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Google Alerts: what’s going on

Google Alerts

Several people have asked me lately about the demise of Google Alerts so here’s a little background for you as well as links to selected resources for more information and better results.

In case you’ve never used Google Alerts, here’s what they are: Google has a page where you can set an alert on a search string to automatically run the search and have results sent to you on a schedule of your choosing. Until recently, this notification could come by email OR via a very handy direct pipeline called an RSS feed to a free Google Reader account.

THE BEGINNING OF THE PROBLEM

Unfortunately, and to a great deal of hue and cry, this past July Google pulled the plug on Google Reader and on the ability for users to receive Google Alerts via an RSS feed. Alerts could only be received via email.

Coupled with all of this was evidence that Google Alerts were not working as well as they had been in the past. Noted search engine expert Danny Sullivan reported that his alerts were significantly reduced and he wondered (as many others did) if this signaled the demise of Google Alerts as well.

However, in September of this year it was reported by a few who noticed that Google Alerts were again available via RSS feed – not that Google made a splashy big deal of it. Quite the contrary.

SO WHAT’S THE DEAL?  

We really don’t know if Google Alerts are going away, or if they are going to remain but be unsupported, or if they will eventually be phased out like Reader. It certainly appears to experts that alerts are not being supported by Google now as they were in the past. Notifications are now available again as RSS feeds, but that is small consolation if the information you receive is sparse compared to the amount of information that is truly available within the search engine’s database.

ARE THERE ALTERNATIVES?

We certainly haven’t stopped using Google Alerts here at HBG, but we are using alternatives, both free and fee-based. Two of them are Lexis Nexis and Mention, but there are many for you to choose from. My feeling is: even if Google Alerts give good results, there’s no harm in being sure you’re getting the full scope of what’s available within your budget.

Are you using Google Alerts or an alternative (or both?). Do you have recommendations?

 

Reading list: (articles in order of appearance in post)

Warren, Christina – Mashable: Are Google Alerts Dying? 22 March 2013

Sullivan, Danny – Search Engine Land: Dear Google Alerts: Why Aren’t You Working?  15 February 2013

Protalinski, Emil – The Next Web: Google Alerts regains RSS delivery option it lost after Google Reader’s demise.  11 September 2013

Dembak, Yoav – VB Social: 7 Apps to Help You Replace Google Alerts. 13 May 2013

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Fundraising Analytics ABCs – Visualizing Data

What are the best representations of information that you’ve ever seen? For most people, they’re the ones that are the simplest to understand. The ones that display information clearly and move people to action. Or inaction:

Even in a different language, if we understand the context, the message is still clear.

That’s what good data visualization does. It takes information and lays it out in the simplest of terms to get across what needs to be communicated.

KISS

There’s no getting around the fact that data analytics is intimidating for most of us, and that it produces a lot of really interesting factoids that can move people to action. But when you’re trying to get across complex information, there are still ways to keep messaging simple. In fact, the more complex the information, the more imperative it is to KISS (Keep It Simple, Stupid). Or, in the words of Joey Cherdarchuk, director of operations at DarkHorse Analytics, Data Looks Better Naked.

THE MASTER AT WORK

If you haven’t seen Hans Rosling’s fascinating TED Talks using his free software GapMinder or watched his fascinating holographic data visualization on YouTube, you really should take the time to be impressed. And inspired.

Even if you’re not a data analytics person, watching Dr. Rosling will help you think about presenting information better, whether you’re a frontline fundraiser, researcher, social media guru, consultant or …just about anyone. Okay, go watch those two videos and then come back and we’ll talk more about available resources for visualizing data.

RESOURCES

Now that you’re inspired to do something different, let’s talk about what’s available for manipulating and showing off the great conclusions (or continuing questions) that your data is begging you to share.

Enter the graph, the moving chart, the GIF, the mini movie, the podcast, and the interactive illustration, to name a few, all made possible by recent entries into the market from companies including (in alpha order) Advizor Solutions, a flexible visualization tool that is especially good for looking at annual giving results and gift officer portfolio performance; Factary, whose product Atom allows you to visualize relationships between people, organizations and entities; Rapid Insight, a modeling and illustration package; and Tableau Software, an interactive visualization tool that allows for on-the-fly graphic shifting and drill-down-into-the-data capability.

What’s free?

NodeXL, which adheres to Excel like an elbow-length glove to allow you to manipulate and visualize relationships and social media interactions. Hans Rosling’s Big Data manipulator, GapMinder, which he uses in the aforementioned videos, is also completely free to download. And there are lots of others.

Where are some examples of visualizations?

Here is a terrific collection of resources from Andy Kirk, a UK-based freelance data visualization design consultant. And Mike Bostock of The New York Times has pulled together a great compilation of compelling visualization tools.

Finally, we’d like to leave you with a quote by David Schmitt, head of Performance Strategy and Planning Analytics in the finance division at the Intercontinental Hotels Group (IHG). Schmitt’s team is responsible for communicating information about IHG’s financial performance in a way that is entertaining, compelling and clear. You wouldn’t think that corporate financials would lend themselves to music videos, but that’s one of the tools Schmitt’s group has used to visualized data. For him, “data isn’t the point; numbers aren’t the point—it’s about the idea.”

It looks like our Excel pie chart days are probably over, thank goodness. We’d love to hear about any tools, resources or sites that you’ve found to help you visualize data, too! Please share them here in Comments, so that all of us can check them out.

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Fundraising Analytics ABCs – Donor Modeling

Chances are good if you are in the fundraising field that you have heard the term “fundraising analytics.” You’ve probably also heard the terms “data mining,” “donor modeling,” “reporting” and “prospect identification,” too. Do these terms mean the same thing? What are the differences among them?

I asked Marianne Pelletier, who leads the HBG Analytics team, to help me put together a series of short articles designed to make sense of these terms. In each, she will describe the method and give examples of how they can be used. To continue our series, we describe the questions that Donor Modeling can answer.

Let’s begin with a case study:

A museum is in the planning stage to launch a major fundraising campaign. Their last campaign was over 5 years ago, and while they had a number of significant gifts, the coming campaign will require many more major gifts in order to be successful. After developing a table of gifts for the campaign, it quickly becomes apparent that there are huge gaps that need to be filled with prospects at every level. Significant prospect identification needs to happen.

To score the museum’s database and identify the top prospects, the museum decides to use a technique called predictive modeling, also referred to commonly as donor modeling.

What is donor modeling?

Donor modeling uses statistics tools to score a group of records using a variety of methods, including regression analysis, clustering, decision trees, neural networks and support vector machines (SVMs) amongst lots of others. Let’s take a look at just one of them, regression analysis.

Regression analysis uses calculus to find the slope of a line, which helps us visualize trends in the data. For example, we could see (based on a number of factors) which groups of people in the museum’s database have the most capacity to give as well as affinity, or connection to, the museum.

Here’s a standard matrix that is often built for major gifts programs. After downloading records and using regression analysis to score the group studied, prospects would be shown along the slope of the red line based on their relative affinity with the museum and their capacity to make a major gift.

Affinity, or “how much they love the museum” might be measured by the number of times someone attended events, or donated in consecutive years, or bought tickets to special exhibits, amongst other things. Capacity, or “how much they can give” might be found through primary or secondary research, such as a visit, prospect research or an electronic screening.

A graphic describing the relative level of a group of prospects’ affinity using a number of hearts (ranked on a scale of 1 to 3) and the relative level of their  gift capacity (ranked 1 to 3) by dollar signs might look something like this:

In this example, the top-right box represents those with greatest capacity and affinity for the organization, and the bottom-left box shows those with the least.

If you were the chief development officer at the museum, whom would you want to approach first? Your answer is likely to be those in the top right group. Unfortunately most of the time that group is also the smallest population among the scored groups, and are usually the donors you know fairly well.

Whom to select next, then? Often, two of the largest groups, represented by the larger boxes, are the $$$ ♥♥ and the $$♥♥♥ groups.  And of those, it might be hard to decide which to choose.

So, your next donor modeling study might be to look at the museum’s past track record with each of these two groups. What is your level of success in cultivating each group? What motivates them to become major gift donors?

Donor modeling helps answer those questions. The characteristics of top level donors are compared to various segments of the pool, and their scores help bubble up the best future prospects.

What else can you use donor modeling for?

Although it’s most often used to identify major gifts prospects, donor modeling can also rank groups like these:

  • Annual giving prospects who are most likely to renew
  • People who are likely to be good board/volunteer candidates
  • Planned giving prospects
  • People who would be great prospects for a specific project or campaign (like a library fund, or for endowment)
  • People who would be most likely to accept a request for a visit
  • Top level annual giving prospects
  • Prospects best suited for a particular gift officer or volunteer

Donor modeling can even help determine the best ways to acquire new members for a member recruitment campaign. It’s a powerful tool to help your organization identify new donors, whether you’re in a campaign, thinking about a campaign, or just looking for new donor prospects.

What do you need to know?

Our series on the ABCs of fundraising analytics continues next Thursday, September 19 with a look at data visualization.

Do you have questions about donor modeling or would you like to see it at work at your organization? Contact us at info [at] helenbrowngroup [dot] com for more information.

 

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Fundraising Analytics ABCs – Data Mining

Chances are good if you are in the fundraising field that you have heard the term “fundraising analytics.” You’ve probably also heard the terms “data mining,” “donor modeling,” “reporting” and “prospect identification,” too. Do these terms mean the same thing? What are the differences among them?

I asked Marianne Pelletier, who leads the HBG Analytics team, to help me put together a series of short articles designed to make sense of all of this. In each, we will describe the method and give examples of how they can be used. To begin our series, we discuss data mining.

Let’s begin with a case study:

The fundraising team at a university is having a problem with donor retention. Every year the university must acquire a significant number of new donors to offset the nearly 50% of donors they lose from the previous year. They need to find an answer to the question “why are we losing so many donors, and what can we do to keep them from leaving?”

They decide to use a technique called data mining to find out.

What is data mining?

Sometimes we don’t know what we don’t know. In those situations, it may be best to explore a little to see if we can find answers (and perhaps even see the questions we need to ask). Think of it as discovering what’s in a new mall by walking the length of it: data mining is like shopping in the data mall. What will we find when we look in each store?

Data mining sifts data back and forth until it finds natural breaking points, puts together associated characteristics and then lays out what it finds. For example:

“The donors who give the highest gift amounts are married male alumni. They’re in their 50s. They live along the east or west coast. They have a job and children that we know about.”

Data mining delves deeper to find relationships between many characteristics

The good news is that data mining also names the characteristics for the second best segment, and the third best, and so on, so a university could use it to find out various solutions to their attrition problem. The characteristics they see might look like these:

“The donors who stop donating tend to leave between their 5th and 6th years of consistently donating to the annual fund” So we can work harder to retain them before year 5!

“The donors who stop donating tend to be married alumni males in their thirties” What special incentives can we offer to that group since we know that married men in their 50s tend to be our largest donors later on?

Data mining can also be used for:

  • Determining the best solicitation methods for donor acquisition, renewal, or upgrade
  • Measuring the characteristics of event attendees who later become donors
  • Understanding the clusters of members/grateful patients/families/alumni/docents who respond better to e-mail, direct mail, phone calls, or social media
  • Finding the best pattern for the cultivation/giving ladder
  • Adding or dropping solicitation methods, or venues
  • Assessing timing, including how long it takes to successfully solicit gifts at different levels

What else can data mining do?

Have you ever walked into a store that has section after section of fun things for purchase? A department each of clever t-shirts, gifts that your best friend would love, beautiful hand-crafts, and more – things that are so perfect that you’ve picked up an armful of things and you need to find a basket to dump them all in.

Data mining is like that. It can also be for:

  • clustering like-minded, or like-attributed prospects for a cultivation dinner
  • breaking long-held “truths” about your donor base, such as “our best athletics prospects are male football alumni.” What if that’s not actually true?
  • looking at what statistics calls “interactions” – the combination of characteristics that make good prospects, members, volunteers, trustees, etc. For example: Married prospects and/or prospects living in rural areas show a mild relationship to loyal giving. However, prospects who are married AND live in rural areas show a strong relationship to loyal giving.
  • determining which group responds best to email and which to social media.

What do you want to know?

Our series continues next Thursday, September 12 when we will discuss Donor Modeling.

Do you have questions about data mining or would you like to see how it can work for your organization? Email us for more information at info [at] helenbrowngroup [dot] com.

 

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What if fundraisers reported to the Director of Strategic Information?

Are you hearing a lot of talk lately that fundraising is becoming more data-driven? That we need to show the return on investment of donor dollars? We’re all hearing this train coming down the track and it’s fueled by top volunteers who are used to seeing that kind of business intelligence in their company board meetings. In the past few years they’ve come to expect to see it when they sit at the nonprofit board table as well.

It’s good business, and it makes sense

We all want to cultivate prospects that have the highest likelihood to become donors. And we need to be careful with our most valuable resources – time and money. So it makes sense that business intelligence methods are edging into fundraising work as well. Ten years ago, we didn’t hear much about analytics in fundraising, but in the past five years more and more shops are hiring fundraising analysts – internally or outsourcing the activity to companies like mine.

Earlier this month, Forbes magazine published an article called “Does Your Organization Need a Chief Analytics Officer?” (link here). The article describes two very interesting case studies highlighting how Caesars Entertainment and KeyBank are using analytics to create stronger relationships with their customers and creating more revenue.

Ruben Sigala, the new CAO of Caesars:

“The data we collect is a treasure trove that enables us to treat every guest well, but treat every guest differently,” says Sigala. “And centralizing the function has enabled us to get a lot more creative about how to reward customers across properties and functions, and how to drive more revenue for Caesars.”

By substituting a few words, it’s easy to see how that could translate to fundraising, isn’t it?

At Cleveland-based KeyBank, one of the top 20 largest banks in the country, they’ve done something really interesting: the marketing team and the analytics team both report to the Chief Analytics Officer. What would that look like translated to fundraising? Major gifts officers would report to the Director of Strategic Information.

Will that happen in your shop? I’m sure the marketing folks at KeyBank wouldn’t have thought it possible 10 years ago.

Regardless, the big takeaway here is that fundraising analytics is here to stay. These tools are incredibly nimble and powerful and are having a tremendous impact on the organizations – large and small, for-profit and nonprofit – that are using it. And if you are unfamiliar with the terms or how data analytics can help you, stay tuned to this space.

Over the next few blog posts, HBG’s chief analytics consultant Marianne Pelletier and I will go over, in English, what analytics are and what these tools can do for you and your organization. If you have any questions at all, or are interested to see how we can help, don’t hesitate to be in touch.

First in the series, this Thursday we’ll discuss Data Mining.

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From Twit to Twitterer: the brief story of a reluctant user

A couple of years ago I was talking with an intelligent, interesting, down-to-earth marketing guy. (And no, that’s not an oxymoron). Although Mark’s got a career that you might expect would entail being smarmy or jumping on couches screaming words like “SEO!” and “market penetration!” he’s not like that at all. Even remotely.

So I got nervous when he started trying to convince me to join Twitter. I diverted and moved the conversation on. When Mark pressed, I finally told him I thought it was only for twits who talk about what they had for lunch. He said that, while there certainly was an element of that, not everyone on Twitter was like that. That there are a lot of influential people using Twitter in order to share important information – at immediate, lightning speed and that I would always have control over who I followed.

I’m a sucker for lightning speed information, and I trusted him not to lead me down a path that was a time-waster. So I gave it a try.

 

Fast-forward to today. I’m not a super power Twitter user by any means, but I do follow nearly a thousand interesting and informative people, nonprofits and companies. That may sound like a lot, but trust me, a thousand is actually manageable with good filtering. And people aren’t out there constantly tweeting all the time. (Well, most people aren’t, anyway).

And honestly, some of the best information that crosses my screen, whether it’s white papers, studies, or news about big gifts or innovative things that businesses or nonprofits are doing, comes from Twitter. Often I find that I get some news before other people have heard about it – because they aren’t where the breaking news is. Twitter gives me an edge because I find out about things that are being released by thought leaders as they happen. And I re-tweet the most valuable information that comes my way and use the information to inform my work.

Perhaps nicest of all is that I have met some of the smartest, most generous people on Twitter that I have gone on to meet in real life. And we can just pick up the conversation there as we do on Twitter.

So if you’ve ever considered signing up for Twitter, but decided not to bother, do give it a try. And no– it’s really never too late. Give it two weeks. If you’ve given it a real college try and you still think it’s not for you, just cancel the account. No harm, no foul.

To get you started

Mark Schaefer has written a short, very engaging guide to getting started on Twitter called The Tao of Twitter. The book has lots of case studies and examples for how you can get the most out of your Twitter experience. 

If you’re looking for people to follow, try picking and choosing from these lists (or just follow the lists wholesale!)

Prospect researchers: my list

Fundraising experts/consultants: from Beth Ann Locke

You can also look at the people on Twitter that you respect to see who they are following, and add those people.

Filtering tips

As with most research resources, filtering is important because Twitter is a constant barrage of information. One easy way to keep track of things is to use a dashboard like Hootsuite.

Set up is pretty easy and Hootsuite has even compiled a handy Quick Start Guide. You can get a free Twitter or Hootsuite app for your smart phone so you can read your feed while you’re waiting in line at Costco. And if you want to post from your smartphone, you can even do it via text message if you’re a texter.

Making a hash(tag) of it

Another way to filter to find the best information is by using hashtags, which are just key words with the prefix ‘#’ attached to them, as in

#prospectresearch

#nonprofits

#fundraising

So for example, when I post a tweet with information I think a prospect researcher will find useful, I will use the hashtag #prospectresearch to categorize that tweet. Someone later searching on that hashtag will find my tweet (whether they follow me on Twitter or not).

You can even use hashtags to join in on a live chat or follow what’s happening at a conference (such as #APRAprospect2013).

There are lots of hashtags out there. Two blog posts by the venerable Kivi Leroux Miller and Kerri Karvetski provide useful lists for nonprofiteers.

Are you a fundraiser or prospect researcher on Twitter? Which hashtags do you frequently use? Comment here, or send me a tweet! Let’s connect on Twitter!

Full disclosure: none of the companies or individuals mentioned above paid me to praise them. They’re just that awesome.

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Welcome, Kelly!

I’m delighted to welcome Kelly Labrecque as HBG’s newest employee. Kelly’s experience includes one of the most respected cancer care organizations in the world, the Dana Farber Cancer Institute, and Wheaton College, a traditionally all-women’s college and now a co-ed institution. Experience at two different types of nonprofit organization gives Kelly a great prospect research edge.

Kelly’s been with us for just a month, but already she has impressed me with her willingness to volunteer for special projects and her interest in providing a 360-degree view of prospective donors in her profiles.

She is an active member of the New England Development Research Association (NEDRA) and the Association of Professional Researchers for Advancement (APRA). Please join me in welcoming Kelly!

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Research Magic

I think it’s easy to get frustrated with assumptions that some front-line fundraisers have about prospect research. On the one hand, we researchers want people to see us as a resource. Indispensable. That we have (or can get) all the answers. Fast.

As a personality type, we tend to be diligent and dogged sorts of people – we generally can’t rest until we find the answer. We learn Boolean logic. We use databases that give us reliable answers. We get faster at it and we’re proud of our agility and reliability.

But that can foster an assumption that research profiles just appear (poof!) with the push of a button. Or that full profiles only take a couple of hours to do.

As a colleague at the APRA conference said two weeks ago, “Research profiles take two hours to do just like a major gift takes 18 months to get.”

They have no idea what we do all day…

A few months ago I did a training session – an introduction to prospect research – for a development team at a mid-sized nonprofit that had no researcher. I asked them to give me the name of one of their donors that they’d recently researched using the big search engine. They were feeling pretty confident that it had turned up everything there was to find about their Mr. Smith.

So first I used that search engine (and taught them about a couple of others) and we went through the results. Then I pulled out my research magic wand.

I admit, I just love the ooohs and the aaahs that always generates. Then I showed them a few other fee-based resources we use. Deep web, pay-wall, give-me-the-serious-411 kinds of resources.

“Wow, that’s a lot of information. It must take you forever to visit all these sites and pull together a profile on someone” said the director of major gifts.

…and we have no idea what they do.

But before we researchers start feeling too smug here, let me just say that we make a lot of assumptions, too, about what fundraisers do all day. The good ones make it look easy – but it’s a lot of hard work and it takes longer than we think.

So here’s my proposal: The next time your development office does a brown bag lunch together, show each other what you do. Just a half-hour each. Talk about how much time each thing that you do takes and what your greatest joys and frustrations are.

Honestly, it’ll just be…magic!

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The true test of research

Changed priorities ahead EDIT

“The true test of research is whether people use it – for reference, for influence, and most importantly, for change.” *

 

We all want our work to mean something, don’t we? It just kills us when research (or screenings, or any information, really) just sits on a shelf unread. Unused. All that work – all that potential – just…going nowhere.

In order for it to be a force for change, our research has to grab hold of people and inspire them to take action with it. How do you do that?

Is your research being used?

How do you know for sure? Have you talked with your end users in the past 6 months? Are reports being delivered in a format that is helpful or would a different deliverable be better (fit for iPad, or in a podcast?). Do they contain the right amount of information? The right information? If so, have you shared your success stories with peers in the profession? What’s business-as-usual for one could be innovation to another.

Is your research creating change?

How do you know for sure? Are you measuring its impact? Maybe it’s making more of a difference than you think. Or maybe by tweaking your resources, your training, or your delivery methods a little bit you can deliver significant improvement. What metrics can you use to track and discover your success and gaps?

Your research and the critical information it delivers can create change.

How do you want to be part of that change?

*DFID website, several months ago. Sadly the quote is no longer there but they’ve got other great ones, as well as really interesting research studies.

 

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More than just prospect research

Next month, members of the Association of Professional Researchers for Advancement (APRA) will gather in Baltimore, MD for the association’s annual conference. If you know someone who is thinking about a career in prospect research or are a supervisor with a staff member who needs training, this really is the conference for them to attend. Topics will range from basics training for new researchers to in-depth training on fundraising analytics and everything in between.

Throughout the rest of the year, many APRA chapters offer excellent continuing education, including networking events, brown bags, and conferences. Both APRA and many of its chapters also have monthly or quarterly newsletters as well.

BUT…in addition to APRA, there are a variety of allied professional associations that are highly relevant to prospect research, and reading their newsletters and blogs, and following the associations or members on social media can be a great way to enhance a researcher’s knowledge. They include:

  • the Association of Advancement Service Professionals (AASP)
  • the Association of Independent Information Professionals (AIIP)
  • Strategic and Competitive Intelligence Professionals (SCIP)
  • Special Libraries Association (SLA) – Information Outlook, their association’s bi-monthly newsletter is available free at their website.

Finally, besides the newspapers and magazines that we may subscribe to keep up on business and industries there are also several journals, websites and blogs that provide insight about the craft of information discovery and searching. They include:

 

What resources do you follow to stay up on the craft of research? Share!!

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