by Brad Pilcher
In Part I of this piece, I encouraged you to think of data and its relationship to audience building more in terms of a process. Rather than focus on the data, in all of its intimidating glory, focus on your circumstances, where you are in the process of connecting with the audience you have (or the audience you want).
I also hinted that if you were still struggling to wrap your head around data, you’d be pleased to know it could be broken into three types. So, what are they?
Super-Macro data is generalized, not-specific to any single organization or audience. It’s limited in its ability to predict for your specific circumstances, but many groups think this is the easiest data to work with.
When you’re small, lacking in resources or expertise, that can be true. After all, most of this data has already been collected and analyzed by groups like the National Endowment for the Arts, who issue freely accessible reports.
But Super-Macro data isn’t just packaged information like NEA reports. It can include a survey of ticket prices from other arts groups like yours across the region, a survey you may have to do yourself.
What you should know about this type of data is what it is often used for: positioning yourself within your market. In other words, it can tell you how audiences are behaving beyond their relationship to you.
Let’s take the example of that survey of ticket prices. Maybe you discover that your ticket prices are considerably lower than the average. That might mean you could afford to increase your prices (and thus your revenue) without your audience batting an eye. Alternatively, it might mean you could emphasize your value in marketing, targeting new audiences that care about thrifty options.
Other types of super-macro data are equally helpful in giving you big picture snapshots of your existing (or potential) audience. For example, [publicly accessible ESRI data] [ http://www.esri.com/landing-pages/tapestry ] could give you a snapshot of the general lifestyles in your area. Just plug-in your ZIP codes, and you’ll have a sense of what audience is nearby.
So if Super-Macro data is the most generalized, least specific data, then Macro data must be less general and more specific, right? Well yes, and no.
Macro data is still generalized, but it does have a specific link to you. More specifically, it’s about your audience.
For example, you might compare year-over-year trends in your attendance. This would offer general conclusions about the popularity of your programming. Audience surveys after a program will give you a snapshot of satisfaction among your existing audience.
None of this data is specific to any particular member of your audience, but it’s very useful for responding to shifts in your relationship to your audience. What’s the old saying? A bird in the hand is worth two in the bush.
Where Super-Macro data helps position you in the market, Macro data helps you stay ahead of shifts in taste or behavior. It will help you maintain your good relationship with your audience.
Imagine that you introduced a decrease in prices last year, in an effort to attract new ticket buyers. Did your average ticket sales per show increase? Or what if you didn’t do anything to your prices, but ticket sales declined anyway? Now you have a problem that needs exploring, but at least you know!
In fact, this is a very good example, because it shows that almost every group has some data. You know how much money you earned last year, and you probably have a pretty accurate count of how many tickets you sold. That’s very useful data just sitting there [waiting to be analyzed]
[ https://www.lynda.com/Data-Analysis-training-tutorials/1303-0.html ].
Then there’s the most specific, most personal type of data. This is perhaps the scariest type of data for groups who aren’t used to doing much data collection and analysis.
After all, keeping track of information specific to individual audience members requires special databases and training on how to use them. You have to ensure you respect people’s privacy. You have to figure out new ways to induce people to reveal more about themselves.
Let’s be honest; yes, this can be the hardest data to get involved with. It does require a certain level of investment, planning, and training.
But – yes, there is a but – it’s not quite as complicated as you think. There’s an increasing number of tools that are relatively affordable, and will help you utilize Micro data effectively.
The question is, why bother? What does Micro data get you? The answer is, when used correctly, this kind of individualized data will help you engage with your audience more efficiently, and with a personal touch.
Link your database of supporters and audience members (called a CRM – [Constituent Relationship Manager]
[ http://www.idealware.org/articles/search-crm-understanding-constitutents-and-processes ]) to third-party marketing tools, and suddenly you can target your emails based on a person’s interests and past behavior.
Don’t spam them with emails about programs they may not care about. Audiences are more likely to respond if you tell them about events that align with their interests. Try sending them something for their birthday. You can talk to them like you know their name, and who they are, because well… you do.
If you were to do this manually, you’d spend hours upon hours of staff time handling these kinds of calls and emails. But if you track the data in a CRM, and link that system to platforms like your email marketing tool, you can create simple automations that handle the work for you.
Yes, this will require thoughtful work at the beginning; you will have to setup these systems, after all. But once you’ve got everything running, you’ll be amazed how much more effective even a small team can be.
What Do You Need to Do, Right Now?
What is important to remember is that while all of this may feel intimidating, it doesn’t have to be. Audience building happens in slow spurts. It takes patience and a dedication to do little things that eventually add up to big things. It is hard work.
Data won’t change that, but it will let you work smarter, instead of harder.
Start with what you need, or rather what you need from your audience. Then, and only then, start figuring out which type of data will get you there. Believe it or not, most of your answers will flow naturally from that point. Why? Because you’ll have a context, a process, in which to find answers.
That’s what data-driven decision-making is really all about: a process, where data plays a part, and you play all the rest.
Well, you and your audience.