Optimizing Pipelines, AI & Predictive Analytics in Marketing, a Data Science Challenge, and More

Andrea Steffes-Tuttle Weekly Roundup

This week, we learn how to optimize your nonprofit’s prospect pipeline in four steps. We find out how artificial intelligence and machine learning are effectively used in marketing and examine the immense opportunity of predictive analytics for marketers. Taking this a step further, we feature a case study that illustrates how one higher education organization used predictive analytics to increase graduation rates and close achievement/opportunity gaps for low-income/underrepresented student groups. And finally, we share a seven-day data science challenge to help you get started in the world of data science.  

How to Optimize Your Nonprofit’s Prospect Pipeline

by Kayla Matthews, contributing writer for NonProfitPro.com

Since donations often become the lifeblood of nonprofits, it’s crucial to ensure your prospect pipeline functions well. It is the framework and process that fundraisers go through when they work to find and nurture the people who ultimately become first-time or repeat donors. This article covers four items you can do in order to optimize your prospect pipeline and ensure you’re targeting the potential donors in your database most likely to give.

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What Is Artificial Intelligence & Machine Learning in Marketing?

by Indrajeet Deshpande, contributing writer for MarTechAdvisor.com

This article brings us back to the basics. It breaks down the use of artificial intelligence (AI) in marketing, which includes using online and offline customer data along with concepts such as machine learning (ML), natural language processing, social intelligence, etc. to gauge your audiences’ future actions, target them effectively, and deliver highly relevant messages to them. Let’s take a look at how organizations can use artificial intelligence and machine learning to their full potential with an understanding of the fundamental concepts.

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Reading Customers’ Minds: Immense Opportunity in Predictive Analytics for Marketers

by Anand Jain, contributing writer for FinancialExpress.com 

Today’s shoppers are dynamic and have more access to information than ever before. They’re also mobile, with $200 billion in revenue expected to be spent from smartphones this year. Companies that tap into this customer data and use predictive analytics to predict what the customer will do and serve the right message/offer at the right time, will have an advantage. This article features a few examples of companies using predictive analytics well. 

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Transforming Programs Through Predictive Analytics

Parag Gupta & Jeff Gold, featured on SSIR.org

In this recording from the 2019 Data on Purpose conference, Parag Gupta, vice president of the Stupski Foundation, and Jeff Gold, assistant vice chancellor at California State University share a case study that illustrates how public higher education institutions are successfully using predictive tools to increase graduation rates and close the achievement and opportunity gaps between low-income and underrepresented minority students and their peers. 

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7-Day Challenge Apra

by Ashutosh Nandeshwar, on LinkedIn.com

Data science can be overwhelming to get into, but sometimes the only way of breaking through is to roll up your sleeves and just do it. This simple and straightforward seven-day challenge helps you do just that. With clear tasks and outcomes defined for each day, you’ll find yourself getting started with data science in no time!

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Did you see an interesting article in the last week? Share it with us! Send it to astuttle [at] lityx.com.


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