Stephen Ferrando, SVP Strategy and Analytics  ●  1/3/2018

Fundraising 103: Lifecycle’s Impact on Budgeting

Our recent post on how lifecycles can be used by fundraisers created lot of good conversation in the blogosphere. One such discussion, on The Agitator, centered largely around RFM-based targeting versus more advanced statistical modeling approaches, and touched upon the viability of using qualitative data elements (surveys, focus groups, etc.) instead of behavioral data (donations) to build out targeting solutions.

For most organizations, however, modeling is part of an evolution, not an immediate destination. And that evolution is heavily predicated on need-state, sophistication, data assets, resources, and ultimately a cost/benefit assessment.

To be clear: Using lifecycles is not a cutting-edge idea. This three-part blog series is comprised of tried-and-true lessons, with the hopeful aim of propelling fundraisers forward on your unique evolutionary paths. Everything is prologue, after all.

A Quick Review of RFM

To recap what we covered in the last series post on donor lifecycles, we took campaign results and examined the results based on RFM (Recency, Frequency, Monetary) audience segments. To add context, the results could have been from any appeal — reactivation, renewal, etc. Essentially think “housefile” across any channel.

In that example, we selected the 06 Month (Recency), $25$49 Cumulative (Monetary), Single & Multi (Frequency) audience to create an easy-to-follow view of 47,988 donors (below):

  UNIVERSE GIFTS REVENUE RR% AG$ GIPN
Total 47,988 1,412 $33,867 2.94% $23.99 $0.71

RR% = Response Rate Percent
AG$ = Average Gift Amount
GIPN = Gross Income Per Name

We then demonstrated how we were only seeing part of the story when we added further segmentation detail to that population by adding lifecycle into the mix. What we found with lifecycle included were distinct performance differences even within that narrowly defined audience (0–6 Month, $25–$49 Cumulative, Single and Multi):

LIFECYCLE UNIVERSE GIFTS REVENUE RR% AG$ GIPN
New Donors 619 21 $560 3.39% $26.67 $0.90
2nd Year New 14,666 263 $7,974 1.79% $30.32 $0.54
2nd Year Regained 11,363 216 $4,900 1.90% $22.69 $0.43
Multi-Year 21,310 912 $20,433 4.28% $22.40 $0.96
Recently Lapsed (1324) 3 0 $0 0.00% $0.00 $0.00
Deeply Lapsed (25+) 27 0 $0 0.00% $0.00 $0.00
Total 47,988 1,412 $33,867 2.94% $23.99 $0.71

 

RFM + Lifecycle = More Accurate Budgeting

Generally speaking, organizations and consulting agencies create planning or budget estimates derived from a review of prior year campaign results and “All Available” RFM counts that reflect where donors stand at some point in time predating the start of the fiscal year they are budgeting for.  

This is not only less than ideal, but also slightly flawed in methodology.  

This situation can be improved by using RFM + Lifecycle.

Consider the dramatic fluctuations in performance we observed when we added lifecycle to the analysis of the audience (above). What do we think the limitations might be on a budgeting approach that only looks at RFM audience?

Well, let’s play the scenario out to see if we can answer that. 

Here are the results we looked at above for the 06 month, $24$49, Multi/Single audience, trimmed down for simplicity.


  UNIVERSE GIFTS REVENUE RR% AG$ GIPN
Total 47,988 1,412 $33,867 2.94% $23.99 $0.71

Pretend you ran your “All Available” RFM report as you started making the budget for next year, and you noticed that this same audience now had 57,988 donors in it, instead of the 47,988 contacted this year.  

Nice! An increase of 10,000 donors in this audience for next year. One might be inclined to take the Response Rate and Average Gift from the segment above from last year and budget something like this for next year:


BUDGET ESTIMATE
UNIVERSE GIFTS REVENUE RR% AG$ GIPN
Total 57,988 1,705 $40,899 2.94% $23.99 $0.71

Feels logical right?

dune book cover.png

“Deep in the human unconscious is a pervasive need for a logical universe that makes sense. But the real universe is always one step beyond logic.” — Frank Herbert, Dune

Here is where most budgeting efforts performed this way fall apart. 

If the lifecycle populations shifted under this audience year-to-year, the results for this 06, $25$49, Single/Multi audience are going to differ from last year’s campaign result — possibly dramatically.

In the view that includes lifecycle (below), what we can see are the composite elements under the expanded 57,988 donors 06, $25$49, Single/Multi audience. 

What you will notice is that the only thing that differs from our original lifecycle view is the universe by lifecycle.

This reflects the migration of donors and shifting subpopulations.

What this means is that when we apply the exact same observed metrics from the prior year to these migrating lifecycle universes, the result for this 06, $25$49, Single/Multi audience is going to be very different than what it was before.

 

 

In the charts below you will see that there's a 10% deviation between the actual number of gifts and a 9% drop in total revenue versus the budget estimate!

 

In this example, the budget for this audience is off by -10% on donations (or response rate) and -9% on revenue (or average gift), simply because of this lifecycle migration. Worst of all, had we taken the time to pursue a budget approach that utilized RFM + Lifecycle, this variance was preventable.

LIFECYCLE UNIVERSE GIFTS REVENUE RR% AG$ GIPN
New Donors 5,619 190 $5,080 3.39% $26.67 $0.90
2nd Year New 13,666 245 $7,417 1.79% $30.32 $0.54
2nd Year Regained 23,363 444 $10,072 1.90% $22.69 $0.43
Multi-Year 15,310 655 $14,678 4.28% $22.40 $0.96
Recently Lapsed (1324) 3 0 $0 0.00% $0.00 $0.00
Deeply Lapsed (25+) 27 0 $0 0.00% $0.00 $0.00
Total 57,988 1,534 $37,247 2.65% $24.28 $0.64

 

BUDGET ESTIMATE
UNIVERSE GIFTS REVENUE RR% AG$ GIPN
Total 57,988 1,705 $40,899 2.94% $23.99 $0.71


This is what happens when budgeting methods are based on a single isolated segment from a single campaign. What does this lifecycle migration mean if we analyzed it for all the segments in that campaign? And if that doesn’t make your palms start to sweat a bit when you think about it, what might this same type of lifecycle migration analysis mean for all your campaigns across every channel throughout all of next year?

Suffice to say, the devil is in the details, and you should be challenging your team to evolve the way they approach budgeting to include methodologies like these to avoid -10% errors at best or annual plans that are dead-on-arrival at worst.

 

 


This is the final installment in a three-part series about donor segmentation and targeting.

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