Creating a donor profile in T-Stats?

So excited to try this!

THANK YOU!

Marie

---

Marie Kocher | Development Assistant

Kansas City Ballet | Todd Bolender Center for Dance & Creativity

500 W. Pershing Road, Kansas City, MO 64108

816.216.5582 (D) | 816.931.2232 x1382 (O) | 816.931.1172 (fax)

kcballet.org

From: Tessitura Development Forum [mailto:forums-development@tessituranetwork.com] On Behalf Of Amanda Freeman
Sent: Thursday, August 25, 2016 5:46 PM
To: Marie Kocher <mkocher@kcballet.org>
Subject: RE: [Tessitura Development Forum] Creating a donor profile in T-Stats?

Hi Marie(s)!

I'm sure the community will share some great ideas with you, but one approach I've presented previously is what is called the POWER approach. That stands for Profile, Overlay, Weigh, Extract, Review. It's cheesy but easy to remember.

The gist of the approach is this:

Most donors at some point are also ticket buyers. So you can generate a report (or reports) in the Tickets cube, filtered to just donors. You can do this using the Const Sum Total Giving Range attribute, or Current Member Level, or however else you want to identify the constituents who are the kind of donors you're trying to profile. You could also use a list-based filter so you know you're only reporting on those people who are the types of donors you're after. So in the first step,  you're making sure to look at people who already ARE donors.

Then you decide: OK, what fields can give me insight into the behaviour of these people?

So you start with a hypothesis about these donors. You know your data so you probably have an idea of where to start, but some examples might be "donors like certain types of seats" or "donors like certain types of performances" or "donors come certain days of the week".

So you might drag zone, or genre, or day of week into your report alongside Num Constituents. You'll test those theories: what types of seats do they seem to like? What types of performances are they gravitating toward? Sort and see what's most popular.

Then adjust your filters to add the non-donors back in to the report.

Does the pattern change?

If the pattern is roughly the same with and without the non-donors, then the item you are looking at is probably not a distinguishing factor about donors. If it's very different, then maybe this is something worth noting.

Repeat the process a few times, maybe by zip code, matinee vs evening, or other factors.

Once you've concluded you've identified a few decidedly donor-like qualities, you overlay. Let's say by doing the previous step you concluded my donors live predominantly west of your venue, go to matinees and participate in pre-sales.

Now you want a new report in the Tickets cube just limited to non-donors. You want to filter this report to all the factors you decided above are common among your donors. So you're looking for non-donors with donor-like tendencies.

Next you weigh the profiled segments: so you take your report that's filtered to western, matinee loving presaling non-donors and save that as a list. Let's say we weight these prospects a 3, because they match all three of your donor profiles. You can remove one of the filters, save that list and weigh it a 2, and so on, until you have a list of prospects for each combination of your donor-like properties, weighted by how many donor-like qualities they match.

Next you'd want to go into Extractions and start with your standard suppressions (do not contact, no valid contact info, etc), then add the lists you just created in weight order. Then extract and proceed with your telefunding, or direct mail, Plans or however you intend to approach these prospects.

Later, you can keep tabs on the results in T-Stats too. Say all of the prospects above went into inside sources under their own appeal. You can go into the Memberships cube and filter to that appeal, and current record, and the desired membership org, and look at the Num Memberships or Total Memb Amt. Or if you have a list in Tessitura that is everyone included in the above extraction, you could filter your T-Stats report on that. You might also do similar filtering in the Contributions cube to review contributions associated with these folks, rather than strictly memberships.

I hope that helps!

So excited to try this!

THANK YOU!

Marie

---

Marie Kocher | Development Assistant

Kansas City Ballet | Todd Bolender Center for Dance & Creativity

500 W. Pershing Road, Kansas City, MO 64108

816.216.5582 (D) | 816.931.2232 x1382 (O) | 816.931.1172 (fax)

kcballet.org

From: Tessitura Development Forum [mailto:forums-development@tessituranetwork.com] On Behalf Of Amanda Freeman
Sent: Thursday, August 25, 2016 5:46 PM
To: Marie Kocher <mkocher@kcballet.org>
Subject: RE: [Tessitura Development Forum] Creating a donor profile in T-Stats?

Hi Marie(s)!

I'm sure the community will share some great ideas with you, but one approach I've presented previously is what is called the POWER approach. That stands for Profile, Overlay, Weigh, Extract, Review. It's cheesy but easy to remember.

The gist of the approach is this:

Most donors at some point are also ticket buyers. So you can generate a report (or reports) in the Tickets cube, filtered to just donors. You can do this using the Const Sum Total Giving Range attribute, or Current Member Level, or however else you want to identify the constituents who are the kind of donors you're trying to profile. You could also use a list-based filter so you know you're only reporting on those people who are the types of donors you're after. So in the first step,  you're making sure to look at people who already ARE donors.

Then you decide: OK, what fields can give me insight into the behaviour of these people?

So you start with a hypothesis about these donors. You know your data so you probably have an idea of where to start, but some examples might be "donors like certain types of seats" or "donors like certain types of performances" or "donors come certain days of the week".

So you might drag zone, or genre, or day of week into your report alongside Num Constituents. You'll test those theories: what types of seats do they seem to like? What types of performances are they gravitating toward? Sort and see what's most popular.

Then adjust your filters to add the non-donors back in to the report.

Does the pattern change?

If the pattern is roughly the same with and without the non-donors, then the item you are looking at is probably not a distinguishing factor about donors. If it's very different, then maybe this is something worth noting.

Repeat the process a few times, maybe by zip code, matinee vs evening, or other factors.

Once you've concluded you've identified a few decidedly donor-like qualities, you overlay. Let's say by doing the previous step you concluded my donors live predominantly west of your venue, go to matinees and participate in pre-sales.

Now you want a new report in the Tickets cube just limited to non-donors. You want to filter this report to all the factors you decided above are common among your donors. So you're looking for non-donors with donor-like tendencies.

Next you weigh the profiled segments: so you take your report that's filtered to western, matinee loving presaling non-donors and save that as a list. Let's say we weight these prospects a 3, because they match all three of your donor profiles. You can remove one of the filters, save that list and weigh it a 2, and so on, until you have a list of prospects for each combination of your donor-like properties, weighted by how many donor-like qualities they match.

Next you'd want to go into Extractions and start with your standard suppressions (do not contact, no valid contact info, etc), then add the lists you just created in weight order. Then extract and proceed with your telefunding, or direct mail, Plans or however you intend to approach these prospects.

Later, you can keep tabs on the results in T-Stats too. Say all of the prospects above went into inside sources under their own appeal. You can go into the Memberships cube and filter to that appeal, and current record, and the desired membership org, and look at the Num Memberships or Total Memb Amt. Or if you have a list in Tessitura that is everyone included in the above extraction, you could filter your T-Stats report on that. You might also do similar filtering in the Contributions cube to review contributions associated with these folks, rather than strictly memberships.

I hope that helps!