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Top Ten Data Challenges (And Solutions) for Associations

Association Analytics

7: Your Taxonomy Isn’t Organized In a Useful Way Challenge : Digital closets are a lot like physical closets. Whatever the case, if your organization doesn’t keep your taxonomy tidy, you’ll spend more time querying and comparing reports than finding the data you need the first time. Focus on what matters to operational outcomes (ex.

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To Get Close to Members, Follow MarTech Trends

.orgSource

Instructions, such as a style guide and taxonomies, are part of this process. They must also provide the authority and guidance that unites strategy, brand, and voice across the organization. But ongoing inter-organization communication and dialogue are even more important.

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3 Design Thinking Facilitation Resources for Nonprofits

Beth's Blog: How Nonprofits Can Use Social Media

The many methods of Design Thinking go through a similar path of gathering research, analyzing and identifying the right problem, developing creative ideas, and testing prototypes. Almost four years ago, I wrote my experience as a participant n a design-thinking lab to give input on a digital strategy for a philanthropy.

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Data-Driven Strategies to Revolutionize Your Association’s Content Marketing

Association Analytics

Associations sit on a trove of valuable information as members look to grow their career and improve themselves, it’s the delivery that is the problem. This content personalization and curation is vital to associations, as members look more and more for the information that matters to them with having to work for it.

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Nym Health raises $16.5 million for its auditable machine learning tools for automating hospital billing

TechCrunch

Billing has been a huge problem for healthcare systems in the U.S., Nym claims to have solved the problem by developing technologies that can convert medical charts and electronic medical records from physician’s consultations into proper billing codes automatically.

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Getting Specific about AI Risks (an AI Taxonomy)

fast.ai

Misleading marketing hype often clouds distinctions between different types of tasks and suggests that breakthroughs on narrow research problems are more broadly applicable than is the case. Furthermore, the nature of the risks posed by different categories of AI tasks varies, and it is crucial that we understand the distinctions.

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Pixyle AI wants to make visual search more intuitive for online retailers

TechCrunch

Many retailers deal with that problem by manually entering better product data, but that process is labor-intensive, expensive and prone to human errors. Retailers often get incomplete and inaccurate product data from brands of people listing secondhand items for sale, which means items don’t show up in search results.

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