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Machine Learning Times
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Wise Practitioner – Predictive Analytics Interview Series: Brian Reich, Former Director at The Hive


In anticipation of his upcoming conference presentation, The Data Set You Can No Longer Ignore: Consumer Engagement with Social Issues, at Brian Reich IMAGEPredictive Analytics World New York, October 23-27, 2016, we asked Brian Reich, former Director at The Hive, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what behavior or outcome do your models predict?

A: We started by analyzing current donors. From our current donors, we created lookalike models that gave us an appreciation for who was already responding and taking action to support refugees – and, of course, the much larger universe of people who were not yet engaged. We also conducted a national survey to measure people’s knowledge and support of refugee aid, along with a host of related issues, and we used that information to build models that explored the population beyond the lookalikes – what they know about refugees, what they might need to understand better in order to be motivated to take action, and similar.

We started all this work when awareness and interest in the global refugee crisis was pretty limited – and certainly confined to only people who were already deeply knowledgeable on the subject. Then, at the end of last summer, that all changed. The number of refugees flooding out of Syria into Europe exploded. Heart-breaking pictures of a young refugee who drowned trying to make it to safety suddenly made headline news and took over social media channels. All of a sudden, the global refugee crisis was the top story all over the world. President Obama challenged Americans to step up and help. The Pope said it was our moral responsibility as a society to aid refugees. The attention and the interest in the refugee crisis was higher than ever before. And we were able to organize our response, both short-term and long-term using the data as a guide.

Q: How does predictive analytics deliver value at your organization – what is one specific way in which it actively drives decisions or operations?

A: Everything is informed by the data, both directly and indirectly. We have an unprecedented level of sophistication that we can apply – who we target, how we position issues related to the refugee crisis, and the ways we work with partners. Beyond our specific efforts:

  • We have demonstrated that we aren’t a traditional non-profit organization, but rather a sophisticated, engagement-oriented organization that approaches engagement with a combination of political, consumer, media, and tech expertise that hasn’t been attempted before.
  • We have clear insights to our audience and can prioritize accordingly – not just look at who might engage based on their past behaviors, but look to engage people who are likely to engage if given the right opportunity.
  • We build our messages based on the rapid-message testing, so we don’t have to rely on what our gut tells us.
  • We know the best ways to reach individuals, whether digital ads or snail mail, through partners, or another method, so we don’t waste time or resources on audiences that aren’t likely to take action.

And with all of this, we’ve been able to improve our organizational capacity and shift the way we think about our challenges. We’re looking at individuals – human beings – not donors, or advocates. We can do a much better job tapping into what we know people are already doing, or comfortable doing, instead of trying to compel people to do what we think benefits our organization best. Our cause is important, but we need to think more about the people we are talking to – understanding who they are and what motivates them to ultimately engage them and support our cause.

Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: Prior to doing the modeling, we had been making assumptions based on our gut – and they were pretty good. While the data validated our assumptions, it also revealed a whole new set of opportunities. It uncovered some surprising untapped geographic markets, hotspots in the parts of the country that we had never thought of, groups of people who don’t fit the stereotype of those who would have been our targets. Over the past several months we have used the data to reach and engage hundreds of thousands of new people who would not have been targetable without the data.

Q: What surprising discovery or insight have you unearthed in your data?

A: Beyond target audiences, the data has expanded the ways we think about how to engage people. Instead of relying on the existing messages – the ways you commonly hear about the refugee crisis from a nonprofit or through media coverage – we now had messages that have been tested and verified by data science. Instead of speaking about the refugee crisis as an emergency situation, or telling stories of the horror refugees face or hope they retain against all odds, we can present issues in ways that Americans understand, connect with on a more personal level, or make sense of through an experience they can appreciate. All of these insights continue to show how data enables us to target more efficiently and effectively.

Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.

A: We knew that the traditional methods and messages wouldn’t be enough to get new potential supporters engaged. It was clear that Americans cared about helping refugees, but we needed to know more so we could determine how to get people more involved, to take more meaningful actions. We used our data models, plus survey research and rapid-response message testing, to experiment with different efforts we thought could be most effective, and learn the most in the shortest period of time.  And it paid off in a big way.


Don’t miss Brian’s conference presentation, The Data Set You Can No Longer Ignore: Consumer Engagement with Social Issues, at Predictive Analytics World New York on Wednesday, October 26, 2016 from 3:30 to 3:50 pm.  Click here to register for attendanceUSE CODE PATIMES16 for 15% off current prices (excludes workshops).

By: Eric Siegel, Founder, Predictive Analytics World

Eric Siegel is the founder of Predictive Analytics World ( — the leading cross-vendor conference series consisting of 10 annual events in New York, Chicago, San Francisco, Washington DC, London, and Berlin — and the author of the award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated Edition, (Wiley, 2016).

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