investment in future marketing resources.

Buyer journeys are rarely straightforward and the paths to success can be long and winding. With so many touchpoints to consider it is difficult to distinguish between the true high and low impact interactions, which can result in an inaccurate division of credit and a false representation of marketing performance. This is why choosing the best attribution model for your business is so important.

In this post, I provide some insight into how Cloudera has used Cloudera products to build a custom, data-driven attribution model to measure the performance of our global campaigns.

data-driven cloudera attribution-modeling marketing-technology markov-chains data analysis

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Analysis, Price Modeling and Prediction: AirBnB Data for Seattle.

Analysis, Price Modeling and Prediction: AirBnB Data for Seattle. A detailed overview of AirBnB’s Seattle data analysis using Data Engineering & Machine Learning techniques.

Data-Driven Marketing: an important aspect of Mobile Apps ROI

Data driven marketing if implemented correctly can boost the ROI of mobile apps making it profitable by enabling improved connectivity with customers.

Introduction to the Markov Chain, Process, and Hidden Markov Model

Introduction to the Markov Chain, Process, and Hidden Markov Model. The concept and application of Markov chain and Hidden Markov Model in Quantitative Finance.

Exploratory Data Analysis is a significant part of Data Science

Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.

Tableau Data Analysis Tips and Tricks

Tableau Data Analysis Tips and Tricks. Master the one of the most powerful data analytics tool with some handy shortcut and tricks.