tag:blogger.com,1999:blog-56506958885726908472024-02-18T23:28:32.957-06:00DonorCast NewsWatchThe DonorCast NewsWatch covers the topic of analytics in nonprofit fundraising. The blog is a resource about data mining, metrics for development, advancement strategies, and new technologies.Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.comBlogger151125tag:blogger.com,1999:blog-5650695888572690847.post-41624740396375921232013-02-20T13:34:00.001-06:002013-02-20T13:34:28.836-06:00Annual Giving Analytics (Part 2)The previous
post in this Annual Giving Analytics series focused on how analytics can be used
to further the goals of Annual Giving, but how exactly is it done? This post will document and describe a few methods and approaches that can get you going on
furthering your use of the analytics for annual giving at your institution.<br />
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<o:p></o:p></div>
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<br /></div>
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Annual giving
is primarily interested in three variables that can influence the dependent variable
of how much a particular constituent is likely to give: Segment, Method, and
Timing. Segment is the demographic segment that a donor is categorized as being
a part of, method is the channel or means by which an individual donor makes gifts, and
timing is exactly when they are asked, either during the calendar year or
relative to specific institutional events. <span style="text-transform: uppercase;"><o:p></o:p></span></div>
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Building a
predictive model to assess the optimum conditions for annual giving can help
your program to understand a number of things, like which donors are the most likely
to give and therefore who should be prioritized by the program, where ask amounts should be
set for the maximum contribution, and how each solicitation channel like
email, mail, and phone should be utilized. Good places to start when building a
predictive model are who is likely to renew, at what levels should people be
solicited, and who is likely to upgrade to leadership annual giving.<o:p></o:p></div>
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Let's go through the creation of these three models step-by-step:<o:p></o:p></div>
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<b><u><span style="color: #990000;">Giving/Renewal Likelihood Model </span><o:p></o:p></u></b></div>
<div class="MsoListParagraphCxSpFirst" style="margin-bottom: .0001pt; margin-bottom: 0in; mso-add-space: auto; mso-list: l0 level1 lfo1; text-indent: -.25in;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Flag donors in your database that have a renewal history.<o:p></o:p></div>
<div class="MsoListParagraphCxSpMiddle" style="margin-bottom: .0001pt; margin-bottom: 0in; mso-add-space: auto; mso-list: l0 level1 lfo1; text-indent: -.25in;">
<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Gather data points such as demographics, activities,
interests, and geography related to these donors.<o:p></o:p></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Use logistic regression or decision trees to
rank donors based on probabilities to renew. <o:p></o:p></div>
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<br /></div>
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<b><u><span style="color: #990000;">Ask Amount Model </span><o:p></o:p></u></b></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Use a linear regression model to predict the
largest or most recent gift given.<o:p></o:p></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->If the resulting “predicted” dollar amount is higher
than the most recent gift amount then increase the ask.<o:p></o:p></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->If the “predicted” amount is lower then leave
the ask amount the same. <o:p></o:p></div>
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<br /></div>
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<b><u><span style="color: #990000;">Leadership Giving Likelihood Model</span><o:p></o:p></u></b></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Derive a binary dependent variable for existing
donors at the leadership level. <o:p></o:p></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Use a binary prediction method like logistic
regression or decision trees to compare independent factors.<o:p></o:p></div>
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<!--[if !supportLists]-->-<span style="font-size: 7pt;">
</span><!--[endif]-->Output will be predicted probability that can be
ranked.<o:p></o:p></div>
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Models like
these can be constructed for any number of donor behaviors that might be important to your institution like sustainer/recurring, catastrophe response, preferred giving channel, or cause or
interest specific appeals. But of course, all of these models are best used
together in order to maximize efficiency and effectiveness. Results for the programs for which the models are used to boost efficiency should be considered
holistically as one strategy and results should be captured not only by appeal but
also by demographic segment. Tracking, testing, and reporting mechanisms must be
in place prior to launch in order to accurately measure performance improvements. <o:p></o:p></div>
Unknownnoreply@blogger.com153tag:blogger.com,1999:blog-5650695888572690847.post-55471792838790755542013-01-29T10:26:00.000-06:002013-01-29T10:26:09.164-06:00Annual Giving Analytics (Part 1) This is the
first entry in a two-part series dedicated to Annual Giving analytics. These posts are derived from a webinar that was given by Bentz Whaley Flessner
partner Joshua Birkholz and BWF’s Annual Giving expert Heather Greig. They
are available to be viewed on the <a href="http://www.youtube.com/user/bentzwhaleyflessner">BWF youtube channel</a>.<br />
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<o:p></o:p></div>
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<br /></div>
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This post
will explore the relationship that business and data analytics can have with
Annual Giving operations and the next post will be more in-depth with regards to the
techniques and methodologies that can be used. <o:p></o:p></div>
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Analytics
generally fits into the business process of a philanthropic fundraising organization
in the following sequence:</div>
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<b><span style="color: #cc0000;">- Initial segmentation & prospecting if an organization's constituency. </span></b></div>
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<b><span style="color: #cc0000;">- Portfolio optimization for major gift solicitation and performance management of operations. </span></b></div>
<div class="MsoNormal" style="margin-bottom: .0001pt; margin-bottom: 0in;">
<b><span style="color: #cc0000;">- Advanced forecasting and simulations to better understand how much money can be raised. </span></b></div>
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<o:p></o:p></div>
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<br /></div>
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Most readers
understand segmentation but there are many ways to segment an annual giving constituency, including:
<o:p></o:p></div>
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<br /></div>
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<!--[if !supportLists]-->1)<span style="font-size: 7pt;">
</span><!--[endif]-->Philanthropic Interests <o:p></o:p></div>
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<!--[if !supportLists]-->2)<span style="font-size: 7pt;">
</span><!--[endif]-->Engagement and touch points: events attended,
publications received, services provided, etc.<o:p></o:p></div>
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<!--[if !supportLists]-->3)<span style="font-size: 7pt;">
</span><!--[endif]-->Giving History such and length of giving relationship
or amount given <o:p></o:p></div>
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<!--[if !supportLists]-->4)<span style="font-size: 7pt;">
</span><!--[endif]-->Channels by which gifts are made: mail, phone,
or online. <o:p></o:p></div>
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<o:p></o:p></div>
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Analytics generally supports prospect research by deriving a quantitative scoring methodology that
measures how close or “warm” an individual is to the organization. Scores can
then be used to prioritize which individuals should have a more complete dossier completed. <o:p></o:p></div>
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<br /></div>
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Performance
enhancement is the category of analytics usage that best describes its
relationship with Annual Giving. Annual Giving is usually considered “low gifts
at high volume” and the cost to raise each dollar is relatively high. But the
true value of Annual Giving is not necessarily in how much money is raised at
the lowest possible cost, but instead to cultivate a culture of philanthropy and
engagement at an institution. All of these factors, maybe somewhat misaligned, make Annual Giving operations ripe for quantitative analytics. Our next post will explore specific techniques and methodologies for integrating analytics into the Annual Giving business process. <o:p></o:p></div>
Unknownnoreply@blogger.com12tag:blogger.com,1999:blog-5650695888572690847.post-36812964700873500272013-01-18T15:23:00.001-06:002013-01-18T15:23:37.528-06:002012 is OVER! (So let's talk about it)Happy New Year Everyone!<br />
<br />
2012 was an exciting year at DonorCast. We strengthened our team by adding two new positions and expanded our market to include clients in Continental Europe and the United Kingdom. But not everything we did this year was new, we also freshened up our Fundraising Analytics industry-wide survey. Let's go over the results.<br />
<br />
Ninety-one individuals responded to the survey, 31 more than the 60 that responded in 2010. This larger sample size gives us a clearer picture of how analytics is being used to improve nonprofit fundraising. Higher Education continues to be the largest category of institutions participating, with research universities the largest sub-category. This probably shows that higher education organizations have the most developed and sophisticated fundraising operations. However, even though research oriented institutions made up 50% of the respondents, both staff sizes and the amount of money that respondents raise annually varied greatly, with the average staff size being about 25 fundraisers raising approximately $45 million a year.<br />
<br />
The analytical techniques that are applied to the multiple aspects of fundraising have remained stable with most respondents using descriptive analysis, predictive modeling, and point-based scoring to identify prospects, analyse performance, and segment donors to create more donor-centric appeals. Interestingly, more organizations have stated that they use analytics to assist in the production of reports, which might mean that analytics is becoming more ingrained in the culture of their organizations. This is a good sign and should lead to higher productivity across all aspects of their fundraising operations. Of the software tools used to complete analysis, both the open-source program R and the statistical package Minitab are more widely used now than they were two years ago. SPSS is still the most widely used software program but it's share has fallen by about 20%.<br />
<br />
Staffing, and staff compensation, have remained stable since 2010. Ninety-one percent of the respondents have dedicated prospect research and analytics staff with analysts reporting an average annual salary of $45,000 to $50,000 and Directors earning roughly $80,000 per year. Two directors reported earning over $100,000 in annual salary.<br />
<br />
While there weren't any "eye poppers" in this year's survey, that might be a good thing. Since the fundraising analytics industry has grown substantially in the past five to ten years, two years of relative calm might show that our institutions have embraced analytics for the long haul and we are fully integrated into our institutions' operations. The increased use of anayltics in reporting and the integration of R and Minitab into our shops shows that people in our industry are continually experimenting with analytics – both its uses and the products used to create powerful analysis. I think this bodes well for future innovation in our space. Unknownnoreply@blogger.com16tag:blogger.com,1999:blog-5650695888572690847.post-71214709101816650472012-10-08T13:53:00.001-05:002012-10-25T11:32:25.078-05:00Analytics and Research in Fundraising<!--[if gte mso 9]><xml>
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</xml><![endif]-->Last time, I wrote about how research and analytics functions are viewed in other industries in order to gain some perspective on how the two disciplines
fit into a fundraising shop. <br />
In most institution's fundraising development programs there are two
categories of activity and responsibilities, front-line fundraising and
back-of-the-house operations. Front-line fundraising is pretty self explanatory;
it is working with donors face-to-face on a day-to-day basis and is what our
prospect and relationship managers do. Sometimes we refer to this work as
acting as a liaison between philanthropic donors and an organization's mission.
Back-of-the-house operations encompass a lot of activities from technology management,
data maintenance, gift processing and…and…and…prospect research and analytics. This
goes to show that before front-line fundraisers can talk to donors, or an
annual giving director can send out their mailing, quite a bit of work needs to
be done to understand an individual donor’s ability and propensity to give.
This work is done by analysts and prospect researchers. <br />
<br />
The first step in any prospect development process is analytics. Analytics
staff, using advanced data mining and modeling methodologies as well as wealth
screenings conducted by outside vendors, identifies an organization’s best potential
prospects. These prospects are then placed into refined pools and assigned to
the limited number of managers that all institutions have. In addition to identifying
potential prospects, analytics staff will also produce technical reports that
help management to best understand the performance of the entire development
program. These activities are programmatic and on-going. Identifying potential
prospects and measuring performance never ends and is an important part of
stewarding an ongoing concern like a university or medical center. <br />
<br />
Prospect research provides the specific information that is required to best
solicit and steward those prospects that are merely identified by analytics. This
research uses multiple techniques – surveys distributed amongst constituents,
peer screening collected by research staff, and discovery visits – to determine
what it takes to turn a prospect into a donor. Unlike an on-going analytics
program, these research activities are specific to each prospect at that point in time. Examples of
specific prospect research deliverables include donor engagement reports, donor
profiles, and targeted research for unique to individuals. Each of these deliverables
are individual projects that once completed lead to better insight about
already identified prospects. They answer the research question: “Is this identified
prospect a potential donor? And if so, under what conditions and strategy.” <span style="mso-spacerun: yes;"> </span><br />
<br />
So even though analytics is a relatively new function in fundraising development,
it does not replace traditional prospect research. It enhances it, and provides
accountability to the entire development program through measurement. Analytics
is an aid, a technical tool that improves our philanthropic work by increasing return-on-investment
and better targeting very large files of prospects. <span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span>
Unknownnoreply@blogger.com8tag:blogger.com,1999:blog-5650695888572690847.post-67707350224059438422012-09-27T11:02:00.000-05:002012-09-27T11:03:16.051-05:00Analytics and Research Functions in Industry<!--[if gte mso 9]><xml>
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Analytics is a growing function across all sectors and industries of the
economy. DonorCast and Bentz Whaley Flessner are committed to harnessing and implementing the
best analytics practices for the betterment of philanthropy and charitable
giving. As many of our readers already know, we find that using analytics as a
part of an organization's fundraising development program greatly increases not
only the total amount of money that an organization can raise, but also the
efficiency of the resources required to raise those dollars.<br />
<br />
As proponents of analytics, we must explain what analytics is and where it
fits as the third leg of a fundraising operation stool alongside front-line
fundraising and prospect research. This post is the first in a two-part series regarding
how we should think about analytics in fundraising and especially its
relationship to prospect research. <br />
<br />
<br />
I think that it will be helpful to look at how many other industries
distinguish between "research" and "analytics". In consumer
markets like packaged goods, financial services, and retail as well as the
medical fields of toxicology, oncology, and epidemiology, research is the
process of discovery, and is associated with proving a hypothesis. Research
deals with specific cases, and generally, smaller, more manageable amounts of
data that can be controlled and isolated in order to identify key relationships
between independent and dependent variables. In terms of management, research
is more project based, and when conclusions are found, or insights arrived at,
then a research project is concluded.<br />
<br />
Analytics, also referred to as Business Intelligence, is slightly different
and is most accurately thought of as an ongoing management tool. Analytics is a
program that constantly collects and measures data that can then be used by
management to make decisions about, and adjustments to, strategy. Analytics is
much more aligned with an organization's overall business needs – the
allocation of resources, return on investment, and definition of success – than
research. Many practitioners will say that as a phenomenon becomes better
understood, it moves from being the subject of research questions to being a component
of management analytics. Instead of understanding what something is or how it
works, analytics focuses on the incremental changes that are needed to make a
process as efficient and effective as possible. So while many of the tools that
research and analytics use can be the same, such as quantitative methods and
predictive modeling, their role in an on-going, enterprise system are slightly
different.<br />
<br />
In conclusion, analytics and research are both extremely valuable to all kinds of organizations but they play different roles and should be
thought of as separate, essential functions. The next post,
will discuss analytics and research in fundraising specifically and how they work together to accomplish institutional goals. <span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span><span style="mso-spacerun: yes;"> </span>
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<![endif]-->Unknownnoreply@blogger.com3tag:blogger.com,1999:blog-5650695888572690847.post-14616369318424712152012-08-15T14:11:00.002-05:002012-08-15T14:12:28.194-05:00Medalball - Statistics is a ScienceOkay, real quick. Before we are all fully recovered from our Olympic hangovers, I thought that it would be helpful for me to bring to every one's attention Nate Silver's article from a few days ago about using data to identify which sports a poor nation should focus their resources on if they want to medal at the Olympics: <a href="http://www.nytimes.com/2012/07/22/sports/olympics/how-much-for-an-olympic-medal.html">Medalball</a>.<br />
<br />
As many of you may know, Josh and Alex like to use Michael Lewis’s famous book-turned-movie "Moneyball" as an analogy for the work that we do at DonorCast helping nonprofits to identify the ways to get the best fundraising returns given their usually limited financial resources. Nate's article uses the analogy as a way to give direction to small, poor nations that might want winning a medal at the Olympics to give their countries a PR boost. But what I like most about this article is it's structure, and how it sheds light on the logic and thought that is needed to give context and underlying reasoning to the use of statistics and quantitative methods. <br />
Too often in our careers we encounter clients, decisions makers, or individuals that just want to know "what the data says" or to be "given the stats". They will then use this measured, quantitative information to make a decision. But really, it's not that easy, and actually such an approach can be very dangerous. <br />
<br />
What many people often forget, especially non-quantitative professionals, is that statistics is a science, the science of uncertainty, variability, and decision making. The scientific method requires the testing of a hypothesis, or <i>proposed explanation of a phenomena</i>. This means the stats don't tell a story by themselves, stats are only tools that we use to paint a clearer picture of phenomenon that we already believe that we have a good idea of how it looks. Statistics and data are properly placed at the end of a decision making process, not at the beginning.<br />
<br />
Colin Mallows, the one time President of the American Statistical Association, once stated that "<i>statisticians should give more attention to the questions that arise at the beginning of a problem or an issue:</i><br />
<ol>
<li><i>Consider what data are relevant to the problem,</i></li>
<li><i>Consider how relevant data can be obtained,</i></li>
<li><i>Explain the basis of all assumptions, </i></li>
<li><i>Lay out all sides of an argument,</i></li>
<li><i>Formulate questions that can be addressed by statistical methods.</i>" </li>
</ol>
This is what Nate Silver does in Medalball. He begins with considering what data is relevant to solving the problem of "<i>which sports a small country with limited resources should direct their energy to in order to maximize their medal count</i>". He already had a string of logic that he would wanted to follow in order to solve the problem that he then used statistical methods, in this case descriptive analysis, to verify and test his hypothesis. <br />
<br />
Statistics and data are not replacements for thought and contemplation, instead they are merely powerful aids for better understanding our already formed ideas and presumptions about the world. Unknownnoreply@blogger.com50tag:blogger.com,1999:blog-5650695888572690847.post-37279120597277256792012-08-10T11:09:00.000-05:002012-08-14T12:46:21.181-05:00Morgan Zehner Introduction<div class="MsoNormal" style="font-family: Arial,Helvetica,sans-serif;">
<div class="MsoNormal">
<span style="font-family: "Arial","sans-serif"; font-size: small;">My
name is Morgan Zehner and I am the newest member of the DonorCast Team. I want
to introduce myself to the awesome community that we serve and I thought that a
blog entry would be a good place to start. I will be the primary analyst for
all of DonorCast’s program analysis projects. I am really looking forward to
providing continued innovation to the DonorCast forecasting methodology and
designing nonprofit sector metrics to better understand development
productivity and performance. And, like Josh did, I am going to write a book. </span></div>
</div>
<div class="MsoNormal" style="font-family: Arial,Helvetica,sans-serif;">
</div>
<div class="MsoNormal" style="font-family: Arial,Helvetica,sans-serif;">
<span style="font-size: small;">So, a
little about ME (visit <a href="http://www.bwf.com/who-we-are/team/morgan-zehner/">my web page</a> and
watch <a href="http://www.youtube.com/watch?v=cBy6rP3Gv9E">my bio-video</a>). I
began my career in nonprofit leadership as the Executive Director of Dupont
Circle Main Streets. Dupont Circle is an internationally recognized commercial
district in Washington, DC. I first joined the nonprofit world because I was
passionate about a specific mission – urban revitalization – but I quickly
realized that I had a knack for fundraising. While in Dupont, I was able to
quadruple the organization’s budget by executing a portfolio of fundraising
methods – from annual giving and grant writing to special events and securing a
$90K major gift. After leading the organization through this growth period, I
started my own consulting business where I provided small businesses and nonprofit
organizations with counsel in the areas of market research, strategic planning,
and fundraising development.</span></div>
<div class="MsoNormal" style="font-family: Arial,Helvetica,sans-serif;">
</div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;">While the first part of my career has been
incredible and full of accomplishments, I have always wanted to do technical,
analytical work. As an undergraduate student at McGill University, I was
drawn to quantitative social research and wanted to use those skills, or as
Alex says “flex those muscles”, in my career. With that as my calling, I
attended the full-time MBA program at the Carlson School of Management at the
University of Minnesota where I focused my studies on market research and
strategic management. It is this combination of experience and education that
has made Bentz Whaley Flessner, and DonorCast in particular, a perfect fit. BWF
is an entrepreneurial and innovative small consulting shop where I use my
technical skills to serve an industry I respect. Nothing could be better
and I am greatly looking forward to working with all of you. </span></div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
</div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;">If you have any questions or would like to
introduce yourself to me (please do!) drop me a line or follow me on Twitter</span></div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
</div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;"><a href="mailto:mzehner@bwf.com">mzehner@bwf.com</a></span></div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;"><a href="https://twitter.com/morganmz">@morganmz</a></span></div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
</div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;">Thanks! and looking forward to working with
you, </span></div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
</div>
<div style="font-family: Arial,Helvetica,sans-serif; margin: 0in 0in 0.0001pt;">
<span style="font-size: small;"><a href="http://www.bwf.com/who-we-are/team/morgan-zehner/">Morgan</a> </span></div>
<div class="separator" style="clear: both; text-align: center;">
<span style="font-size: small;"><iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/cBy6rP3Gv9E?feature=player_embedded' frameborder='0'></iframe></span></div>
Unknownnoreply@blogger.com4tag:blogger.com,1999:blog-5650695888572690847.post-13754673354358922982011-10-28T14:16:00.005-05:002011-10-28T14:32:29.790-05:00Predictive Modeling for Direct Mail at Children's Mercy Kansas CityThe direct mail program at <a href="http://www.childrensmercy.org/" target="_blank">Children’s Mercy Hospitals and Clinics in Kansas City</a> has been raising more money and is costing the hospital less to implement. Why? Because <a href="http://www.linkedin.com/in/davidpaullogan" target="_blank">David Logan‘s</a> annual fund team has been paying attention to the numbers and using <a href="http://donorcast.com/services/predictive_modeling.php" target="_blank">predictive modeling</a> to better target the mail they send out. Check out the video below for a more complete explanation of David and team’s work…<br /><br /><iframe width="398" height="238" src="http://www.youtube.com/embed/6HpXb-h33kM" frameborder="0" allowfullscreen></iframe>Unknownnoreply@blogger.com6tag:blogger.com,1999:blog-5650695888572690847.post-48813595080170988652011-10-06T14:23:00.007-05:002011-10-06T15:05:05.511-05:00"Data Hoarders" A New Parody from the BWF TeamAre you a data hoarder? Do you have to parse through mountains of relatively useless information to find those oh-so-valuable tidbits that can make or break your fundraising efforts? If so, help is available...<br /><br />The <a href="http://donorcast.com/"target="_blank">Donorcast</a> team joined forces with the <a href="http://www.bwf.com/services-for-you/social-media/"target="_blank">BWF Social</a> crew to bring you "Data Hoarders" - a parody of the A&E series "Hoarders."<br /><br /><iframe width="398" height="238" src="http://www.youtube.com/embed/EsY5hnE1NKs" frameborder="0" allowfullscreen></iframe>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-11870662034994326792011-09-19T10:55:00.007-05:002011-09-19T11:02:10.425-05:00Should I go into fundraising analytics?<a href="http://s3.amazonaws.com/data.tumblr.com/tumblr_lrmzz20ylb1qhmsybo1_1280.jpg?AWSAccessKeyId=AKIAJ6IHWSU3BX3X7X3Q&Expires=1316534481&Signature=Xz8Kp6leU0ufyui3N6aTZAshCOA%3D" onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}"><img style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 400px; height: 606px;" src="http://s3.amazonaws.com/data.tumblr.com/tumblr_lrmzz20ylb1qhmsybo1_1280.jpg?AWSAccessKeyId=AKIAJ6IHWSU3BX3X7X3Q&Expires=1316534481&Signature=Xz8Kp6leU0ufyui3N6aTZAshCOA%3D" border="0" alt="" /></a><br /><div style="text-align: center;"><br /></div>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-32931899388384267162011-06-08T13:00:00.000-05:002011-06-08T13:01:56.074-05:005 reasons every nonprofit should use analytics for fundraising<span style="font-weight:bold;">1. Identify Prospects </span><br />Anyone working in major gift development realizes, despite all the benefits, wealth screening has its limitations. Most wealth data is not public information, matching is never perfect, and being wealthy alone does not make one a prospect. Predictive analytics can find the individuals fitting your organization’s donor profile. It can help you find the people with the connections, potential passion for mission, and likely wealth. By adding dimensions to your prospect identification, you can find more and better potential major donors.<br /><br /><b>2. Do more with existing staff</b><br />Among the most immediate benefits of predictive analytics is staff efficiencies. Prospect researchers can look at fewer names to find prospects for assignments. This can bring up to double the output from research at many nonprofits. You can contact fewer individuals and net at-or-above previous direct marketing efforts. Analytics is also helpful in tuning processes such as prospect management and engagement strategies.<br /><br /><b>3. Make better decisions</b><br />When I meet with the fundraising staff at most of my clients, they tell me that their executives are not data people. When I meet with the executives, they often say, “No one gives me data around here.” Modern, effective fundraising leadership desires and requires more thoughtful decision support than ever before. Analytics can point out gaps, reveal opportunities, and clarify production clogs better than any tools we’ve had to date. Arming the experienced fundraiser with timely and relevant data can be transformative for nonprofits.<br /><br /><b>4. Manage data more effectively</b><br />Organizations with an eye towards analytics gather and store data in their donor management system differently than other organizations. Initially, they make sure every touch point between constituent and organization is captured. Then, they make strides in capturing process data in a more granular fashion. Rather than simply record contact reports as free text data, analytics enterprises will record where the meetings took place, what steps were taken, adjustments to strategies, and targeting refinements as codes. This enables them to learn how to best cultivate new prospects, engage cold relationships, and bring about sustainable involvement.<br /><br /><b>5. Raise more money</b><br />Productivity is the bottom line of any nonprofit fundraising program. To raise more money, an organization needs to ask more and ask smarter. From setting campaign ask amounts to determining solicitation readiness, and from staffing analysis to measuring return on investment, analytics can help your nonprofit raise more money. And, that’s why we’re here. Isn’t it?Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com1tag:blogger.com,1999:blog-5650695888572690847.post-72693802926058465852011-06-01T15:23:00.005-05:002011-06-01T16:18:32.340-05:002011 Analytics for Fundraising survey results infographic<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDQCZkaN1vYbsykE3Bi6bYPY7NTTWTJkQdZR8ey1phX8G5O6LSJyZavebekjWRGv84kmfUWLh5EYkKbOrYCzbfzW0dd52aRIRNMk0fRIF2mqwdYdEyuB7FPCoH0Rc5kOsh_TG7QAzKMwpS/s1600/Analytics.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="960" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhDQCZkaN1vYbsykE3Bi6bYPY7NTTWTJkQdZR8ey1phX8G5O6LSJyZavebekjWRGv84kmfUWLh5EYkKbOrYCzbfzW0dd52aRIRNMk0fRIF2mqwdYdEyuB7FPCoH0Rc5kOsh_TG7QAzKMwpS/s640/Analytics.jpg" width="391" /></a></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfXNZBA-wD4MHIg23nSXUn4-8d-MTBKSz8amOAxi40LLGuxXlQy4iIUEO0Rq3gxAMO8DnI9_CJ1T697grgPw-bb53hG7tjzsmsWZbjzrZC16G3gIhSKZ8C32nMb6dU9mKDV4SdPYRgWd3D/s1600/Analytics.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><span id="goog_175663116"></span><span id="goog_175663117"></span></a></div>Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-5650695888572690847.post-55502208832801987782011-05-19T10:11:00.006-05:002011-05-19T10:18:19.695-05:00FREE Webinar - The Role of Data in Fundraising StrategyTo Join the Online Briefing: click <a href="https://www119.livemeeting.com/cc/gc_pro_namewreg_bwf/webJoin?id=May_Online_Briefing&pw=strategy&role=attend" target="_blank">HERE </a> Entry Code: <span style="font-weight:bold;">strategy</span><br /><br />Perhaps e.e. cummings best described the prevailing approach to fundraising strategy in Seeker of Truth. But sometimes what is common is not what is best. <br /><br />To celebrate Analytics month at Bentz Whaley Flessner, our three in-house fundraising economists will explore the role of data in fundraising strategy development and decision-making. From predictive analytics in prospecting to cultivation modeling, and from risk-adjustment to campaign forecasting, expect a practical exploration of data-driven approaches for your fundraising operation. Join Alex Oftelie, Jeff Lockhart, and Joshua Birkholz in this unique online discussion. We may not know where all paths lead, but truth is here and the price is right.<br /><br /><span style="font-weight:bold;">Date:</span> Thursday, May 19, 2011<br /><br /><span style="font-weight:bold;">Time:</span> 12:00 Noon-1:00 pm Central; 1:00-2:00 pm Eastern <br /><br /><span style="font-weight:bold;">BWF Consultant:</span> Joshua Birkholz, Principal, Bentz Whaley Flessner <br /><span style="font-weight:bold;">Guest Presenters:</span> Alexander Oftelie, Director of Operations and Analytics, and Jeff Lockhart, Senior Analyst, Bentz Whaley FlessnerUnknownnoreply@blogger.com1tag:blogger.com,1999:blog-5650695888572690847.post-24477980648486340062011-05-13T18:48:00.003-05:002011-05-13T18:54:39.992-05:00Top Chef DonorCast Parody (read "math nerds make funny video!" - funny awesome!!)<iframe width="400" height="257" src="http://www.youtube.com/embed/ix_BM-NAyxo" frameborder="0" allowfullscreen=""></iframe>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-16834023277946827802011-04-27T10:43:00.003-05:002011-04-27T10:50:27.625-05:00We’ll be at the APRA Data Analytics Symposium in Austin, Will you?Kate Chamberlin was telling me about the program for this year’s APRA’s analytics symposium. It sounds really cool. I especially like the section of case studies they’ve lined up. Several great institutions will be highlighting aspects of their own real projects. This conference will hardly be just “theory.” Here is the official blurb:<div><br /><div>Explore the potential of data analytics and learn from an expert faculty during the Data Analytics Symposium, July 27 – 28 in Austin, Texas.</div><div><br /></div><div>Designed for analysts, development IT professionals, business intelligence professionals and fundraising managers the Data Analytics Symposium — held in conjunction with <a target="_blank" href="http://bit.ly/eadAtG">APRA’s 24th Annual International Conference</a> — will help you identify new and exciting ways to approach fundraising and organizational growth with minimal investment. Educational sessions will review in-depth case studies to understand what works (and what doesn’t) when tackling real-world solutions. The fundamental track will teach you how to start a successful analytics program, while the intermediate/advanced track will share the latest in ideas, presentation models and analytics methods.</div><div><br /></div><div><a target="_blank" href="http://bit.ly/gGCng2">Read more</a></div></div>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-78799789336594072012011-04-11T15:15:00.005-05:002011-04-12T12:13:21.916-05:00From BWF news today. Welcome Justin Ware. BWF Director of Social Media<p class="MsoNormal"><o:p> </o:p></p> <div style="text-align: -webkit-auto;"><span class="Apple-style-span"><span class="Apple-style-span" style="-webkit-border-horizontal-spacing: 10px; -webkit-border-vertical-spacing: 10px; "><p><span class="Apple-style-span" style="font-family: 'Trebuchet MS', sans-serif; font-size: 13px; ">Friends,</span></p><p><span style="font-size: 10pt; font-family: 'Trebuchet MS', sans-serif; ">At Bentz Whaley Flessner, we appreciate the confidence and loyalty you have in our innovative specialty consulting services. From development operations to prospecting and from analytics to engagement strategies, we are proud of the ways we’ve partnered with you to transform philanthropy. Now, in response to considerable demand for counsel and services in new media, we are pleased to announce a new addition to our specialty consulting team, Justin Ware.<br /><br />Justin Ware is the Director of Social Media for Bentz Whaley Flessner. Justin provides our clients with his proven experience in new media technologies, specifically with diagnostic assessments of their social media strategies; content production guidance, counsel and training in social graph development and video communication, and coaching for nonprofit leadership in press and media interaction.<br /><br />Justin brings nearly a decade of video communication and new media experience to Bentz Whaley Flessner. He began in television news as a reporter, anchor, and producer; continued on to higher education at the University of Minnesota, where he developed the top ten, most-viewed YouTube site in higher education, and went on to found the social media company, Warehouse Media, where he provided media services in higher education, youth development, environment and green energy, convention and event management, and financial services. Justin puts his Emmy-winning experience to work producing and leveraging video and written communication strategies to help nonprofits achieve their goals and communicate their message using new media. He has a BA in Journalism and Mass Communication from the University of Minnesota.<br /><br />We look forward to partnering with you once again, that together we might transform philanthropy. Justin can be reached at <a href="mailto:jware@bwf.com">jware@bwf.com</a> and at our website, <a href="http://www.bwf.com/">www.bwf.com</a>.<br /><br /><i>Joshua M. Birkholz<br />Principal, Bentz Whaley Flessner</i></span></p></span></span></div>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-60602294213948452592011-03-28T12:35:00.002-05:002011-03-28T12:39:37.635-05:00The Popularity of Data Analysis Software: R vs SAS vs SPSS<span class="Apple-style-span">As posted on KDDnuggets. A paper written by <span class="Apple-style-span" style="border-collapse: collapse; font-size: 14px; -webkit-border-horizontal-spacing: 2px; -webkit-border-vertical-spacing: 2px; ">Robert A. Muenchen.</span></span><div><span class="Apple-style-span" style="border-collapse: collapse; font-family: arial, verdana, tahoma, geneva; font-size: 14px; -webkit-border-horizontal-spacing: 2px; -webkit-border-vertical-spacing: 2px; "><br /></span></div><div><span class="Apple-style-span" style="border-collapse: collapse; font-family: arial, verdana, tahoma, geneva; font-size: 14px; -webkit-border-horizontal-spacing: 2px; -webkit-border-vertical-spacing: 2px; "><p style="font-family: arial, verdana, tahoma, geneva; font-size: 14px; ">Among more interesting observations</p><ul><li>R has the largest number of email discussions (by 2-to-1 margin), followed by Stata and SAS</li><li>the number of R packages published on CRAN continues to grow exponentially</li><li>R is leading in blogs (170), with only 31 blogs for 2nd place SAS</li><li>However, jobs mentioned SAS and SPSS have a big lead over jobs mentioning R</li></ul><div><a href="http://bit.ly/gvz3Kf" target="_blank">Click to see the KDD page with the article</a></div></span></div>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-2112622739720339492011-03-21T15:04:00.001-05:002011-03-21T15:05:28.865-05:002nd Survey on Analytics for FundraisingThe 2nd Survey on Analytics for Fundraising is here! The goal of this survey is to better understand our industry, our colleagues, and trends in analysis and software.<br />
<br />
<div class="MsoPlainText">All results will be public. Anyone can request a raw file of the results yourself for your own data-mining!</div><div class="MsoPlainText"><br />
</div><div class="MsoPlainText">Please feel free to send a link of this survey to anyone you feel has something to share. </div><div class="MsoPlainText"><br />
</div><div class="MsoPlainText"><a href="http://www.zoomerang.com/Survey/WEB22C4528DXVY/">Click here to begin the survey </a></div><div class="MsoPlainText"></div><div class="MsoPlainText"></div><div class="MsoPlainText"></div><div class="MsoPlainText"></div><div class="MsoPlainText"></div>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-6242367145246463322011-03-21T00:00:00.007-05:002011-03-21T00:11:32.876-05:00The Last 12 Months of DonorCast Newswatch Posts Visualized in Many Eyes<div style="text-align: center;"><br /></div><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDk_E1SKVC_kHIvLdjVTIfmYFTKIlay0_ncoaUDbw4fkKRcmEjPSaWQXRX6FPj7zoT5t6wEw015NN684PGQ_MyTLiNGefhWqQnf8JPCMjdo-ZJCiiGpE_3YtEikGMVV60Zujc84XDNkCOQ/s400/Tree.jpg" style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 400px; height: 227px;" border="0" alt="" id="BLOGGER_PHOTO_ID_5586394989740262978" /><div><a href="http://www-958.ibm.com/software/data/cognos/manyeyes/visualizations/fundraising-analytics-from-12-mont" target="_blank">Click for interactive view</a><br /></div><div><br /></div><div><br /></div><div><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQKtNe4UKulZIEPOJ9NZYZwecBuiY4-qxFxkyUT5C92-BMrU-h5R6JXSA9FoeiannwFCXszZhNChT-RGukBNufr4j4f-eOnFlz1hYXMMEywngnwfZ9QMco7EnD8XOjR29Z-EnYUOM96nXP/s400/cloud.jpg" style="display:block; margin:0px auto 10px; text-align:center;cursor:pointer; cursor:hand;width: 400px; height: 177px;" border="0" alt="" id="BLOGGER_PHOTO_ID_5586395294806424514" /><div><a href="http://www-958.ibm.com/software/data/cognos/manyeyes/visualizations/12-months-of-donorcast-newswatch-p" target="_blank">Click for interactive view</a></div></div>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-84870980043525284322011-03-15T10:33:00.002-05:002011-03-15T10:43:56.532-05:00Hear me on AFP/wiley Radio with Ted Hart noon EST today http://bit.ly/enkGmOAFP/ Wiley Radio The Nonprofit Coach w/ Ted Hart (Joshua M. Birkholz - Fundraising Analytics Expert) Noon EST Today, March 15, 2011<br /><br /><a href="http://bit.ly/enkGmO">Click to join</a>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-11611869573610981252011-03-11T17:56:00.001-06:002011-03-11T17:58:27.141-06:00Big Data mining: Who owns your social network data?An attractive application of Hadoop and other Big Data technologies is to analyze users' social activities, sometimes without their express knowledge<br /><br />By Paul Krill | InfoWorld<br /><br />The now-trendy concept of Big Data usually implies ever-growing hordes of data, including unstructured info posted on Facebook and Twitter, and ways of gleaning intelligence from all of it to create business opportunities. The concept, however, also carries with it risks for anyone opening up about themselves on the Internet and raises questions about who exactly owns all this data.<br /><br />Big Data is associated with technologies such as the Apache Hadoop distributed computing platform and is prompting some technology companies, including IBM, to make major acquisitions. But the term "Big Data," claims GigaOm analyst Derrick Harris, is a bit of a misnomer; it's really about data from different sources, including social networks and even cell phones. "It's coming from sensors, it's coming from computers, it's coming from the Web," he says.<br /><br /><a href="http://www.infoworld.com/d/business-intelligence/big-data-mining-who-owns-your-social-network-data-746""target="_blank">Read more</a>Josh Birkholzhttp://www.blogger.com/profile/05141204260038463872noreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-8218269566457091002011-03-11T16:06:00.004-06:002011-03-11T16:17:26.330-06:00Statistics in golf can yield great benefitsFollowing up on our sports-related posts a few months back, the golf fan in me loved this article. Now I can tell my wife I have to watch golf for work.<div><br /></div><div><i>In response to such trends, the Massachusetts Institute of Technology's Sloan Sports Analytics Conference held the first Golf Analytics panel in the conference's 5-year history to discuss potential applications of advanced statistical analysis in golf. We've seen numbers-crunchers change baseball, basketball, and football. Golf could be next. </i><br /><br /><div><span class="Apple-style-span"><span class="Apple-style-span" style="line-height: 21px; "><span class="Apple-style-span"><a href="http://www.golfweek.com/news/2011/mar/09/statistics-golf-can-yield-great-benefits/?BLOG-TourBlog"target="_blank">Read more</a></span></span></span></div><div><br /></div></div>Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-5650695888572690847.post-77766352509710776132011-02-23T14:49:00.003-06:002011-02-23T15:00:04.765-06:00And the Oscar goes to......Ryan Kavanaugh? In the spirit of Sunday's Oscars, I wanted to pass along an article I read the other day discussing Ryan Kavanaugh, a movie producer, and his company's use of analytics to manage risk.<br /><br /><span style="font-style: italic;">When deciding which films to make, Relativity Media executives rely heavily on data. They use what they call a regression analysis—a computer deep-dive into dozens of variables that could affect a film's potential performance, such as genre, release date, and actor's appeal—before deciding to greenlight a film. The goal: limiting the company's risk. </span><br /><br /><a href="http://www.businessweek.com/magazine/content/11_09/b4217024893975.htm" target="_blank">Read more<br /></a>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-48996730436804235242011-02-04T17:35:00.000-06:002011-02-04T17:35:49.978-06:00The "Netflix prize" model...only this time more seriousJosh and I have both <a href="http://donorcast.blogspot.com/search?q=netflix">posted</a> about the Netflix Prize...drawn to both the idea of creating a very accurate preference/choice models with a very large menu of outcomes, as well as the <a href="http://en.wikipedia.org/wiki/The_Wisdom_of_Crowds">crowd-sourced</a> approach to solving the problem (and there was in fact a winner).<br />
<br />
Well I am very excited to share this approach has been applied to a more "serious" problem: build a model that will predict upcoming hospitalizations. The end result is far more lofty than a movie pairing to "Young Frankenstein". This project hopes to identify individuals at greatest risk for imminent adverse events before they happen, creating an "early detection" system to save lives and reduce overall costs.<br />
<br />
A $3mil prize is also a great incentive...keep an eye on this content.<br />
<br />
<b><i>Netflix Prize-Style Competition Predicts Hospitalizations</i></b><br />
<i>What if you could predict if a given patient were at a higher risk for hospitalization in the coming year? You could potentially save money, and lives, by pulling out all the stops to prevent that hospital visit, if possible. And that's why the Heritage Provider Network (HPN) has put up $3 million for a Netflix Prize-style competition that will pit coders against each other to devise the most effective predictive algorithm for incipient hospitalizations. HPN will be announcing a launch date for the prize this week.</i><br />
<br />
<a href="http://www.fastcompany.com/1722576/netflix-prize-style-competition-predicts-hospitalizations">Read more</a>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5650695888572690847.post-37277311940933744892011-02-01T09:14:00.001-06:002011-02-01T09:14:54.273-06:00A interwebs dialog!Mark Egge, a very sharp prospect researcher and data-miner, in addition to being my favorite classical saxophonist, posted a response to my CRISP-DM post. It only took about two years but we have an actual interwebs dialog on data-mining!<br />
<div><br />
</div><div>I know Josh posted a link to the CoolDataBlog (Kevin MacDonnell has some great ideas and since he is Canadian, all the American readers can say they consult "international sources"). Well Mark is another colleague to pay close attention too.</div><div><br />
</div><div>Maybe this dialog can put the pressure on both of us to add content more frequently </div><div><br />
</div><div>Check out Mark's blog, <a href="http://managingprospectresearch.wordpress.com/?p=50&preview=true" target="_blank">Managing Prospect Research</a><br />
</div>Unknownnoreply@blogger.com0