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Review: SimioAudience Featured

Review: SimioAudience Scott Graham

Fundraising is a critical component of any successful nonprofit organization. While it may be essential, it is also time consuming. Reaching out to donors takes time. Often, the end result falls flat. SimioCloud (owned by Moore, a provider of performance-driven marketing solutions), recently announced their newest solution, SimioAudience in hopes to cut down the time an organization needs to fundraise by providing a list of prospect donors that have given to similar nonprofits in the past.

In Use

Touted as a next-generation cooperative database designed specifically for nonprofit fundraising – SimioAudience aims to deliver real-time insights on donor information. According to Doug Kaczmarek, the Chief Data Officer of Moore, SimioAudience is a co-operative database that is able to identify new perspective donors using machine learning capabilities to develop predictive models. Unlike their competitors who only have access to transactional information – SimioAudience can provide their clients with distinct donor history to get more accurate results. This means a nonprofit more time marketing to those that statistically have a better chance of donating to their cause.

To get the most out of the solution, SimioAudience is geared towards mid-large level nonprofit organizations and they recommend each nonprofit have at least 5 thousand donors with a robust growth plan. Interested parties rent the list from SimioAudience as a “one time” which Kaczmarek states is industry practice. The platform charges nonprofits $65 per 1,000 names.

Ease of Use:

SimioAudience is easy to use because clients receive a report of targeted donors that are highly likely to engage with the charity.  There’s no dashboard or back-end platforms that the clients have to manage. SimioAudience will analyze the data on the backend and send their clients a curated list full of donors that are more than likely to donate.

Technology Needed:

What sets SimioAudience apart from their competition is that they are based in the cloud. Therefore, they have the advantage of having up-to-date donor information where other co-operative databases may only update their database once or twice a month.

SimioAudience also makes it a point to connect billions of data points through their machine learning and AI capabilities. This ensures their predictive models are equipped with making precise recommendations.

Recap:  

In a press release in late September, chief executive officer of Moore, Gretchen Littlefield explained, “SimioAudience identifies new and emerging donors using cloud-based processing, transactional data and machine learning technologies unlike any other data source. It’s truly the next generation co-op.” The platform works by collecting donor data so SimioAudience is able to provide a concise report of potential donors to clients. By using predictive models, SimioAudience is able to predict which donors are most likely to respond and donate and which donors are not. This way nonprofits can spend their time and money marketing to the correct people. 

Advantages:

  • SimioAudience is based in the cloud so their database is always updated with the latest donor pool
  • They use predictive analytics, and many data points to predict which donors will likely respond and ultimately donate
  • There is no dashboard or heavy lifting on the client’s part. They will receive a curated report that they use for their marketing initiatives.

Disadvantages:

  • This is geared towards mid-large nonprofits. Nonprofits must have at least 5 thousand donors to participate
  • There’s no guarantee that the donors in the report SimioAudience provides will actually donate
  • You are expected to give your donor information to SimioAudience to contribute to the database

My Opinion

I think SimioAudience can provide great benefits to large nonprofit organization looking for a list of potential donors. Because they’re based in the cloud their information is constantly being updated. It’s also nice that there is no heavy listing on the nonprofit’s side.

As a data nerd I think it’s really interesting that they’re using predictive analytics and AI to predict potential donors. I think this is something that we’ve been seeing from tech companies and will continue to see more and more.  At the same time, I would still struggle with providing my donor data despite Kaczmarek assurance that all data is anonymized. 

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Danielle Loughnane

Danielle Loughnane earned her B.F.A. in Creative Writing from Emerson College and has currently been working in the data science field since 2015. She is the author of a comic book entitled, “The Superhighs” and wrote a blog from 2011-2015 about working in the restaurant industry called, "Sir I Think You've Had Too Much.” In her spare time she likes reading graphic novels and snuggling with her dogs.

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