Category: annual giving

Data Science Giveaway Ends Tomorrow, Feb 7th!

Join our data science giveaway, which ends tomorrow Feb 7th! No purchase required.

http://nandeshwar.info/ds4fundraising/

Just share your referral link with friends.

The more friends you get to sign-up, the better rewards you can win.

Enter To Win:

  • DataCamp’s 100+ Video Courses (one year subscription)
  • Top Five Data Science books, including R for Data Science and Machine Learning with R
  • NYT’s Digital Subscription (26 Weeks)
  • Machine Learning Flashcards
  • R Stickers

Data Science for Fundraising: Build Data-Driven Solutions Using R

I’m pleased to share that Ashutosh Nandeshwar and I have co-authored a book Data Science for Fundraising: Build Data-Driven Solutions Using R, which is expected to release Feb 2018.

Please share with anyone interested in learning about data science and how to build machine learning solutions with step-by-step recipes.

Check out the attached link for more details about our data science giveaway!

Predictive Modeling for Acquisition

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OVERVIEW

Acquiring new donors can be difficult and expensive for any annual giving program. Fortunately, predictive modeling can make the challenge of converting non-donors into donors easier and more efficient. Creating and applying a simple scoring system can help you to determine which non-donors are most likely to respond to direct appeals and which marketing channels will yield the highest return for various segments.

WHAT YOU’LL DISCOVER

  • Methods for building low cost donor acquisition models in-house using Excel
  • Guidelines for applying model scores to prioritize prospects and non-donor segments
  • Advice for allocating your resources to each of your marketing channels based on model outcomes
  • Tips for assessing the strength and effectiveness of your models and your acquisition efforts
  • Examples from other institutions, and more!

Thanks to the Annual Giving Network (AGN) team for inviting me to present on predictive modeling for donor acquisition.