The Birthplace of Apra

Dispatches from DRIVE/ (and overDRIVE/)

19 Jun 2017 9:19 AM | Joseph Gonzales (Administrator)

Michael Pawlus has presented extensively on fundraising analytics including DRIVE/, overDRIVE/, Data Analytics Symposium and APRA-Canada. He contributed content on predictive modelling for the book Prospect Research in Canada: An Essential Guide for Researchers and Fundraisers. In addition, Michael was interviewed for an article in the Chronicle of Philanthropy on text analytics. Connect with Michael: @michaelpawlus

Dispatches from DRIVE/ (and overDRIVE/) (by: Michael Pawlus)

This year I presented at the DRIVE/ conference and I was also co-faculty for the overDRIVE/ conference. It was a great experience to catch up with some colleagues and meet some people in real life whom I had previously only interacted with on forums like prospect-dmm. There were a lot of really thoughtful presentations and I left with some really practical ideas. However, I want to focus this blog post on two major takeaways that shifted the way that I think about fundraising analytics.

The imminent arrival of algorithmic prescription as a disruptive force

DRIVE/ this year was a very forward-looking conference with many presenters positing a vision of our profession in 5-10 years. Technologies such as artificial intelligence and prescriptive models were mentioned as game-changing disruptive innovations and there are now case studies in other industries proving the impact of leveraging these methods which are now materializing from the nebulous buzzwordy ether where they once resided.

A great example of a possible future was illustrated during a conversation between Chris Sorenson, DRIVE/ conference founder, and Ashutosh Nandeshwar, Assistant Vice President, Relationship Management and Data Sciences at the University of Southern California. Their session took the form of an interview with Chris as the host and Ashutosh as the guest. When asked how artificial intelligence may impact fundraising analytics, Ashutosh provide the following vision:

Imagine an app that a gift officer can use that serves up the best three prospects. It then recommends all the latest content and upcoming events that match best with this prospect’s interests and if appropriate aligns this prospect with a suitable gift fund and target ask amount. The app would provide all the contact details and the gift officer would be able to reach out directly from the app.

If this seems at all too far fetched or something that is still a long way off there was a recent article in Harvard Business Review1 documenting how Harley-Davidson used a similar strategy to massively increase revenue:

“Armed with creative content (headlines and visuals) provided by Harley-Davidson, and key performance targets, Albert [the name that Harley-Davidson gave to its AI program] began by analyzing existing customer data from [the] customer relationship management (CRM) system to isolate defining characteristics and behaviors of high-value past customers: those who either had completed a purchase, added an item to an online cart, viewed website content, or were among the top 25% in terms of time spent on the website.

Using this information, Albert identified lookalikes who resembled these past customers and created micro segments – small sample groups with whom Albert could run test campaigns before extending its efforts more widely. It used the data gathered through these tests to predict which possible headlines and visual combinations – and thousands of other campaign variables – would most likely convert different audience segments through various digital channels (social media, search, display, and email or SMS). Once it determined what was working and what wasn’t, Albert scaled the campaigns, autonomously allocating resources from channel to channel, making content recommendations, and so on.”

To translate this back to the world of fundraising we are constantly creating content to share various success stories throughout our organizations. We also plan and host numerous events. Using existing tools, we can measure the impact of all of these efforts. We should be able to define our best prospects through affinity scores, wealth ratings and, for some, modelling. To take this all a step further, my own presentation at DRIVE/ along with at least one other addressed how sentiment and common terms can be extracted from free form unstructured data such as survey responses, gift officer reports, and online giving comments.

So, we have the data and from a technological perspective all that is missing is for an algorithm to create calculations based on these data to inform strategy which we know exists from the example above and where we can assume that the price point for such a resource will fall within the capacity of some of our budgets in the near future. This is all to say that the data silos that we create and enforce through disparate policies created in multiple departments will quite possibly be the biggest barrier to this type of future being realized.

Why Not to Invest in Fundraising Analytics

I had an equally profound revelation during the overDRIVE/ conference during a section styled as an Oxford debate pitting two teams against one another to answer the question. Should we invest in fundraising analytics?

We were all at an analytics conference and we are all either regularly incorporating analytics into our work or we had a clear interest in doing just that so from my perspective the setup was risky and I imagined the team arguing in the negative to have nothing to say. This displayed a clear lack of critical thought on my part and a lack of faith in my far wiser contemporary, event chair Stephen Lambert, Advancement Researcher at Susquehanna University.

The debate was far better contested than I could have ever anticipated. If it were being scored on a fair scale I think there is a good chance that the team in opposition would have won the day. This is not to say that I am now convinced that analytics has no place in fundraising. However, it allowed me to better understand the view of those who are skeptical of analytics.

A few of the reasons given to not invest in analytics included the following:

  • There are not enough resources to allocate so why wouldn’t an organization just invest in more major gift officers.
  • Gift officers have passed the test of time. Fundraising analytics have not.
  • The data is really bad right now so what is the point of even trying to perform analytics.
  • Fundraising is an art and at its core it is about relationships.
  • Those in analytics do not understand how fundraising is done.
  • There are already cautionary tales in the UK regarding privacy concerns which means that analytics may be a future liability.

For those of us who firmly believe in the value of analytics this should help us as we advocate for our role within the fundraising ecosystem. There is a clear danger in insulating oneself so deeply in a supportive community which mirrors the hazards of echo chambers in society writ large. Until this debate, the world that I experienced through my network reaffirmed that investing in analytics is one of the most powerful ways that all organizations can improve. As I, device in hand, swiped through the endless scroll of data and evidence supporting my point of view, how could I imagine that anyone could possibly ever think otherwise?

Conclusion

These two experiences led me to arrive at the following actionable insight: For those of us in fundraising analytics, we need to advocate for our present place and prepare for disruptive technology to radically change the future. Here is the hope that I bring to this observation: almost all of us had to learn something new as we entered and advanced through prospect development. That is to say that none of us studied this in school and we are not dissimilar to other fields in the truth that even if we could have studied this in school we would still likely have had new concepts and resources to learn throughout our time actually working in the profession.

DRIVE/ painted a picture of a future that seems like a significant departure from our current experience; one where we are spending less time formatting outputs and more time collecting inputs and tuning the programs that create the outputs. If you are like me, do you find the most enjoyable part of our work is solving puzzles and thinking creatively to craft a narrative that helps drive strategy? Right now, we may find that we are able to perform these two tasks when creating profiles and maybe we still will for quite a while however if this proposed future comes to pass we will still maintain the aspects of this work that we love most.

My parting thought is that if you are already with me and excited for the future or if I was able to bring you along a little, if even slightly reluctantly, just remember that there will always be those who don’t see the value in analytics so remember to continue to speak with our partners who have not yet bought in and if you are one of them then let’s talk soon.

https://hbr.org/2017/05/how-harley-davidson-used-predictive-analytics-to-increase-new-york-sales-leads-by-2930 

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