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Three Data-Informed Strategies for Better Member Engagement

Association Analytics

You’ll come away with specific examples from the team at the International Association of Exhibitions and Events (IAEE) that you can use to inform your own strategy. Once the team aggregated the data and they were able to form a hypothesis, test it and confirm a need.

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Study the Data, But Eat the Cake—Put the Human Factor Forward

.orgSource

You’ll recognize these examples. Confirmation bias is the tendency to place the greatest value on information that supports your pre-existing beliefs. Anchoring bias makes people rely too heavily on the first bit of information they receive. AI provides a satellite image of an entire data landscape.

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Top Ten Data Challenges (And Solutions) for Associations

Association Analytics

But when it comes to a troubling relationship with your data, can you turn to those same people? If you’re struggling to find someone to share your data woes with, we’re here to help you decipher the signs and get you back on track. Older models tended to be AMS-centric, leading to siloed data, static reports, and that trapped feeling.

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Let Data Drive Your Decisions

Bloomerang

Fortunately, data can help you make good decisions during uncertain times. Why data should drive your decisions Many key industries, including retailers, manufacturers, and healthcare organizations, use data to inform decisions. To be successful despite uncertainty, you must let data drive your decisions.

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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 Simply put, dirty data is data that is inaccurate, incomplete, inconsistent, duplicative, or outdated.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.

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Five myths and misconceptions about Candid’s grant data

Candid

At Candid, our mission is to get you the information you need to do good. This also means clearing up mis information when we come across it. In service of this, in this blog, we’re highlighting five things we’ve heard about our grants data that aren’t quite accurate. Myth 1: “Candid grants data” is the same as “990 data.”

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How to Streamline Your Grant Management Process with Technology

sgEngage

You want applications from organizations that align to your mission, but the frequency of the requests can easily bog down your processes if you aren’t careful. To avoid overwhelming your team, standardize how you receive and process grant applications at your organization. And what is the workflow once an application is received?

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