# Toward a linear RFM

In addition to the many challenges of RFM already discussed, the segmentation puts up artificial barriers between segments.  Some of these include:

• Let’s say someone is one of the people we talked about yesterday that gives every November or December.  If s/he gave in November 2014, then again in December 2015, are you really going to consider them having “lapsed” in the middle?
• The distinction between frequency groups is artificial. As we discussed on Tuesday, Sandy, who gave you 100 gifts, and Miriam, who gave you two, are both considered multidonors for most RFM segmentations.
• The distinction between monetary value segments is artificial. Which donor would you prefer – a donor who donates \$10 ten times per year or a donor who donates \$50 once a year?  RFM prefers the latter; I’m guessing you would prefer the former.

But how to do you create equivalencies among every different segment?  Would you rather have a donor who gave \$100 to an acquisition package six months ago or a loyal semi-frequent \$20 donor?

The ideal would be to run a model with lifetime value as the dependent variable and your traditional RFM variables, plus as many of the ones that we’ve talked about this week, and determine what your actual drivers of value are.

But lifetime value, as you can tell from the name, takes a long time.

So let’s steal a rule-of-thumb model from the for-profit world.  Connie Bauer first (at least first to my knowledge) proposed this in an influential 1988 Journal of Direct Marketing article called “A Direct Mail Customer Purchase Model.”  Here, I’ve replaced purchases with donations; I think it works in our world with this replacement.  To get the RFM score, you multiply these three things together:

1. The reciprocal of recency of the last donation in months.
2. Number of donations
3. The square root of the total amount of donations the person has made.

• There’s a reasonable equivalence between recency and frequency.  Would you rather have someone who has given four gifts who gave their last gift a year ago or someone who has given two gifts and their last one was six months ago?  These would be roughly equivalent in this model and that looks about right.
• It mitigates the artificial distinction between months.  That 12-month versus 13-month difference that in a normal RFM analysis could be the difference between sending and not sending a communication?  In this model, it’s about an 8% difference in scoring.  Important, but not fatal.
• Because I’ve not seen the effect of the sheer numbers of gifts have a huge impact (once you get above a certain point) on retention rate, it seems intuitive that monetary value is a smaller factor than the other two.

There are some weaknesses.  Donation amounts aren’t linear: if someone has given a \$25 gift in the past, the odds that they will go from there to \$26 to \$27 is not likely.  Some time periods, like a year, are somewhat magical, especially for one-gift-per-year, seasonality-focused donors.  And in an ideal world, you would want more recent gifts weighed a bit more than more distant gifts.  A donor’s behavior tomorrow will be more like their behavior last month than their behavior in 1988.

But given that, it’s an interesting look at the topic.  I hope the week gives you the courage and the tools to take another look at your segmentation strategy and calculations.  You’ll go nuts if you try all of these simultaneously, but conscious and continuous improvement can make huge differences in the long term.

# Vive le donor difference

When I was but a wee lad, I played youth baseball.  Or perhaps more accurately other kids played baseball at me.  I excelled in three things and three things only:

• Bunting
• Getting hit by pitches, to the point that I once got hit by a pitch that was called a strike.  I had to wait to get hit by the next pitch to take my base.
• Stealing signs.

This last was where my “talent” was.  I would watch the third-base coach and when I thought a steal was coming from the signals, I would yell into the pitcher and catcher from my position in right field.  (Of course I was in right field.  There’s a chance someone might hit the ball to left field.)  I probably caused more outs with catching signs than catching balls (though still far less than I caused by batting).

The trick to stealing signs is to look for what is different from the usual.  The same is true for catching donor signals – the trick is to look for what is unusual and work from there.  Some tips:

Seasonality: Most donors are season agnostic.  They donate when an appeal touches them or strikes their fancy or they hear about you on the news or they found a \$20 in a purse in the back of a closet.  However, some will renew membership in January like clockwork.  Others believe in end-of-year giving (this is prevalent among online donors).

Like everything else, there is a way of doing a sophisticated model to determine this.  However, like only some things, there is also a fast, relatively easy, and free way to do it in Excel or similar spreadsheet:

1. Pull all of the gifts at which you want to look.  I would recommend donors with at least three years of giving history and at least four gifts, so you have a sufficient history to work with.  You want the gifts labelled by a unique donor ID number.
2. Label all of the gifts by month (1 = January, 12 = December, and everything in between)
3. Run a pivot table that summarizes the gifts by donor with the min month and the max month.
4. Subtract the min from the max.

(If you’d like a walkthrough of this in more detail, please email me at nick@directtodonor.com)

Now look at the results.  The majority of donors will likely have a wide spread of 9, 10, or 11 months.  However, you will also see some 0-3 month spreads, meaning that over (at least) a three-year period and (at least) four gifts, they have given to you only in one quarter of the year.  Thus, you can likely reduce your costs on soliciting them in the other quarters of the year (not eliminate, as you don’t want them to forget you exist).

If you want to be very thorough, add six to each month number and repeat to capture those few donors who may focus their gifting around both the end and beginning of the year, but not the middle.

This is powerful combined with seasonality analysis; if you find someone only gives at the beginning of the year to your membership campaign and has never given to a premium piece, you don’t need to send them address labels in May or the calendar in September or telemarket to them in June.  Instead, you can use lower cost (and more cultivative) pieces like donor newsletters to maintain the relationship with them.  Yes, this may only be saving \$3 per year per donor, but if there are 10,000 of those donors on your file, you are talking about real money.

Out-of-place gifts: Someone has given you \$10 times.  They just make their 11th gift to you: a \$173 check.  What should you logically ask them for next time?

HPC says you should ask them for \$173 (possibly rounding to \$175).  Common sense says that the person may not have turned from a generally smaller donor to a prospective mid-major prospect overnight.

Research indicates a better answer is to use average donation of giving for longer-term donors.  Thus, you see the anomaly, take it into account, but don’t let it drive your decision making.

Another potential treatment is to use a continuous, rather than segmented, version of RFM.  We’ll discuss that tomorrow.

In the meantime, if you are interested in more research on ask strings and amounts you should ask for, I’m working on a book/white paper/whatever it ends up being on just that topic.  Newsletter subscribers will get a free PDF copy of it when it comes out, so if you would like one, please sign up for my free weekly newsletter here.

# Using non-donor knowledge to enhance segmentation

Yesterday, we introduced you to two special people that a traditional RFM analysis would group as 4-6 month \$25-49.99 multis.  To wit:

Since Sandy first donated to your organization in 1992, she’s given over 100 gifts.  Nothing exorbitant – she’s now giving \$30 every three or four months – but she also has volunteered, come to three walks, signed up for emails, and taken almost every advocacy action you offer.

On the other hand, you acquired Miriam from an outside list in 2012.  She gave \$25, but nothing since then.  You don’t have her email or phone number, but a last chance lapsed package piqued her interest four months ago and she gave another \$25.

We talked about how their donation history can and should differentiate them.  There are additional indicators here, however, that can also enhance your messaging and segmentation:

Online interactions.  If someone is active online, it’s relatively simple to group their interests by their activity – what they click on, look at, and interact with.  (Actually, technically, interact with is the easiest, click on is slightly harder, and look at can be a bear with some online tools.)

With Sandy, she is an advocate for you and doesn’t seem to require premiums to donate – perhaps you can replace the labels in that upcoming package with a paper version of an action alert – cheaper, and likely more effective.

Other organizational interactions.  Sandy has been a walker – do you want to mention that your walk is coming up in 90 days in the PS or in a buckslip?  Similarly, you should probably customize the messaging to acknowledge that she has given her time as well as her donations.  Making her feel known will only help her loyalty.

Outside data.  Getting outside data on your donors can help you adapt your tactics.  If you find out that Miriam does all of her banking online, perhaps she’s a better target for an EFT-based monthly gift than you thought (with the right messaging).

List co-operative data may indicate that that she gives to nine other charities far more often and more generously than to you.  Perhaps she’s just not that into you and you might want to cut your losses soon than you might have thought.

You may find out she does a lot of business on the telephone and find that it isn’t your organization that wasn’t lighting her up; it was the means by which you were approaching her.

All this and more can come from data appends.  And you can try to get that email address and engage her online, so hopefully you can learn more about her.

All of this – donor and non-donor interactions – are masked by an overarching RFM category.  But what if we could dispense with RFM categories altogether?  We’ll talk about that Friday; if you don’t want to miss it, or any of our Direct to Donor posts, please sign up for our free weekly newsletter.

# RFM segmentation alone must die

Recency, frequency, and monetary value (RFM) are the ruling troika of segmentation-land.  And like one of the old Soviet troikas, they brook no challenge to their rule (e.g., Trotsky, pictured at right, was murdered on Stalin’s orders with an ice ax).

But they are simply not good enough alone anymore.  I tried to be civil about this in my post Beyond RFM.  But beyond is not good enough.  We need to let a million flowers bloom in the world of segmentation.

This means taking the “7-12 \$15-\$19.99 multi-donor” view of segment out for a date with your ice ax.

OK, not really.  It’s still going to be a decent starting point.  But it has to stop being the ending point.  Even for those of us that have to leave complex modeling to people with more letters after their names.

So this week, I’d like to take you through various different ways of figuring out the all-important question “is communicating with this donor in this way going to help achieve my goals of net revenue, quality file growth, and/or world domination?”.

And the first topic that should be layered on is listening to what a donor’s behavior is telling you.

Part of this is non-donor behavior.  You likely already have this information if you have the donor’s email.  You can potentially tell if they’ve been to your Web site, how often, how long they spent, and what they looked at.  You definitely should be able to know how they’ve reacted to emails you’ve sent them in the past.  The difference in a lapsed donor who still regularly opens your emails and clicks on the articles versus one who, according to your email records, may or may not be dead is a significant one.

If you can get robust data, so much the better, because now you can not only include people in a communication they may not have received before, but also customize it based on what they are interested in.

But some of this is donor behavior you already know, but RFM filters out.  Channel is one. Take an online donor who is reliable and frequent at donating online.  If you’ve mailed her/him 25 times over the years to try to get him/her to donate, but s/he hasn’t responded, chances are that s/he doesn’t want to give through the mail.  Personally, I’ve found telemarketing to be the most persnickety channel: those who give through it really give through it; those who don’t, really don’t.

Another is cadence.  If someone has given you ten gifts in the past ten years and all of them have been in November or December, my money is on the fact that you can ease off the gas in May.  One program of my acquaintance runs a membership campaign that starts every January.  There is about five percent of their file that will give a membership gift like a clockwork every January or February and then nothing for the rest of the year.  Should you stop trying to get extra gifts?  No.  Should you cut your cadence way down and save yourself some costs?  Yes.

These are things the donor probably thinks they are telling you explicitly with their behavior.  It’s now incumbent upon you to listen.

Because tomorrow, things get a little bit harder, as we talk about lifecycle and loyalty.

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# 5 simple rules of thanking donors

For everyone.  E-very-one.  I once worked with a nonprofit that thanked everyone who gave \$250+ on letterhead, \$10-249 on copy paper, and under \$10 not at all.  My first step was to thank everyone.  I know that the love discussion from yesterday can come under pressure when finances are tight.  But as an exercise, go back and look at the first donors of your last ten large bequests.  My guess is that the majority were under \$20 and some under \$10.  Thanking everyone is not only right and polite; it is a great investment in your long term.

That doesn’t mean that you have to ask for a \$2 gift again, or in the same way.  You still have a responsibility to maximize your contribution toward your cause. But you do have to be grateful that they gave a gift.

That doesn’t all mean that you shouldn’t differentiate your thank you’s.

Differentiated by reason for giving. Part of making people feel special is to treat them specially.*

Your different types of donors are supporting different types of things for different reasons.  Your monthly sustaining donors are giving, presumably, because of appeals you have make about the need for steady, predictable income.  Your advocacy donors – those who donated in conjunction with an urgent appeal for change – are going to be the exact opposite.  They will be looking to support the urgent rather than the constant need.  Thus, the messaging should be dissimilar for these.

Differentiated by lifecycle.  If someone is a lapsed donor who is reactivating, remember the prodigal son.  Now is the time to kill the metaphorical fatted calf and welcome them back and letting them know you appreciate that they are coming back, especially if you had been using lapsed-type “why has thou forsaken us?” language to get them back.

Similarly, new donors should have a whole new set of acknowledgment and onboarding messages.  I won’t repeat my blog post on onboarding for new donors and supporters, except to commend that piece to you.

Differentiated by amount given/quality of supporter.  This in part pragmatic – you want to invest more in keeping your better donors.  But it is oft said that smaller gifts are given from the heart and major gifts are given from the brain.  This is partly misleading, in that you have to engage the heart of your major donors first, but the pitch that you make to a major donor is more about the long-term impact that they are going to make with their investment.  Similar language just isn’t appropriate for a \$10 donor, who is helping your mission, but not because of a transformative legacy they are looking to leave.  There too is a difference in messaging necessitated by a difference in reasoning.

And then there’s the obvious part – your largest donors should have higher touch acknowledgments.  That includes handwritten notes, personal phone calls, cards for special occasions like birthdays or holidays.  The key that many, many organizations forget is not to let high touch get in the way of a timely thank you.  If you normally send out thank you letters every day, but your high dollar donors get a letter from your ED that s/he sends out every 1-2 weeks, you are falling into this trap.  You are essentially differentiating backwards – your best donors are receiving the worst donor service.

The way to avoid this is to get the standard receipt and thank you immediately as you normally would do, then to follow up with your high-touch thank yous.  Few will mind if you say “I know you got our standard thank you last week, but I wanted to personally reach out to tell you how much your gift meant to me.”  Rather the opposite in most case.

This is imperative because one of the best predictors of whether someone will give again is how quickly and well they are thanked.  So, the final rule is:

Timely.  Get your receipts out as soon as you can, because of the impact on the next gift.  If it’s for a high-dollar donor, consider differentiating even on timeliness, with first-class postage on those thank yous.  Take a look at Blackbaud’s mystery shopper experience here.  Your donors are used to get receipts in week one (for the above average) or week two (for the just average).  You want to be above average to get those additional donations.

Thank you for reading.  Tomorrow, we’ll talk about different ways to thank your donors: some that are a bit nonstandard, all of which help express your gratitude.

* It’s statements like that that are the reason I make the big bucks.

# Beyond RFM – doing intermediate-level segmentation

By now, hopefully, you have seen the benefits of segmentation and the value of RFM as a preliminary tool.  But you have probably intuited a few of the flaws in it already:

• The distinction between recency groups is sometimes artificial. Let’s say two people give \$20 per year, one at the end of January and the other at the beginning of February.  The former would be at 13 months for a January mailing; the latter at 12 months.  A few days difference could mean that one gets mailed and the other didn’t.  (In fact, I’d love to test a segmentation out to 13 months instead of the standard 12 because of this; please comment or email me if you’ve done this, so I can share and illuminate myself).
• The distinction between frequency groups is artificial. Your multidonors range from people who donate once a year over a series of years to people who donate to literally every communication they get.  RFM analysis gives these two people the same number of communications.
• The distinction between monetary value is artificial. You probably saw this one coming, given the first two.  Which donor would you prefer – a donor who donates \$10 ten times per year or a donor who donates \$50 once a year?  RFM prefers the latter; I’m guessing you would prefer the former.
• It carries literally no other information. The \$25 dollar donation of today could be from someone who clipped coupons to raise the money to donate or Bill Gates divesting himself of what he found in one cushion of his couch.  What a person donates is an indicator of capacity, but it’s a blunt tool when a scalpel is possible.
• You probably noticed I was talking only about the mail in examples. RFM doesn’t look at channels of donation, nor at the sensitivity of people to those channels.

Let’s address this last one first, as we look for ways to customize RFM more than using it alone.

Separate RFMs by channel. When you do your telemarketing list pull, you will almost certainly want to call deeper into your file to people who have made a previous telemarketing gift than those who you are trying to make their first gift on the phone.  Same thing in the mail: you may be willing to mail multidonors out to 48 months \$50-99.999 for people who have given through the mail, but only to 12 months or 18 months \$50-99.999 for people who have only given online or on the phone.  Separate RFMs by channel will help you make these determinations.  Remember that you are looking to make sure that you have a strong multi- or omni-channel program, but that doesn’t mean you have to be agnostic as to channel of origin or preference.

Cadence analysis.  This goes to your \$10 10x versus \$50 1x donor example above.  You have to figure out who likes/needs multiple communications to make a gift or gifts and who doesn’t.  Some ways you can do this:

• Look at how many types of offers you have going to a person in rotation; hammering the same key on a piano over and over isn’t music, nor will the same approach be music to your donor’s ears.
• Take a look at how many times you mail someone in acquisition. Sometimes chronic non-responders need a different offer (as with rotating your offers above), but you can also see whether someone after seven or 17 or 27 times of getting a message from you means they almost certainly won’t donate and you can bless and release.  The same holds true for your lapsed donors as well.
• Test consistent communication versus no communication versus resting periods to see what happens when you try different cadences.
• Look at frequency of gifts within a certain period of time, rather than ever. You can see dramatic results sometimes by decreasing your mailings to your one-time-per-year donors versus your multi-per-year donors.

Mission area: I mentioned this when discussing customization types, but tailoring your communications toward the area of your donor’s interest is also a legitimate segmentation target.  Why would you send that advocacy alert to people who care only about your work in schools or your calendar with pictures of dogs to your car people?

Income: If you don’t want to ask that millionaire for \$17, a wealth append can get you the information you need to customize your ask strings and communications strategy.

Location: Zip codes are the poor person’s income append and can be free-ish, so that’s a potential win.  More often, though, you can use zip code modeling to breathe life into underperforming acquisition lists.  Simply find your top X percent of zip codes from your current file and ask for just those zip codes from the rental list.  It will be slightly more expensive to rent per name this way, but it can provide a 20%+ lift in response rates and/or average gifts.  This is also a way to test new lists while minimizing risk.  One caution: you don’t want to do this for all lists or you risk self-limiting your acquisition strategy.  If a list works well for you across zip codes, use the whole thing – that way you give yourself a chance to be wrong about a zip code long-term.

Demographics: Some nonprofits find that different messages work better for men versus women.  Age can also be helpful, as you work to avoid sending your one millennial donor your planned giving brochure (there’s optimistic and there’s delusional…).  With demographics, backtesting makes initial sense, where you see how people of different demographics responded to previous appeals and messages, then use that data to define your strategy.

Previous responsiveness: It sounds obvious, but it’s ignored by CRM: if someone like getting your calendar three years ago, they may like getting it again.  Replace “calendar” with member card, action alert, survey, etc., and you have the makings of a profitable add on to your usual list mix.

Those are some of the things you can add to spice up RFM.

I said at the beginning that this was intermediate segmentation.  Advanced segmentation is modeling.  The hacks above will help get you many of the benefits of modeling at a fraction of the cost, but it won’t get you all of the benefits, so definitely leave yourself open to building smarter and smarter donor modeling solutions.

Any other segmentation recommendations you’ve seen work?  Please leave them in the comments.

# RFM part 2 – segmentation goals beyond net revenue

From yesterday, we had a sample membership mailing with these results from last year, and we were going to cut any segment that didn’t get \$.33 per piece or more, since that is what the piece costs.

To do so would actually cost us dearly.  As we discussed this week, there are more goals than just the immediate gaining of revenue.  Looking at mail pieces alone with a “here’s a piece; here’s another piece” mentality can ignore what other things a mailing can do for you.  Let’s take a look at this chart of historic gross per piece by segment with two ideas in mind: groups we want to invest in and testing opportunities.

Take a look at our \$50-99.99 37-48 single donors.  They have an anemic response rate of .3% and an average gift of \$80, so they would only gross \$.24 per piece to mail to (and thus lose \$.09 for each piece sent out).  Should you mail these donors?

There are some organizations that would say no – they think that every segment should net positively in a donor mailing or that they should only do no net cost acquisition.  I’ll try to demonstrate why I think these people are wrong.

With a response rate of .3%, it would take 333 1/3 pieces to generate one donor.  At a net loss of \$.09 per piece, that’s a cost of \$30 to acquire that donor.  Chances are that that is higher than you are spending in your acquisition mailings to get new donors.

But you aren’t acquiring just person off the street.  You are getting someone who then slots into the 0-3 \$50-99.99 M segment for the next mailing.  You can see if the person got this mailing again for their next one, they would be predicted to gross \$3.62 per piece sent to them or people like them, which is very nice.

Let’s run the numbers assuming that their average gift is \$50, your retention rate per year for lapsed reactivated donors is 50%, your retention rate per year for multi-year donors is 70%, and it costs you approximately \$10 to mail your \$50-99.99 donors for one year.  To make the math easy, we’ll assume only one donation per year (it should higher) and we’ll assume that any donation is worth a net of \$40 knowing the mailing costs (in reality, you would want to look at both the possibility that someone will give multiple times per year and that you will have to mail someone even when they don’t give).

This works out to:

.5 * 40 + .5 * .7 * 40 + .5 * .7^2 * 40 + .5 * .7^3 * 40 … .5 * .7^n * 40

(Can you see why I simplified the math?)

What this basically says is that there’s a 50-50 chance of getting any future gift from this person and they have a 30% chance of lapsing every year thereafter.  We aren’t using a discount rate because interest rates now are so low.

To simplify, it’s \$20 + \$14 + \$9.80 + \$6.68 and so on.  A bit of high school calculus later and this donor will likely return an average of \$66.67 to your organization.  All for the cost of \$30.

If you had a magic box where you could put in \$30 and didn’t know what it would give you back, but knew the return would average over \$60, you’d put money in.  I myself would ask if I could put in more than \$30 to speed things up, like asking the genie for more wishes.

See the full comic and other fun stuff here

In general, your multi donors are going to be far better donors.  However, you need to communicate to single time donors in order to get those multi donors.  You also need to talk to those people whose last donation has been a while to renew them for future support.

The corollary to this is that you shouldn’t just look at this segmentation and see what to cut; you should also be adding back in.  Looking at these gross revenues per donor, you are probably (hopefully) wondering why you wouldn’t want to mail 7-12 month single donors of \$100+, or deeper into your \$1000+ donors, or more.  These are all correct thoughts.  Looking farther back into your pieces, you might see that someone has made the previous mistake – they looked at a small sample size of a \$1000+ mailing, found that no one responded, and cut the segment.

Thinking further about this, you can see that perhaps the \$1000+ donor shouldn’t get this piece, but they probably should be communicated with.  These are your best and best potential donors and there probably is a way to increase their value more so than not communicating with them.

Similarly, you’d love to renew those \$15-\$19.99 13-24 month donors, but this also isn’t the way to do it.  Now we are going to break out of yes/no segmentation and into using segmentation to create differentiated communications.  For simplicity sake again, we’ll assume that we have four treatments we are going to try:

• This mail piece, plus a pre and post email, for our “normal” donor segment (red)
• This mail piece with “lapsed” language, plus a pre and post email, for our lapsed segments (green)
• A high-touch invitation-style mailing to higher-value donors with first-class postage to invest in getting their gift (with email and higher-touch telemarketing as well) (blue)
• A prerecorded outbound voice mail campaign, coupled with an email ask to less valuable or less likely donors to attempt to renew them without high marginal costs. (yellow)

I’ve oversimplified here.  With the high-touch piece, we’d almost certainly want to test borderline segments part with the high-touch and part with the control to see if the additional investment is worthwhile.  You’d also want to test what segments telemarketing works best with.  And so on.  But for first steps, it’s directionally correct.

So let’s color in the mail plan with these four layers.

Note that you are able to contact more people with more appropriate language with this strategy.  Segments that a pure net perspective would have ignored are renewed in this new model and our most valuable donors are treated that way.

But that’s still just RFM with some embroidery on top.  It’s a fine model, but there’s more that can be done.  We will go beyond RFM tomorrow to add a few other pointers tomorrow.

# The building block of donor segmentation: RFM

Over 80 percent of nonprofit marketers know the term “communication segmenting” according to a Bloomerang survey.  Over 60 percent say they segment their files.  This means that almost 20 percent of them don’t know what segmentation is and 20 percent more know about segmenting, but don’t.

Let’s see if we can reduce those numbers.

Segmentation, as you can see from my last two posts, really is for everyone, regardless of the size of your file. We’ve talked about, obliquely, two different types of segmentation – yes/no segmentation (will someone be communicated with or not) and segmentation to help create versions or customizations.

RFM analysis can help with both of these.  It stands for:

• Recency: Usually used as how recent was someone’s last donation to the organization. You may occasionally also look at their last interaction with the organization, but we can put that aside for now.  This is perhaps the primary driver of segmentation and, if there is an answer to the “how many people do we have on file?” question, it’s when it phrased as “how many people have donated to us in the past two years” or the like – with a time horizon and action attached to it.  Do yourself a favor and add “recency” to your Microsoft Word dictionary; you are going to be using it a lot and Microsoft Word doesn’t know that word exists.
• Frequency: We go from the most often used to the most often ignored – how many times someone has given to the organization (or interacted with in non-donor contexts). This is often simplified to single v multi, as this dyad makes it easier to plan your communication.
• Monetary value. This is usually measured by another TLA (three-letter acronym): HPC or highest previous contribution – what’s been the highest amount the person has made in any one gift. This is an area of some debate, as if someone makes gifts of \$20, \$20, \$20, \$20, \$500, \$20, \$20, \$20, and \$20, it is fairly predictable that they are probably better grouped with the \$20-\$24.99 donors than the \$500-\$999.99 donors and their ask strings changes along with this (more on ask strings here).  One solution is to use a formula like 2/3 of their HPC + 1/3 of their most recent contribution or half of their HPC + half of the average of their last five contributions.  But this is something worth testing how it works best for your file.

Let’s do a yes/no segmentation with RFM.  We have a membership mail piece that has historically very well with a number of segments.  It costs \$.33 to mail and you are looking for segments that net.  Here are what your RFM response rate, average gift, and gross revenue per piece would look like from last year.

Response rate:

Gross per piece:

(these are intentionally realistic, but false, data)

To explain, the first numbers are the months (so 0-3 is someone who last gave a gift in the past three months), S & M stand for single and multi (get your mind out of the gutter), and the dollar amounts across the top are that person’s highest previous contribution.

Looking at this, to maximize net revenue, we can cut some of the segments to lower HPC groups and to one-time donors.  Anything under \$.33 per piece isn’t going to net us money.

This is a decent baseline that answers the question “I have this mail piece going out in February; to whom should it go to maximize the net revenue of the mailing?”.

However, we are going to look at it as “how do we maximize the value of this donor by treating them appropriately?” and layer in some treatment segmentation tomorrow.

# Wherefore segmentation?

Yes, wherefore.  As long as we are starting from first principles, we can go a little bit Elizabethan.  In the one and only famous “wherefore” quote, Juliet isn’t asking where Romeo is (below the balcony).  Hers are existential questions – for what reason does Romeo exist and what cruel twist of fate made him a Montague, her family’s mortal enemy?

For more of this, check out my likely-never-going-to-be-written book The Bard Does Nonprofit Direct Marketing (All’s Well that Ends with a Donation).

But wherefore segmentation – why does it exist?  We covered a lot of this in the last post, but we’re going to be going into them more granular than that as to who gets what communication when.  Why are we doing this?

The simple answer is “to maximize revenue.”  In this world, every mail piece would be opened and responded to, every phone call answered, every email and online ad clicked upon and donated to.

In this world, the ideal model would be one that gets this 100% response rate – it would read people’s minds and get them the lowest possible cost means of communication to get the maximum gift at the precise right moment.

This is not a horrid definition and, in fact, that would be a really cool (if magical) model to apply.

But it ignores two things: how people give and what your goals are.

Let’s say you have a person who, every year, like clockwork, gives to your membership mail appeal every January.  She’s on your email list, gets your e-newsletter, and a number of other mail pieces each year, but only gives to that one membership mail pieces every single year.

Do you think she would still give to you if that was the only communication she got from you throughout the year?

Probably not. I once walked each year for an organization that will remain nameless.  Every year, I started getting emails from them a couple months before the walk encouraging me to walk (whether I’d already signed up or not) and I would stop hearing from them after the final walk email for another 10 months.

Please notice I say I “once” walked for this organization, not that I still do that.

The bottom line is that even the most loyal of donors (especially the most loyal of donors!) want to hear from you.  Look at Professor Adrian Sergeant’s surveyed reasons why someone stopped giving to an organization:

The full study is here; it’s real and it’s spectacular.

Many of these involve someone not being communicated with enough (not acknowledging support, don’t recall supporting, no longer needs my support) or not being communicated with effectively (other causes more deserving, not informing how money was used).  Now look at the bugaboo of many an ED or board member: inappropriate communications is less than 4%.  More people defect because we don’t talk to them than defect because we talk to them too much.  So we can’t do just the pieces that “work” for a person without cutting the heart out of our communications.

As mentioned earlier, it also ignores other goals you have for your direct marketing program.  In a classic, Mal Warwick’s The Five Strategies for Fundraising Success articulates there are five goals you can set:  Growth, Involvement, Visibility, Efficiency, and Stability (GIVES).  He further says these are to a large extent mutually exclusive.

I’m not going to ruin the book for you, but this is just to say that there are things you want beyond maximizing short-term revenue.  You may want to get long-term revenue, volunteers, advocates, awareness of your causes, and more.

So how do we restate our goal?  How about:

The goal of the direct marketing program is to maximize the lifetime value of each of your constituents.

This isn’t just financial lifetime value if you have other non-financial goals, but it likely helpful to help quantify what you are willing to pay to get, for example, an advocate in order to put everything on the same scale.

This is important to have as a definition because it will help you transcend many obstacles.  When should your direct marketing donors get a major gift officer working with them?  When it will increase the donors’ lifetime value (and shame on you for saying “your donors” – donors belong to no individual within an organization). Should your national office or field offices do communications to donors?  Well, which mix will maximize lifetime value? These will likely need to be tested, but won’t it be nice to have an objective answer to some of these?

We’re going to initially talk about RFM analysis, which takes a look at which donors should get which communications.  This is absolutely necessary as a baseline.  However, if you are looking to maximize the lifetime value of each constituent, you will have to look at things differently.  It’s a minor difference, but you will need to think of “should this donor and donors like them receive this communication?” rather than “who should this communication go to?”.  It’s when you get to the point of thinking about donors first and make your communication vehicles reflect that rather than taking your communications and seeing to whom they should go.

# Why “mail everyone” is never the answer

I’ve had my first request – to talk about the basics of segmentation. Thanks and keep them coming!

The question will eventually come, if it hasn’t already: “how many people are on our list?”.  The answer?

For those who may not get the reference, it’s from The Hitchhiker’s Guide to the Galaxy.  When assigned to find the Ultimate Answer to Life, the Universe, and Everything, the computer Deep Thought ponders this for 7.5 million years and comes up with the answer 42.  It then says that:

“I checked it very thoroughly … and that quite definitely is the answer. I think the problem, to be quite honest with you, is that you’ve never actually known what the question is.”

The question of how many people are on our list or in our database is similarly ill-formulated.  You may have a list of X people, but are you really going to ask for a donation the person who called your executive director a [redacting] [redacter] at the gala 11 years ago and never corresponded with your organization thereafter? So your list is X-1.  How about dead people?  You need them in your database so you know not to solicit them.  And so on.

Every time you communicate with these folks, you are losing something.  Usually, for methods like mail and telemarketing, there is an additional marginal cost for each person reached.  With email, there isn’t, so email tends to be the least segmented direct marketing method.  This, however, ignores that there is a cost for not segmenting an email file; the less people open your emails (and especially in cases where you are emailing an account that no longer exists or is checked), the more likely systems are to think you are a dirty dirty spammer and cast you down into the ranks of personal attribute enhancers, Nigerian princes, and your great-aunt who thinks that you absolutely need to know about the ecstasy-lased gummy bears “epidemic.”

The bottom line is that even when you aren’t paying the bill, you have every incentive to make sure your list is as trim as possible.  That means not communicating with the deceased, opt-outs, those with incorrect communication data (although you should be doing NCOA (national change of address), eCOA (electronic change of address), and corrective phone appends on those people you would still like to talk to), and those who have opted out of the medium (e.g., email opt-outs) or message (e.g., solicitation opt-outs).

You may think that once you clear those people out of your list, you should have a defined number.  However, different people are at different stages of interaction with your organization.  Here are a few:

• Some guy (aka suspect)
• Prospect
• One-time giver
• Multi giver
• Sustainer
• Mid-major donors
• Major donor
• Planned giving donor

These are frequently presented in a pyramid because there are only so many easy-to-use graphics in PowerPoint.  Some may say it’s because suspects and prospects are the base of the program and they grow from there in smaller and smaller numbers, but you and I know the truth.

The truth is that these are like the stages of grief, in that they don’t always apply, don’t often go in order, and abstract over significant parts of the donor journey. For example, take a look at the types of retention you should be measuring and you’ll see that there are categories – first-year, but not first-time, givers and reactivated lapsed – that this pyramid doesn’t take into account.  Similarly, you will see people who are major donors on their first gift, people who you didn’t know about who leave support to you in their will, and the former sustainer who no longer wants to support your organization.

I take inspiration from Stephen Jay Gould, who critiques in many discussions of evolution the ideal of progress or, worse, inevitability:

Progress is not merely a deep cultural bias of Western thought…it is also…the explicit expectation of all deterministic theories of evolutionary mechanism that have ever achieved any popularity, from Darwinian selection to Lamarckism to orthogenesis. I do not, of course, mean progress as an unreversed, unilinear march up the chain of being; Darwin did away with this silly notion forever. But even Darwinism anticipates that an imperfect, irregular, but general ascent should emerge from all the backing and forthing inherent in a theory based on a principle of local adaption to changing circumstances.

Stephen Jay Gould, “The Paradox of the First Tier.”

In reality, the donor journey isn’t a net gradual march from suspect to prospect to one-time donor, to multi-donor, and so on.  But the general theme of this – that you should treat different types of donor different based on what you want them to do for the organization, what they want to do for the organization, and their means and interest – is a good one.  A suspect and a potential major donor are very unlikely to want the same communication in the same way.

So there are some folks you may want to get some communications, but never others.  Other such groups:

• Board members
• Organizations
• Recent donors
• The people you serve
• Public officials and opinion leaders
• People who have requested a certain number of communications each year

That’s the broadest type of segmentation – what type of people do we want to include?  But we’ll want to increase revenues and save costs by sending the most effective communication possible. So in this week of segmentation, we’ll talk about the philosophy of segmentation, then start with a basic segmentation – RFM analysis – and build from there.