Internal Data Analysis

The following is an excerpt from our book, Pricing for Associations, available now on Amazon.

When embarking on the journey of creating a new association product or upgrading an existing one, tapping into your organization's internal data can be a game-changer. This internal product data is a goldmine of insights, providing you with a comprehensive understanding of your audience's preferences, behavior, and needs. By examining this data, you're not starting from scratch; you're building upon a foundation of knowledge specific to your own audience.

Your existing products have been engaging with your audience over time, and this history holds valuable clues. By analyzing related audience trends, you can identify patterns and preferences that are specific to your members or sponsors. For instance, you might discover that a particular segment of your audience consistently values networking opportunities or prioritizes professional development. These trends inform the features and benefits you should emphasize in your product to resonate with your core audience.

The beauty of internal product data lies in its potential to reveal hidden trends and patterns. By delving into data from prior surveys, focus groups, one-on-one interviews, discussion boards, or forums, you can uncover insights that might have gone unnoticed otherwise.

Improving Data Quality

The phrase "our data sucks" is more common than you might think. Many associations face the challenge of incomplete or outdated member data, leaving them in a quandary about where to start in their journey toward data-driven decision-making. If you are in this situation, fret not; you're far from alone.

Let's begin by acknowledging that data woes are part and parcel of the association landscape. Among the multitude of organizations we collaborate with each year, nearly all voice similar concerns. Even those who express confidence in their data quality often admit that it falls short of their desired standards.

So, breathe easy—your organization isn't lagging behind your peers. The challenges you face are shared across the industry.

Quality Over Quantity

When it comes to data, quality over quantity is the golden rule. It's better to have accurate but limited data than to drown in a sea of inaccuracies. Imagine grappling with fields filled with information that's a decade or more outdated. Cleaning such data or sifting through obsolete entries to establish meaningful segments is daunting.

This underscores a vital point: Data management is an ongoing effort, not a one-time fix. Data evolves, and maintaining its accuracy is a continuous journey.

If you're currently grappling with insufficient data, here are some actionable steps to work toward clarity regarding the value you should offer and, subsequently, the pricing you can apply:

1. Prioritize Key Segmentation Questions:

You'll never achieve 100% data completion across your entire database. Instead, focus on obtaining a substantial and representative sample. Start by identifying three to five essential segmentation questions that will help you create detailed personas for your audience. As a team, decide which factors are most crucial. These might include seniority level, certification status, educational background, years of industry experience, or if they are in a purchasing decision-making role.

2. Streamline the Data Collection Process:

To encourage data submission, keep the process quick and straightforward for your audience. This may require additional manual work on your end. Rather than overwhelming members with a full profile update, consider sending them a survey with just three to five critical questions. Request they use the email on file with your association, and have your team perform a CSV upload into their profiles. If your AMS lacks this feature, you might need to add data manually, which, though time-consuming, is worth it for high-quality data.

3. Determine an Adequate Sample Size:

Don't aim for every member to complete their profile; it's not realistic. Look at your email click rates, which typically range from 1% to 3%, possibly higher for exceptional content. Target a similar proportion of your audience to click through and potentially provide the needed information. For instance, with a database of 30,000 members, aim for 300 to 900 respondents. Keep in mind that not all who click will complete the survey, so you may end up with 30% to 50% of this number providing answers for your personas.

In the complex landscape of data management, there's no easy fix. If there were, the creator of the solution would be a millionaire for solving one of the association landscapes' most significant challenges. However, there is a practical path forward. It may demand effort and intention, but it's a route that can deliver the results you need. By following these steps, you can gain a clearer understanding of your audience and how best to engage with them, ultimately enhancing your ability to create personas based on their unique characteristics.