By Brian Smith, Communications Specialist    

Members at your association want to be completely sure that when they are paying their annual dues, they are investing in a full experience that brings them value.  

For trade associations, institutional members might expect value in the form of internal educational resources they can share with their staff on community forums. For professional associations, value could mean hosting interactive monthly meetings for your members – providing access and business opportunities to a network of like-minded executives. 

But without collecting and leveraging data, quantifying the expected return on investment (ROI) for membership is an arduous project. 

Our on-demand webinar with Web Courseworks CEO Jon Aleckson and Don Worthley of Element 11 – Using Data to Prove Membership ROI – covers the development of an ROI dashboard for members by pulling datasets from your AMS, e-commerce, Learning Management System (LMS) and other business intelligence platforms. Below are some key highlights from that session. 

What is a Data Maturity Model? 

Before we dive into the different types of data analytics, it’s important to realize your association’s adoption, or lack there of, of data as a driver of business decisions. Are you still in the infant stages of digital transformation at your association? Or have you already reached the point where data drives decision-making?  

The data maturity model allows nonprofit executives to identify what can be improved in their data governance policy. According to Aleckson and Worthley, your association probably falls into one of these three data awareness categories: 

Data Aware 

Used to describe associations that may have access and contribute to standardized – or customized – data reports but are not actively utilizing an AMS or other business platform to drive decision-making. 

Data Proficient 

The next tier above data aware. This implies your association has a centralized data platform and that your staff actively utilizes the system to input data related to your indicated Key Performance Indicators (KPIs). However, decision-making strategies and implementations are still mixed between “gut feeling” and “data–driven.” 

Data Driven 

A successful digital transformation journey ends with a data–driven culture at your association. To be data–driven means, “embedding data into all business process,” so that no decision is made without reviewing the relevant data. Part of a data–driven culture is a clearly defined digital governance policy that outlines how data is collected, shared and utilized between members, non-members and staff. 

What is Data Analytics? 

Many enterprise associations store petabytes of information in the form of raw datasets, tables and big data queries, but what does it all mean and how can it help your association?  

Put simply by Informatica, data analytics is the process of extracting this raw data through, “specialized computer systems,” that, “transform, organize, and model the data to draw conclusions and identify patterns.” Today’s ideal data analytics platform for nonprofits showcases a complete view of membership and the nonmember market, provides AI predictive functionalities and integrates with a recommendation engine. 

As Jon mentions in the webinar, data analytics involves data-guided association decision making that leads to measurable outcomes that can be evaluated and acted on. There are three main categories of data analytics: 

Descriptive 

With descriptive data analytics, you and your colleagues can discover more information about who your members really are. Here are some questions that can be answered with descriptive analytics: 

• How often are members engaging in training certification courses?  
• Which members are engaging more frequently?  
• Where are your members located?  
• What are they saying about your association’s online experience? 

Predictive 

The definition is in the name. Predictive data analytics gives association managers projections regarding membership engagement, event management and financial reports. Data collected here answers the following questions:  

• How many learners will we have in this specific professional development course? 
• How many members will attend this event? 
• Which type of members will attend this event? 

• What’s the proper price point for this product in our online store? 

Prescriptive  

Think of prescriptive data analytics as the, “You might also like,” list feature when you are shopping on Amazon.  

Prescriptive data analytics produces and suggests value recommendations for your association’s members. In the case of an online learning product like Web Courseworks’, that means suggesting which courses to apply for that will allow members to receive their certifications. These suggestions are based on internal scores that are standardized in LMS data. The LMS data includes course descriptions, tags and profile metadata. 

Closing Thoughts 

Your association can no longer afford to manually input data and develop advanced analytics reports, especially with the various automated services and platforms available to end-users. The emphasis on data analytics and visualizations at national conferences and events confirms that there is an exciting opportunity to fundamentally transform how associations operate their business processes.  

Whether it’s a trade association looking to provide institutional members with detailed financial reports on disruptive industries and potential international markets, or a professional association developing an entirely updated curriculum for onboarding new and student members, data will certainly play a front and center role in the successful of the project. 

Wondering how your association can use data to make more informed decisions about your events? Download our e-book, “Revolutionize Your Annual Meeting.”