In this series, we’ve talked about capturing good, clean data. And, we’ve talked about building a segmentation scheme and what should factor into that. Once you know what your needs are, you’ll want to be to calibrate the size of your segments for a given campaign. In this case, size does matter.
Too big. Too small. Just right.
Remember the story of Goldilocks and the 3 bears? Put aside for a moment the fact that the hero broke into a house and slept in the beds of complete strangers. The point of the story was that “just right” is a moving target. Let’s return to the beds in the story. The beds were too big, too small, and just right for Goldilocks. Similarly, your segments can be too big, too small or just right.
A campaign could have a few segments that are very big and broad. You don’t want to have segments that are too big, where you can’t get specific enough for the message to carry contextual weight. A campaign could also have a LOT of really small segments. You don’t want to have segments that are too small—so many segments that it’s difficult for you to manage, or the granularity of segmentation doesn’t actually matter.
What does “just right” look like for you? “Just right” changes from campaign to campaign, and shouldn’t be considered inflexible.
In the second video
we talked about purchase behavior drivers
that can be used to determine your segmentation scheme on a larger scale. Once you’ve determined a segmentation scheme for your database, you’ll then apply it to individual campaigns. Let’s look at how a larger segmentation scheme applies to a specific campaign now.
Taking the example of a renewal campaign that incorporates a donation ask. Invoices will be customized, but we may have to make several different templates that are customized to our patrons’ prior experience with the organization.
What matters from a messaging standpoint?
- how long they’ve been a subscriber
- if they’ve given before
If we’ve set up our segmentation scheme right, we can segment into these categories of patrons. What else might matter? We could segment further by the length of time they’ve subscribed:
- first time subscriber subscribed for 2-3 years
- Subscribed for 4 or more years
What else might matter? Well, if you have detailed donation information in your segmentation scheme, you might know which of them
- haven’t donated,
- have given under $100
- have given $100-1000
- have given over $1000.
What if your organization sells two different types of subscriptions: full series subscriptions, and choose-your-own subscriptions? If I have collected and tracked the type of subscription within each subscriber type, I can add this level of detail to my segments.
This is a lot of different segments, and these segments are very granular.
You might have the ability to segment to this level, or not. That depends on a number of different factors. And, even if you can segment at a very granular level, will having that many segments help you deliver relevant messages? And, will you have the resources to create those different messages? Remember, you don’t want to have so many segments that it’s difficult for you to manage, but you also want to talk to people like you know their history. You want to be specific enough to be relevant—and impact response rates to your campaign.
There’s not one “right” way to do it, but you need to find balance between segments that are too big or too small. What’s going to matter and not kill your staff? Look at what you have and figure out what’s reasonable.
In this case, what is the goal of the campaign? Remember that this is a renewal campaign with a donation ask. So, you want them to renew, and possibly add on a gift.
So, which of these categories get separate communications?
You may be thinking that all this is a function of your database administrator or an assistant that pulls lists for your marketing and development communications. But, the decision on who gets which message should be delivered which groups should be made before the list pull. Every level of your organization needs to start thinking in terms of delivering personalized, targeted messages.
In this example, you can imagine that marketing and development will need to agree on who gets a special invoice. In this case, marketing and development talked and determined that major donors needed to have specialized messaging. Also, marketing decided that first-time subscribers need a special invoice that walks them through the renewal process. In this org, the invoice already takes into account differences between Choose your own and full subscriptions, and an algorithm created last year determines how much the subscriber will be asked for.
Your first steps: How do you begin to use this type of strategy at your organization?
Remember that the data doesn’t do the work for you. Only you can prevent ugly data. Get your segmentation right, and developing patrons relationships becomes that much easier.
- Start with sharing these ideas with your colleagues. Bring it up at your next staff meeting or cross-departmental check-in.
- Discuss what this would look like at your organization, and who should be making decisions about the size of segments.
- Begin asking questions about what your different segments could be.
Is your data ugly? Your arts organization may have terrific branding, a high converting website, a top-of the-line CRM system, and beautiful photos of your productions or exhibitions. Unfortunately, if the data you have on your patrons is dirty, incomplete, or poorly segmented, building patron relationships and loyalty is much harder. That’s why data stewardship, the ongoing process of maintaining data for action, is so important. In this video, Kevin Replinger of TRG Arts explains the beginning steps of data stewardship: capturing data and keeping it clean.
How does a well-planned and consistent segmentation strategy make your job easier? It will help your organization effectively market to patrons, targeting certain segments for certain offers, and help you understand your patrons’ behavior. In this video, Claudia van Poperingen of TRG Arts explains how to organize and segment your data so it’s strategically divided into easiest-to-use groups.