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Who is sharing nonprofit demographic data with Candid? 

Candid

Since 2014, Candid has been collecting demographic data about the people who work at U.S. To date, over 54,000 organizations have shared some data about how their staff and/or board identify by race/ethnicity, gender, sexual orientation, and/or disability status. Demographic data sharing varies by nonprofit subject category.

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Demographics via Candid: Building a movement to promote equity in the social sector

Candid

A lack of standardized demographic data not only hinders our collective work to create a more equitable sector; it also requires nonprofits to take time away from their mission-driven work to respond to disparate requests by funders for this information.

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Four Steps to Align Data with Your Mission and Goals

Association Analytics

Data provides actionable insights and can give associations a navigable path to make better informed business decisions. And yet, the ability to use data to serve your association’s mission has never been more important and timely. Developing a SMART goal is seldom complex from a data standpoint. Develop KPIs for Your Goals.

Goal 192
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Member Retention Strategies For Professional Associations

Association Analytics

You should segment your membership by the metrics that matter most to you, such as demographics, tenure, behavior, at-risk status, periods of time and more. Understanding why these members engage more — or digging into data around less engaged members — will help you to determine how to build effective membership retention strategies.

Retention 169
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Use These 11 Metrics To Evaluate Your End-Of-Year Fundraising Campaign

Bloomerang

In this post, I’ll walk you through why that’s important and what metrics you should measure. . Goals and metrics . Looking at this data will help you make informed decisions and have an accurate picture of your organization’s health. . 11 metrics to evaluate your end-of-year fundraising campaign . Donor demographics .

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Don’t Fear Your Dirty Data

Association Analytics

The concept of “dirty data” and how to approach it can be daunting. Simply put, dirty data is data that is inaccurate, incomplete, inconsistent, duplicative, or outdated. At Association Analytics, we sometimes hear concerns about data quality in the context of associations starting their journey into analytics.

Data 169
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Level Up Your Marketing with Analytics

Association Analytics

Fortunately, with data, we can better understand members’ behavior and which marketing channel is most effective to reach our members. This is how you organize and describe your data. If you don’t tag your data accurately, it will be difficult to actually see what is going on. Sales are instant. Analyze Performance.

Analytics 169