Attribution challenges for online and offline marketers

This week, we’ve been looking at the differences between online and offline direct marketing and how the specialists from these two different worlds can talk to each other.

This difference may be no more stark than it is for attribution.

With online attribution, you can follow a Web visitors journey through your site.  You can (and should) follow them through the site and say that someone we attract to the home page is worth X; if we get them to take an advocacy alert, they are worth Y; if they download a white paper, they are worth Z.  These steps toward donation each have their place in the donor journey firmament online.

With offline, attribution is usually applied with a sledgehammer — they donated to X mail piece, so X gets the credit.

Having run a quasi-membership program, I’ve seen the absurd joy of watching donations spike to last year’s membership pieces the moment this year’s come out.  (OK, “spike” is a bit dramatic; “hill” perhaps?  They go up by a little for a time, then back down.)  People almost certainly set them aside and then, reminded by the latest piece, send in whatever reply device they have at hand.

This is one minor example of how offline attribution is often done, but simplified to the point of absurdity.  One is put in mind of the old physicists’ joke about milk production:

Ever lower milk prices were driving a dairy farmer to desperate measures, so he consulted with  a theoretical physicist. The physicist listened to his problem, asked a few questions, and then said he’d take the assignment, and that it would take only a few hours to solve the problem. A few weeks later, the physicist phoned the farmer, “I’ve got the answer. The solution turned out to be a bit more complicated than I thought and I’m presenting it at this afternoon’s seminar.”  As the talk begins the physicist approaches the blackboard and draws a big circle. “First, we assume a spherical cow of uniform density…” (here’s the origin joke, which I simplified

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So I guess was the only one who thought of that joke with oversimplification?  Sorry ‘bout that…

Anyway, this way of looking at attribution has several program-damaging faults:

  • It can cause people to cut cultivation communications.  These communications that help retain donors, learn about them, and bring them ever closer to the mission but don’t directly convert can have a big impact on eventual conversion.  In essence, you may end up cutting the wrong thing.
  • It can cause overcommunication.  If you add a communication and it nets positive, you may think it is the power of that communication, when it’s really about the the last communication but there wasn’t enough space between communications to differentiate.
  • It puts you in a mindset where you are thinking about the individual communications, not the individual donors.  This puts you in real trouble.  It’s natural to look at a mail piece or an email and think about how it “generated” the gift (when some research indicates that the last piece is about 16% responsible for a gift, leaving the vast majority to other causes).  In reality, the donor generated the gift.  How do you want to treat that donor going forward.

While sacrilegious to some, offline direct marketers would do well to take a bit of the humility from online attribution models (if not the models themselves) — there is only so much the proximate communication is responsible for.

Attribution challenges for online and offline marketers

Easter eggs in your donor database (guest post)

I have the privilege of sharing a guest post from Angela Struebing, president of CDR Fundraising Group.  For more insights from Angela and the CDR team, you can try their blog here.  Thanks, Angela!

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Every year I organize our neighborhood Easter Egg hunt. I stuff and hide over 600 eggs and love watching kids run through the field searching for them. The excitement they feel when finding an egg is the same rush I get when I discover something actionable in a client data file. It got me thinking about some data eggs that are often hidden. For some you have to look a little harder, but the answers are always in the data.

  • When evaluating list performance look past initial response metrics and assess long-term value (LTV) at an individual list level. We often find that lists that look bad upfront may show life when looking at 12-month or 18-month payback periods or retention rates. The same goes for looking at LTV by package. A test that might have had a lower response initially may bring on more loyal donors over the long haul. Make sure you look well beyond just campaign reports for this information.
  • Along the same lines, matchbacks where you look at returns that may be coming in through one channel but driven by another, is another hidden gem in your file. This is especially true for brick and mortar institutions where a recipient gets a mail piece and can respond through the mail, via phone, online, or in the lobby. In order to gauge true list value, you’ll want to look at all response channels and see from where the response was driven. This will also encourage you to make it as easy as possible for donors to give through any channel.
  • This leads us to multi-channel migration and attribution analysis. You’ll want to understand if donors are migrating from online to offline or offline to online. While counterintuitive, we see more people giving an initial gift and then moving to offline giving than vice versa. Knowing this may change your marketing focus. Attribution is critical to making investment decisions and understanding how the various channels are working together.
  • I find lapsed donors particularly interesting and profitable. They have already exhibited an interest in your mission. They can usually be reactivated for less than it costs to find a new donor and are more valuable to an organization (based on number of gifts and average gift). Take the time to test what really works with lapsed segments. Do they perform better in acquisition or to housefile packages or perhaps a tailored lapsed package? All lapsed cohorts aren’t the same with deep and recent lapsed names performing very differently. Should you use a reduced ask, Most Recent Contribution vs. Highest Previous Contribution or generic acquisition string? Do you reference their previous relationship or – if they’ve been absent long enough – treat them as a prospect? How far back can you mail? All of the answers to these questions can be found within your database (and carefully crafted tests).

These are just a few of the things I go looking after when reviewing results and file trends. What hidden gems have you found? Happy Hunting!


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Angela Struebing is president of CDR Fundraising Group, a multichannel agency focused on helping nonprofits maximize their online, direct mail, telemarketing and DRTV fundraising results. As president, Angela is responsible for overall agency management and strategic planning for national nonprofit clients to include Shriners’ Hospitals for Children, MoMA and the Marine Toys for Tots Foundation.

 

Easter eggs in your donor database (guest post)