Deep.BI

11/08/2023

We are big supporters of open-source Druid at Deep.BI, and actively contributing to the project by creating game-changing extensions like the Spark Druid Segment Reader.

This tool provides your data science team with easy access to all historical data on demand.

Want to learn more? Check out our latest blog post to dive deeper into this innovative solution:
https://www.deep.bi/blog/expanding-druid-to-data-science-introducing-the-open-source-spark-druid-connector

Let's keep innovating and collaborating together!

Explore the synergy between Apache Druid and data science with our Spark Druid Segment Reader. Learn how to effortlessly extract and analyze Druid data for AI and machine learning, paving the way for better-informed decisions in the world of big data. Discover the open-source solution to bridge the....

04/09/2021

MediaTech companies that help publishers optimize engagement, visualize data, monetize articles, cut down on research time and more

04/01/2020

The has sent content consumption levels through the roof, and it's not over yet.

Has your organization started strategizing about how to retain these users when the surge passes?

Our new report, as seen in the International News Media Association - INMA Initiative, offers actionable items to target these readers and build revenue over the long term.

Download it here today!

The key objective of this report is to study user behavior, content consumption patterns and the effect this has on user engagement, readership habits, loyalty and, ultimately, revenue generation through subscription sales in the context of the current COVID-19 pandemic in both the short term and lo...

03/17/2020

Diarios Associados and their publication S.A. Estado de Minas are working with Deep.BI to build Propensity to Subscribe/Churn algorithms to capitalize on user engagement and grow subscription revenue.

Read more about the project and S.A. Estado de Minas' vision of how new engagement strategies and can help the 92-year old publication thrive.

Specifically, Deep.BI will provide intelligence to the publication’s in-house paywall via real-time Recency Frequency and Volume (RFV) scoring, and later build Propensity to Subscribe/Churn algorithms - to capitalize on user engagement and grow revenue.

02/27/2020

Deep.BI had a chance to sit down with Marcela Kunova from Journalism.co.uk to chat about how we help publishers fight churn by generating actionable insights into user behavior.

When readers hit a paywall at the right moment they are also more likely to subscribe. Clever algorithms now make this part of reader behaviour easier to understand

02/07/2020

📣📣JUST RELEASED: Spain's leading digital newspaper, El Confidencial to build a new and improved subscription strategy with Deep.BI's Propensity to Subscribe algorithms. Read the press release here: https://bit.ly/37d99fq

FREMONT, CALIFORNIA, Feb 7th, 2020, Deep.BI , an AI-powered data solutions company focused on real-time scoring and intelligent data augmentation for user-centered engagement, has announced that El Confidencial , Spain’s leading digital newspaper, has signed an agreement to begin implementing De

01/16/2020

Can you predict and prevent before it ever happens? Yes, when you use data to identify inefficiencies, you can fight them by building loyal habits for your audience members.

When readers unsubscribe, seek to understand how engaged they were prior to unsubscribing and send personalised offers to encourage re-subscribing to boost future retention rates.

12/31/2019

Happy New Year! 🎆🥂🥳🎉
Digital media saw some big changes over 2019 and it looks like 2020 is going to be just as exciting!

3 digital media trends that look set to become habits in 2020 #1 Registration requirements and hard paywalls will continue to grow in popularity. In early 2019, when The New York Times managed to shut down the swarm of users who had been skirting the site’s paywall via incognito mode , digital

12/19/2019

Dynamic paywalls turn engaged users into subscribers. Find out how in our newest blog post.

Take this scenario for example: a user comes to the site with an increasing frequency and consumes more content per session. One day, the user gets really interested in a story and they wants to read it now. This user’s emotions are heightened at that moment. If we are not able to detect this flar...