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Essential Steps for Tracking and Reporting Association KPIs

Association Analytics

Leveraging your data throughout the entire member journey can impact your association and your members. From successfully converting non-member audiences into members, to your membership engagement strategy, to events and non-dues revenue, data can inform every step along the way.

Track 169
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4 free ways to access Candid’s demographic data 

Candid

Comprehensive and public nonprofit demographic data is central to supporting more transparent and informed decision making in our sector. Our purpose at Candid is to get key information—like this demographic data—into the hands of those who rely on it to guide their decision making. nonprofits and foundations.

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Demographics via Candid: A data-driven approach to encourage equitable funding practices

Candid

By better understanding the demographic profile of those organizations that are—and are not—receiving funding, we can more closely track if they are representative of the communities they serve and whether they are getting the support they need to deliver on their missions. Introducing Demographics via Candid.

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Are you getting the most out of your retention data?

Association Analytics

Many factors are important to consider: tenure, type of membership, demographics, how the member was acquired, how the member is engaging with your association, and more. Analyzing this data is challenging as it typically resides in multiple systems (e.g. Demographic/Career Info. Schedule a demo to learn more.

Retention 192
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What to know about U.S. nonprofit sector demographics 

Candid

What’s the demographic composition of the U.S. The report aims to increase transparency about diversity in the sector, highlight key findings at the macro level, and offer a snapshot and baseline with which to track efforts related to diversity, equity, and inclusion. Are staff, leaders, and board members equally diverse?

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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 Simply put, dirty data is data that is inaccurate, incomplete, inconsistent, duplicative, or outdated.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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Are you getting the most out of your retention data?

Association Analytics

Many factors are important to consider: tenure, type of membership, demographics, how the member was acquired, how the member is engaging with your association, and more. Analyzing this data is challenging as it typically resides in multiple systems (e.g. The post Are you getting the most out of your retention data?

Retention 169