Content recommendations for increased relevance in digital media

Reference number
Coordinator Triggerbee AB
Funding from Vinnova SEK 500 000
Project duration October 2019 - June 2020
Status Ongoing
Venture AI - competence, capacity and capability
Call Start your AI journey!

Purpose and goal

Triggerbee offers a personalization service to e-retailers and media companies. Using behavioral data from the website in combination with customer data, Triggerbee´s customers can create relevance on the website. Through this project, we want to start applying machine learning to automatically identify different personas and categorize content. In this way, no predefined rules are needed for each customer, and we do not have to wait for different predefined conditions to be fulfilled to determine if a visitor belongs to a certain category, and what content to present.

Expected results and effects

The project aims to provide Triggerbee with the conditions to develop the basis for a commercial offering, which after the project has ended can be continuously enhanced together with Triggerbee´s customers and within the framework of Triggerbee´s own R&D budget. Through the project we will collaborate with reference customers where we aim to deliver measurably increased reading and conversion on their websites.

Planned approach and implementation

The project is divided into the following elements: * Evaluate technologies and available frameworks at our cloud provider * Learn to apply these technologies to analyze and detect patterns in large amounts of data * Develop application in the form of software "recommendation engine" that can be used by website owners to recommend content based on data The outcome can be compared with a control group on both participating customers´ websites and non-participating. In this way, we will be able to obtain statistically reliable data on how well the recommendation engine performs.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 23 September 2019

Reference number 2019-03315

Page statistics