5 Common Mistakes Associations Make with Data (And How to Fix Them)

Every association should be using their member data to improve their member experience. It gives you essential insights into what members want, and it’s a helpful jumping-off point for setting up automated marketing campaigns, community automation rules, program development, and more. But it’s easy to make mistakes when working with large quantities of data.

• How do you know what data to pay attention to?
• How do you ensure your data gives you trustworthy insights?
• How do you keep everyone working on your data project on the same page?
• How do you efficiently turn data points into real improvements and actions?

In this article, we’ll outline some common mistakes associations make with their member data. Then we’ll walk through some additional resources to ensure you’re using your member data to best effect!

Mistake #2: Going Too Big

Once you start looking into data, you will find it everywhere. There are so many places you can gather insightful data!

• Observing member behavior on your website using web-tracking
• Monitoring member engagement, frequently asked questions, and discussion topics in your online community
• Engagement with your marketing and community emails, including opens, clicks, and what people click on
• Common roles and responsibilities in your industry from your organization’s job board
• Learning pathways and course completion your LMS
• Opportunities to help members move forward on their credentialing journey

The list goes on and on. Basically any platform your members use to interact with your organization is someplace you can learn about their behavior and interests. Pretty soon you’ll feel overwhelmed by a laundry list of a hundred “nice to have” data projects.

The Solution: Prioritize Based on Goals

A huge list will overwhelm you and your team. Start with a small project with a clearly defined goal, then build from there. Discuss the exact list of metrics you need and, more importantly, how you’re going to use them. Then focus on the one or two metrics that really matter to you over a specific time period. And refer back to the solution from mistake #1 – what are existing processes you already do that you could enhance with data.

Mistake #4: Keeping Data Siloed

You can’t make decisions with data if you don’t have the whole picture. Documenting your data progression over time — whether it’s in dashboards, reports, or AI-powered tools like Power BI — will show you what matters and what doesn’t. When your data is disconnected, it’s harder to put the pieces together and act on that data.

The Solution: Centralize Your Data

Connect and integrate your sources of data whenever possible. You can use all-in-one solutions like Higher Logic Thrive, which offers integrated platforms for your online community, marketing automation, learning management, credentialing, job board, and more! Or you can look for technology solutions that play well together (Higher Logic has got you covered there too – our platforms integrate with many industry-leading solutions).

Essentially, just make sure your data accessible across your technology systems. The better cross-platform connection you have, and the more you look at your data across all those sources, the better you’re able to understand the full member journey and use your data to take action. For example:

• You could use a member’s participation in a community discussion on a specific topic to follow-up via email with resources related to that topic (and you could automate that email!)
• You could send members more information about your credential program based on their behavior on your job board.
• You could use engagement scoring to trigger outreach based on things members have engaged with in the past.
• As you incorporate AI tools and features to improve your ability to segment and personalize your member experience, having interconnected data will be even more important for driving impactful results.

The end result: centralized (or at least interconnected) data sources lead to a better member experience, more member acquisition, improved retention, and even increased non-dues revenue (NDR).

Mistake #5: Poor Data Management

Many of us have probably been there: you put in the effort to pull data reports and create a dashboard to start analyzing the data, only to realize something in the data is making you worry that the data itself isn’t trustworthy. It could be outdated data (e.g. something that hasn’t been updated since a member joined five years ag), a lack of data quantity (e.g. only 30% of members filling out a field in their account), or simply outliers in your data set that are skewing your results.

Another problem you probably run into is data being spread out in so many places you can’t find what you’re looking for. (Maybe it even keeps you up at night worrying that all the random spreadsheets on your shared drive can’t possibly be secure or GDPR compliant).

The Solution: The Right Technology and Processes

When you collect data, you should always think about the format you’re collecting it in, how you’re storing it, and your process for ensuring it’s updated and accurate.

• When you set up fields for data collection and storage, are you using the right field type for the data type (e.g. if it’s a date, it makes more sense to use a date field than a free-form field that will introduce inconsistency).
• Discuss, at an organizational level, your process and schedule for trying to keep information updated. This might include running an annual “Update your account information” campaign with your members, or internally reviewing fields in your systems to make sure your data is complete.
• Do a data inventory. Discuss what data you have where – and if there are duplicate sources for a certain type of data, make sure you have an understanding of which source is the source of record.
• When you undertake a data project, make time to put together a shared plan and schedule time for data validation to ensure you have an understanding of your data quality and limitations.
• Make sure you’re using trusted technology tools to keep it secure. To meet modern member expectations, many organizations have more tools in their technology stack than ever before. This is great for meeting members’ needs, but it also means more opportunities to lose track of your data or introduce inconsistencies between different platforms if you’re not using integrated or connected systems. (The solution to mistake #4 helps here too!)

Data cleanliness isn’t the easiest or most fun task, but it’s essential for getting reliable insights. As organizations incorporate more AI tools, data hygiene and information architecture will also become even more important so that AI can access accurate data from which to generate content and insights. So now’s the time to discuss your processes and the way you organize and store information.