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!
Data analytics is a topic of increasing relevance and priority for organizations of any size or sector.
As you explore different analytics pathways, options and solutions, there are common themes around design, workflow and business requirements, as well as important technical, social and cultural considerations, that must be aligned with organizational goals, priorities and expectations.
Ultimately, the value proposition of data analytics is to help 1) improve results and 2) gain operational efficiencies. Despite the simplicity of these goals, data analytics can be challenging to implement and realize at scale for many organizations.
In the following article, we will explore some ways to effectively organize, contextualize and drive analytics adoption efforts within your team, department or organization.
Thanks to APRA for inviting me to present on relationship management for the 30th annual conference on 7/28/17 in Anaheim, CA.
The topic of my session is Relationship Management and Metrics: Key Fundraising Tools to Drive Acceptance of Analytics, Models and Services.
Here’s a brief description of my presentation:
Effective relationship management is critical to successful fundraising within any organization. Relationship management and metrics describe a system of information tracking tools, reports, policies, processes and measurable actions that organizations can use to 1) move prospects through the continuous fundraising lifecycle 2) chart progress to goal and 3) provide data-driven insights and strategic recommendations to key stakeholders. In this session, attendees will learn how to use relationship management and metrics to improve the acceptance of data analytics, models and services as evidence-based tools to provide context, content and competitive advantage.
Looking forward to sharing insights, expertise and decision support recommendations with the APRA community.