Whether you’re setting annual performance goals, making changes to association programming, or moving into a new membership service, no decision should be made without first examining the previous years’ data.
Oftentimes, associations will entrap themselves in the mindset of establishing long-term marketing or membership-service objectives with just a “gut feeling.”
Lucky for you, your association may have been collecting useful information through their association management system (AMS), customer relationship management (CRM) software, or data management tools without even realizing it.
Furthermore, these useful insights can tell you what you did, what you can do better, and how you can accomplish your future goals by reading the story between the lines.
So where do you start? How can you use your own data to improve the decisions you make?
Layer in different measurements
Specifically, when it comes to your marketing goals, you need to understand what you’re tracking before you turn that information into actionable items. All of the campaigns you run can be quantified into three major categories:
1—Interactions
Typically the most common campaign-data mechanism, measuring interactions gives you a surface-level view on how your audience engages with the content and marketing channel anchoring your campaign. Common examples include open and click-through rates from email, and bounce rates on your web pages.
2—Attributable conversions
For a more in-depth view on your marketing initiatives, you can start evaluating attributable campaign conversions. This measures the performance of your campaign in respect to your definition of success. For instance, if 10 net new members sign up in March, and you can directly correlate 8 of those as a result of your campaign efforts, that's an attributable conversion.
It takes your analysis a step further from “are they engaging with our content?” to “are they completing the action we intended them to complete?” Plenty of digital automation platforms will measure this for you through built-in conversion tracking, campaign tagging, and tracking code functionality.
3—Return on investment (ROI)
These metrics give you the strongest view of marketing campaign efficacy. The key to this metric is that it hinges entirely on the conversions collected.
Essentially, the ROI is determined based on the total monetary value of the conversions collected, and/or on the Member (or Customer) Lifetime Value (MLV) associated with those conversions.
In other words, for the 8 net new members you just brought in from your marketing efforts, each of those members joined at $500 for the year. And maybe you spent $1,000 on paid advertising to bring them in. Reporting on ROI for those conversions would bring you to $3,000.
8 x $500 = $4,000
$4,000 - $1,000 = $3,000 ROI
But let's say that, upon becoming members, each of those individuals is projected to engage in specific revenue-driving programming over the course of their life-span (let's say your AMS tells you the average is 3 years).
Given what you already know about your members based on the transactional data held in your AMS or CRM, you know that they're consistently engaged in
conferences, webinars, certifications—all to the tune of about $2,000 on average a year.
Multiply that by the number of years, on average, your members tend to remain members (remember, it's 3 years) and now you're looking at a different number:
3 x $2,000 = $6,000 (for just 1 of those 8 new members)
$6,000 x 8 = $48,000 (for all 8 members)
$48,000 - $1,000 (for paid ads) = $47,000 ROI on MLV
See how this new formula justifiably changes your definition of success from a marketing perspective? You're not just reporting out on that moment in time when they converted. You're reporting out on the projected future of what that individual will do now that they're under your membership umbrella. And that projection is coming from indisputable historical data just sitting in your AMS or CRM.
Make your metrics meaningful
Any performance that you measure should be compared to either your prior years or an industry standard. Without this comparison, the data you collect has no context. For example, if you're looking to evaluate your marketing performance on campaign interactions, you should use industry standards to measure against.
Average open rates in the association world, for instance, stand at 23% of total emails opened, with clickthrough rates at 1.7%, click-to-open rates at 7.9%, and total deliverability at 99%.
Keep in mind, to truly get a perspective on non-transactional engagement, make sure you're weighting your more substantive metrics (clickthrough rates) over your more surface metrics (open rates). Despite the fact that "opens" illustrate a very low level of commitment, there a number of other factors, including Apple's new iOS policy, that dilute the value of the "open" even more.
Outline what success means to you
Every association defines a “successful conversion” differently. Regardless, by universal definition, it's the act of a member taking action on your goal. This could be in the form of registrations, file downloads, form signups, purchases, or even behavioral attributes.
Conversions also differ by departments and programs. For instance, you might use different conversion metrics for a membership signup campaign than you would for a continuing education (CE) effort.
Build a framework for insight collection
Whether you’re using a marketing tool such as
Adestra, a single-purpose email and data automation platform, or just a basic Excel spreadsheet to track campaign data, there are going to be three main objectives:
- To collect interactions, conversions, and ROI metrics
- To take a deeper dive into what campaigns worked well and what didn't
- To identify trends that can help you forecast and plan for the future
As such, you want to make sure you have a plan in place to collect these insights in systematic way.
For instance, you could divide your campaigns by predefined categories to provide more insight. Let's say you divide your campaigns based on content type which could include: general membership updates, upcoming education/training events, prospective member information, and new products/solutions.
By compartmentalizing these categories, you can compare them against each other to see which audiences are the most engaged and convertible within each of these categories.
The ultimate goal of this process is to generate marketing intelligence. As a result of the numbers you find, you might take away aggregate insights like “our click-through CTAs get higher with dynamic content,” or "our
Salary Report performs best with our entry-level audiences" or “our
1:1 membership newsletters have the highest click rates.”
Focus on improvement over time
Every performance goal should be a relative comparison to a previous time period, such as a month, quarter, or entire year. The simple time-over-time growth comparison can be calculated as (Present - Past) / Past.
To illustrate this formula, if you had an average open rate of 18% in 2020 and 20% in 2021, the growth formula shows:
20%-18% = 2%
2% / 18 = 11.1% performance improvement
Use these comparisons as improvement indicators. For example, if you compared a bunch of metrics year-over-year, saw improvements in most, steadiness in a few, but a 20% performance decrease in clickthrough rates, you need to evaluate why clickthrough rates went down so much compared to the other categories. The issue could be messaging, audience, content, or campaign timing and should be remediated for efforts moving forward.
There’s a good rule of thumb when it comes to comparing metrics against industry standards vs. comparing to your own internal benchmarks:
- Use industry standards to ensure your campaigns, as a whole, are solid and executed properly. This is really more of a benchmark to keep you current on the latest tools, techniques and practices.
- Use internal benchmarks to help you pinpoint, at a much more granular level, areas that need refinement in either marketing or, in some cases, even programming.
Set your goals with intelligence
After you’ve set your campaign performance standards, pulled the data, found interesting trends, and have drawn benchmark comparisons—you're almost ready to leverage year-end data to set your goals for the coming year.
Before you do, however, research whether there were any external factors that influenced your prior year numbers. For instance, COVID-19 variants could have impacted certain content types more than others, while Apple’s new iOS consent-based policy may have skewed open rates.
There also could’ve been significant internal issues that altered campaign performance success. Staff decreases, reallocation of resources, or cancelled events could have heavily impacted your previous year numbers. Any of these influences should be documented in your reporting so that you're making informed decisions as you set your goals.
When it comes to goal setting, there are two primary paths to take:
- Business as usual: Set goals to match or incrementally increase performance levels
- Improvement plan: Set stretch goals designed to considerably improve key performance indicators (KPIs)
Both paths yield varying levels of results. Neither method is superior to the other; it just depends on your association’s culture, resources, and what your cumulative metrics are telling you.
Ready to become a metric-centric organization? We can help.
Book a consultation with us today! We'll guide you through the data, tools, and analysis to help you set your org's performance goals.
