Efficient! Effective! Exceed!

Donor Database Management for Nonprofits

Nonprofits exist to fill a critical need in society. However, in order for nonprofits to be effective, they must have the resources to make a difference. One of the most important resources to a nonprofit is money. Nonprofits generate funds from the local and national community. Nonprofits are expected to maintain accurate records of all donations received – whether fro individuals, corporations, or foundations. Nonprofits should have historical data that dates back to its earliest years in addition to current data with donors’ most recent contact information and giving history. In the digital age, keeping this information strictly in file cabinets is ineffective and inefficient.

To be the most effective and responsive to donors and in order to maintain accuracy, nonprofits need to move to a digital database. Exceed! Premier is one such database that allows not only for the aforementioned tasks to take place, but so much more. It allows pledge tracking, email integration, and report extraction. Exceed! Premier is a nonprofit’s dream come true and solution to so many donor relation issues. As the name hints, if a nonprofit desires to be the premier organization, it needs to obtain Exceed!

 Learn more and purchase Exceed! Premier today. 

Maximizing Giving through Technology

Maximizing Giving Through Technology

         The foundation of raising funds is building relationships, communicating a message, and effectively meeting a community need. Successful fundraisers know they must build rapport with potential and current donors, a task that is usually accomplished through one-on-one communication such as facility tours, lunches, phone calls, and direct mail pieces. Today, another crucial component of fundraising is a nonprofit’s digital presence and capabilities to accept donations through technology. In 96 pages, fundraising guru Richard C. McPherson tackles Digital Giving: How Technology is Changing Charity (ISBN: 978-0-595-44255-3). Written in 2007 and published by iUniverse, Digital Giving  explores the impact technology has on charitable giving.

            The purpose of Digital Giving is to education nonprofit organizations and their leaders on the power of using technology to engage donors and further the mission of the organization. The book is directed toward nonprofit organizations, however the information within it is relevant to anyone who wishes to make an impact in their community. Filled with interviews of nonprofit leaders who’ve successfully incorporated technology as a means to connect with donors and for donors to connect with them, Digital Giving provides a wide breadth of knowledge and perspective. It takes readers on a journey that discusses Web 2.O, blogging, Google, social networks, corporate philanthropy, navigating websites, giving through cell phones, and merging online communication with traditional paper or postal mail. In keeping with the purpose and topics discussed, the theme of Digital Giving is to discuss and “remove obstacles” for readers to understand “big technology trends affecting charity, and how organizations embrace them to increase public support” (vii).

            In one example, McPherson talks about the positive results of merging a digital email campaign with a traditional direct mail campaign. According to a study, “email produces more-informed donors who give generally larger contributions on average than those who do not receive e-mail” (76). And, the most effective emails are those that are received following a direct mail campaign. Today, just sending mail is not effective, but neither is just sending an email, especially given the vast amount of spam mail individuals receive. Combining the e-mail with a social network experience, that allows donors to create and respond to content (35).

            With the rapidly changing scope of technology, much of Digital Giving’s content is basic in today’s world, although it was most likely revolutionary when it was published seven years ago.  It’s accuracy and objectiveness and frequent reference of successful engagement of technology to raise funds makes it a very relevant book for nonprofits and for this course. However, due to the outdated content, a second volume of this book that references today’s technology trends and future trends, would be even more useful. For instance, McPherson spends much time referencing MySpace, and barely mentions Facebook, which is the leading social networking site for today. Although the tool he references is no longer relevant, the information he provides about social network engagement is. For instance, he says that “technology does best when it is integrated into the continuing relationship between an organization and its supporters, and when it fits donors’ lifestyles (63). The key to technology is that it’s not to create a challenge for donors, but to create an easy way for donors to find out more about an organization while they are engaged in routine, common tasks. For instance, having a delightful photo appear in an individuals’ Facebook newsfeed helps potential and current donors click on it and learn more about the nonprofit while doing a regular task – checking status updates of their friends. One of the most obvious ways this book relates to the course textbook Information: A Very Short Introduction  is that the cover features  a picture of Ben Franklin imposed with binary data. Binary data, as discussed in the Information book, is how computers code information. Furthermore, Information discusses the ecological impact of technology, which is also addressed by Digital Giving as it compares and contrasts traditional forms of communication and its cost and environmental impact verses digital communication.

            Despite the assertion that content in this book is basic, it is not widely implemented across the nonprofit sector. McPherson asserts this is because nonprofits often have departmental silos where the person implementing technology is not also the person involved in donor relations (77). This explains why several nonprofits, including the one for which I work have combined the responsibilities of the fund development and communications director. Furthermore, McPherson mentions that many nonprofits retroactively use web tools and do not make them a main practice. Often, nonprofits run “tests” of the effectiveness of technology but don’t put the effort into creating success, resulting in low results of tech use among donors. Nonprofits must begin dedicating time and having a dedicated person to technology as a donor engagement tool.  

In the book, McPherson asserts that “cell phones will very soon replace other things you carry for getting information and making transactions” (65). This relates to nonprofits because nonprofit websites need to have the capability to have websites that are phone-friendly. With the onset of smart, internet-capable phones, websites initially had mobile-friendly websites, generally proceeded by the lowercase letter “m” before the rest of their website name. Now, instead of having mobile-friendly websites, many websites have a distinct, mobile version designed for easy navigation on phones. Plus, text-to-give campaigns have become wildly popular, especially when raising support for national disasters.

            Technology is helping nonprofits become more efficient, especially as it relates to communicating to donors and garnering support. Technology allows nonprofits to not only reach people in their direct community, but also to promote their cause and raise support worldwide. Technology is changing the landscape for the better, as it allows donors to give instantly and learn even more about their nonprofit of choice. The key to successfully incorporating technology into fundraising campaigns can be summarized by the words McPherson uses to close the book, “make the most of [technology] for your cause” (96). Technology helps nonprofits communicate their message, share success stories, and garner support in an engaging, cost-effective manner. Technology provides a powerful opportunity for nonprofits to further their reach, enhance engagement, and diversify funding support.

Connected by Climate

Connected by Climate

                  In A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming¹, Paul Edwards tackles the topic of global knowledge using the climate as his example. He begins by using the common phrase, “think globally, act locally” (Edwards 1). By this, Edwards means that our local actions impact the world and what’s happening around the world impacts us locally, in other words we are an “interconnected whole” (1).  To provide an example, Edward uses climate to address the complex task of identifying and sharing knowledge. It is fitting that he chooses “climate” to talk about people being connected since, according to the Oxford Dictionary Online¹, climate’s suffix “mate” can be defined as a as a noun that means, “a fellow member or joint occupant of a specified thing” and as a verb that means, “connect or be connected mechanically.”  Furthermore, as Edwards says toward the end of the first chapter, the weather data network “is arguably the oldest of all systems for producing globalist information” (Edwards 24). Climate is a great example to use because its suffix not only means connection, but the study of it is one of the first world-wide attempts to form unified knowledge.

            As Edwards discusses, knowledge formation does not begin with communicating information. Knowledge begins with assembling data, which includes knowing how to identify data and also having tools to accurately capture and assess that data. In the case of climate, each country uses different measurements, the tools they use change over time, and even where the data is connected changes. All this results in differences from data collected 150 years ago and even data collected 20 years ago (6).  This is where the concept of a “vast machine” is introduced. A vast machine is “a sociotechnical system that collects data, models physical processes, tests theories, and ultimately generates a widely shared understanding” (8).  Data and observations must be transformed into widely accepted knowledge which includes the political process, transmission of information via the media, and even an understanding of what counts as data.

                  Since we’ve mentioned that data varies, it is important to have “reanalysis,” which is a technique that helps standardize data previously collected, even when collected at different times by different methods. There is also the concept of “gateways” which “can join previously incompatible systems” (10). In the case of climate, this allows weather systems to interact with the ocean monitoring systems, seismographs, and more.  “Knowledge infrastructures comprise robust networks of people, artifacts, and institutions that generate, share, and maintain specific knowledge about the human and natural worlds” (17).  These knowledge infrastructures are sociotechnical because people don’t just add facts. They must assimilate the facts they have, which is akin to the basics of scientific knowledge. To do so, the information presented must be consistent with other things people know. Plus, the new information must be accepted within a community and the person providing the information must have trust and authority. Scientific knowledge is therefore communicated through many infrastructures and institutions including universities, libraries, and laboratories.  “The infrastructure is a production, communication, storage and maintenance web with both social and technical dimensions” (18). Infrastructures are largely invisible until they no longer work. For instance, one may not pay attention to the infrastructure of roads, highways, and traffic lights until the traffic lights don’t work and as a result, traffic no longer flows smoothly and the number of accidents increase.

            Globalist information occurs when the knowledge transcends into a political contect and nations begin working together to create change. “It may be driven by believes about what knowledge can offer to science or society” (25) and creates a world-wide infrastructure of knowledge formation and transmission. With countless examples related to climate, capturing and analyzing climate data, and organizations that study climate, A Vast Machine explains how knowledge is formed and how it is then communicated, not just locally, but globally, influencing people everywhere.

²Oxford Dictionary. Oxford University Press. Accessed at http://www.oxforddictionaries.com/definition/english/mate

¹Edwards, Paul. A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming. MIT Press: 2010.

Simon Says and Computers: Information is not Intelligence

Simon Says and Computers: Information is not Intelligence

Computers can only do what you tell them, making computers akin to participants in the popular children’s game “Simon Says.” In the children’s game, one person plays the role of Simon and commands participants to perform certain actions beginning with the phrase, “Simon Says.” Participants can only do what Simon commands. Similarly, with computers, the programmer is “Simon” and a computer’s response is limited to its understanding of what it is being instructed to do. Computers are not able to act outside of this realm, so the commands (programming) initially received are critical to computers output, functionality, and effectiveness.

In “The Stupidity of Computers,” David Auerbach¹  explores the intelligence of computers. Filled with numerous examples, this article takes readers on a journey of computer output. It begins by discussing how programmers input information so that a computer can understand and respond to queries. It then evolves into conversations about search engines, language and ontology, and popular information-generating and information-gathering websites. Finally, it concludes with greater implications of how computers impact government, social structure, and individuals’ identification and categorization of themselves and others. Ultimately, this article sheds light on the limitations of computer intelligence and the growing dominance of computer intelligence on human life.

Through a series of examples, Auerbach explains the growth of computer intelligence. For instance, a simple sentence such as “Highlight Japan on a map” requires a set of commands that could be as long as a paragraph. The computer can respond to this request only if the programmer properly input the necessary commands and also provided a map and a highlight feature.  Computer instructions must be precise and language matters. Ambiguous language brings about confusion and in searches, can bring about undesired result.  Initial search engines could only search for what an individual input and could not extract similar information. For instance, if an individual did a search for “outdoor parks in Alabama,” original search engines would only be able to generate search results that contained the four words in the original search. The search results would not generate responses that referenced “Ruffner Mountain in Birmingham” because this last phrase does not include any of the key words although Ruffner Mountain is an outdoor park in Alabama. This example shows that computers can only respond to the information given them, whereas a human would be able to respond with Ruffner Mountain if they were asked about outdoor parks. This inability to interpret or extrapolate answers challenged the effectiveness of internet searches, a problem that was solved by the search engine Google.

Eventually, Google found a solution by “using the topology of the web as opposed to its meaning.” Google began paying attention to which pages were linked together – in other words, they must have a connection to one another.  This helped provide more relevant results. That way, if someone types in “outdoor parks in Alabama,” anything that classifies itself as such would pop up. In addition, an individual might even see advertisements for products relevant to being in the outdoors such as an ad for Mountain High Outfitters, a store that provides outdoor gear. Today, Google not only provides more relevant results, but it will also try to “predict” what you are searching for by creating a drop down menu of choices as you input letters and words in the search bar. For instance, by simply typing the letter “a” in my Google search bar, the following pop up “Amazon, Alabama power, AOL, and Alagasco.” When I type in the entire word I’m looking for “Atlanta,” Google populates the dropdown menu with “Atlanta Braves, Atlanta, Atlanta Airport, and Atlanta Braves Schedule.” These are the most popular searches individuals are currently looking for when they type “Atlanta” into Google.  Google is able to return desirable responses because of how its programmers have set it up to recognize information and its relationship to other information and also because of metadata categorization. Individuals can aid how online information is categorized and the frequency in which it is returned in search results by providing “key words” that are often used in searches. On Twitter, the key words are proceeded by a hash tag symbol.

The latter half of the essay focuses on the importance of ontology, or assigning recognizable categories to metadata. This results in comparing and contrasting the effectiveness of several popular internet giants such as Ask (formerly Ask Jeeves), Yahoo, Wikipedia, Amazon, Facebook, Twitter, and more. Due to the massive amount of information online, the web is faced with the challenge of categorizing information. Amazon successfully does this by categorizing information in well-accepted categories such as “books, household appliances, toys.” Facebook successfully does this by having individuals select the categories to which they belong – people can input their religious group, college, favorite bands, favorite TV shows, favorite politicians, and more. These categories or ontology used by Amazon and Facebook create methods in which to group and analyze people. Auerbach cautions that these categories are limited to human’s determination of categories and that computers cannot automatically generate the categories.  Auerbach also cautions that the government and other places are making connections and conclusions between what people have liked. However, “the sheer number of uncontrolled variables at work makes it dangerous to take any of these conclusions at face value.” 

Other internet-based examples of the role internet has in shaping how we receive information include blogs, LinkedIn and Ning. LinkedIn.com uses the slogan, “World’s Largest Professional Network” and is essentially a place for individuals to house their professional and academic accomplishments online. People can link/connect/network with other individuals by searching individuals by profession, college, geographic location, skills and more. In an attempt to help individuals find other individuals relevant to them, LinkedIn also features “individuals who looked at this profile also looked at” and provides a list of other individuals frequently searched for tangentially with the person currently on their screen. Ning.com has the slogan “build and cultivate your own community.” Unlike the other social media websites that connect people who have mutual connections, Ning.com connections are limited to those within that particular Ning group. On Ning, one would be a part of multiple Ning groups that don’t intersect, which is unlike other social media. The information contained on these websites and other websites are being used to create categories, correlations, and connections of people and items that would otherwise not be connected.

Although this article does not go in-depth into any one subject that it mentions, it provides a comprehensive overview of the limitations and implications of computers continual integration in society.  The greater implications of this article are that computers and the internet are only as smart as the information and algorithms initially input into them. Computers and the internet are not able to think for themselves and are therefore just an advanced version of the children’s game Simon Says. Computers can only do what they are told although they are very good at responding and providing information, as long as they have access to the information requested. Information should not be confused with the higher calling of intelligence. Computers can help humans synthesize and analyze information. Computers cannot replace or create human intelligence. 

 

 

¹ Auerbach, David. “The Stupidity of Computers.” Machine Politics: Issue 13, Winter 2012. https://nplusonemag.com/issue-13/essays/stupidity-of-computers/.