Marketing Analytics Learning Center

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Below is a collection of our favorite podcasts, communities, articles and videos that provide guidance on how to use analytics to empower marketing decisions.



Episode 74: “Predictive Analytics” by Eric Siegel

(40 minutes) Dr. Eric Siegel discusses how predictive analytics helps predict human behavior and thus helps reduce risk, boost sales, cut costs, improve healthcare, streamline manufacturing, toughen crime-fighting, and win elections.

Episode 30: Using Predictive Analytics to Segment Your Top Prospects for Major Giving with Target Analytics

(12 minutes) If you are looking for something short and sweet and interested in how non profits are using predictive analytics listen in on Blackbaud’s Mark Christensen and Melissa Bank Stepno, a Practice Manager with Blackbaud’s Target Analytics team. With a history as a nonprofit consultant in predictive modeling and wealth segmentation programs, Melissa shares learnings from the industry and discusses how to use predictive analytics to identify the best prospects for major gift donations.

Understanding predictive analytics

(31 minutes) O’Reilly’s online managing editor Jenn Webb speaks with Natalino Busa on the topic of predictive analytics, the challenges of feature engineering, and a new class of techniques that is enabling features to emerge from patterns within the data. They also discuss the relationship between predictive techniques and high-quality microservices, and how machine learning is being used to improve financial services.

Predictive modeling techniques

(7 minutes) Predictive modeling is more than a math problem. This Talking Data podcast looks at it from the business and technology perspectives.

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Slack Channels

A mix of news, networking and information. They have channels dedicated to machine learning, Python and R.

Experfy’s community of Data Science, IoT, and Big Data experts. Experfy based in the Harvard Innovation Launch Lab, is a data science, analytics and engineering talent marketplace.

Online Geniuses is an internet marketing community based off Slack with events across the globe comprised of over 15,000+ members which focus on SEO, PPC, Social Media Marketing and everything in between.



(5 minutes) Leo Vasiliou walks through the evolution of analytics and how analytics relates to a larger monitoring strategy.


(16 minutes) What’s the future of big data-driven technology and design? In a thrilling science talk, Kenneth Cukier looks at what’s next for machine learning — and human knowledge.

Lityx Concord Direct webinar


(43 minutes) Presenter Gary Robinson (COO of Lityx) and Steve Rudman (General Manager of Concord Direct) present an interactive webinar, using real data to demonstrate how predictive analytics can dramatically impact fundraising campaign ROI for nonprofits.

Nonprofit Advanced Analytics webinar


(31 minutes) Presenter Gary Robinson (COO of Lityx) presents a hands-on training that covers the basics of using predictive analytics combined with RFM data to improve marketing results and reduce costs for nonprofits.


(46 minutes) Presenter Paul Maiste (CEO of Lityx) will explain what Marketing Optimization is and how it is performed using simple, easy to understand terms and examples. Go beyond the use of BI tools and modeling and learn how to get even higher performance out of your marketing programs.

LinkedIn Groups

A network for individuals interested in Big Data with collated industry news and exclusive opinions, features & events.

This group is one of the most dynamic groups on LinkedIn for Predictive Analytics Professionals. The aim of this group is to bring together professionals who are passionate about the growing role of predictive analytics in business

Co-founded by Vincent Granville and part of the community, our focus is on data science, machine learning, AI, deep learning, dataviz, business analytics, predictive modeling, big data, Hadoop, IoT, decision science, and BI.


The article focuses on the four types of data analytics we encounter in data science: Descriptive, Diagnostic, Predictive and Prescriptive.

Simply put, non-subscription churn happens when users or customers, who can end their relationship with your business at any time, leave your website or sales funnel. These types of customers may gradually reduce their purchase frequency over time, or they may all of a sudden never buy again.

With all of the advances in data and technology in recent years—petabytes of data being analyzed by companies like Facebook and Twitter—and with predictive modeling being as hot as it is, one must figure that easier-to-use modeling tools must be ubiquitous. Surprisingly, this is a new frontier.

Other Resources

This handbook digs deeply into managing data mining tasks and data science applications to help ensure that your big data analytics program is in the corporate spotlight for all the right reasons.

The move to predictive analytics is changing and improving how marketing groups are approaching their programs and spend. Download this e-book to see predictive analytics in action, understand the challenges you should consider when using predictive and how you should expect to improve ROI.

Join the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster.

Lityx is an analytics software company focused on empowering companies to improve their ROI through accessible advanced analytics software and services.

We provide advanced analytics software, consulting services and third-party data to our customers. Our team serves a diverse set of clients across many industries, providing cloud-based hosted analytics solutions that help both business and technical users easily leverage the power of data management, insights, predictive analytics and optimization. Our solutions offer access to sophisticated analytics approaches at a reasonable price. Start making better business decisions by predicting customer behavior such as spend and churn, or optimizing your channels and campaigns. Learn more about Lityx and our customers, here.

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