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We all know how much nonprofits rely on fundraising to support their missions. Building relationships with your existing donors is important to facilitate long-term support and loyalty to your cause, but if you want to grow as an organization, you also need to grow your donor base over time.
This will increase your fundraising opportunities, diversify your donor base, and help spread awareness of your mission, all of which are critical to growing your nonprofit.
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As your organization grows and changes, the same old donor acquisition techniques won’t have the same benefit they once did. To reach and convert new donors, you need to try new strategies and evaluate the progress of your efforts.
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At DonorSearch, we enable nonprofits to get the most out of their data—and maintaining a good donor acquisition program includes leveraging your donor analytics. Specific strategies and the infrastructure to analyze the effectiveness of those strategies will be critical to increasing your reach and attracting more donors. If you want to expand your donor base, we recommend that you:
If you want to stay on top of donor acquisition, you need to use a combination of targeting, leveraging data and effective marketing. Let’s dive in!
Donor personas are fictional representations of your target audience – they can help your team understand who they are targeting with their support activities. After all, it’s important to understand what kind of people have contributed to your organization in the past.
To develop these personas, you need to analyze the information in your donor database. As Salsa’s guide to database software points out, your donor database should be able to store a variety of basic information about your current donors. If you want to create donor personas, you should look at a few factors:
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The demographics of your donors can be valuable guides to donor acquisition. Which groups tend to regularly donate, volunteer, or do peer-to-peer fundraising for your organization? You will look at:
You may notice a trend that most of your donors are highly educated, live in suburban areas, or reach a certain income level. Once you have this information, you can specifically target these groups to become advocates for your organization.
As strange as it may sound, understanding the mindset of your donors can provide insight into how and why your cause resonates with them. This can tell you who your thing is most likely to resonate with. After you have some preliminary donor personas at work, reach out to some of your donors who seem like a good fit and ask them for an interview. You want to know about their:
Knowing these data points about your donors can inform your future messaging strategy and help you appeal to your target audience’s attitudes.
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Combined with demographic and psychographic information, the history of donors’ engagement with your organization will be helpful in creating accurate donor personas. This category focuses on the type of supporters your donors are and how they have responded to various outreaches in the past. For example, you will explore:
When you integrate all of this information, some major donor types should emerge to help you create your personas. Once you’ve generated your personas, all you need to do is give them names and images and discuss them with your fundraising team. They will be good guides for your donor outreach efforts.
“Getting more donors” isn’t exactly an achievable goal for your nonprofit. To work effectively towards a goal, your goals must be well defined. Your fundraising goals should follow the SMART template:
By setting appropriate and measurable goals, you will ensure that your organization’s team always knows what they are working towards and that success is much more likely!
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If your new donor acquisition rate is lagging, it may be time to expand your marketing efforts to reach a wider audience. If you’re only using your marketing budget for one channel, remember the adage “Don’t put all your eggs in one basket” and consider diversifying. Consider implementing one of these strategies:
When it comes to acquiring new donors, making sure your marketing materials get in front of a large and diverse audience is key.
As your team implements new donor acquisition strategies and campaigns, keep the “M” in your SMART goal in mind: measurable. Your donor database software should be able to measure the effectiveness of your efforts by analyzing your data for key metrics.
Look for database software with robust deep data analysis capabilities and intuitive reporting capabilities to gain insight from the numbers generated.
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These are just some of the possible KPIs we recommend in our donor search guide to calculations for nonprofit fundraising. But don’t feel like your organization has to keep track
By them. Instead, track the KPIs your nonprofit needs to know based on your specific goals to keep your team focused.
As your nonprofit grows, it’s important to consider the value of expanding your donor base. Welcoming new donors to your organization will help you secure the funds needed to achieve increasingly ambitious goals for your mission. So make sure you set specific goals, change your outreach efforts to a broader audience, and consider using donor personas to improve your target audience communication strategies.
When it’s all over, don’t forget to analyze the results of your efforts so you can make better decisions in the future. Good luck! Data governance is the process of managing the availability, usability, integrity and security of a company’s data. Click here to learn more.
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Data governance is defined as a set of data management processes and procedures that help an organization manage its internal and external data flows. It aligns people, processes and technology to help them understand data and transform it into a business asset. This article covers the definition of data governance, its importance in a post-Covid19 world, and data governance best practices for 2021.
Data governance is a set of data management processes and practices that help an organization manage its internal and external data flows. It aligns people, processes and technology to help them understand data and transform it into a business asset.
Data governance is the process of managing the availability, usability, integrity and security of corporate data based on internal data standards, guidelines and rules. Effective data management ensures that data is consistent, understandable, correct, complete, reliable, secure and searchable.
Data management covers various topics such as data architecture, data modelling, data storage and operation, data security, data interpretation and interoperability, document and content, reference and master data, data warehouse and business intelligence, metadata and data quality.
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Data processing programs affect strategic, tactical and operational levels in businesses. Therefore, to effectively organize and use data in the context of the business and in coordination with other data projects, data management programs must be considered a continuous and iterative process.
Computing is the foundation of all computing programs. It provides the framework, workflows, and decision-making authority to properly manage an organization’s data. Computing has ten key components that exist to meet the enterprise data management requirements of each knowledge area. Let’s look at each of these components in detail.
Computing professionals, data administrators, and other key business and IT personnel are the backbone of a computing program. They establish and develop workflows to ensure that the company’s data management requirements are met.
The data governance team plays a key role in developing and implementing an organization’s enterprise data strategy. A data strategy is a powerful document that provides high-level requirements for business data and ensures that these requirements are met. Building an enterprise data strategy is an important step in an organization’s data management journey.
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Data management programs must establish key data management processes. These include data tracing or debugging, data quality monitoring, data sharing, data lineage tracing, impact analysis, data quality testing and many more.
A data policy is a high-level set of one or more statements that outline expectations and expected data outcomes that influence and guide enterprise-level data practices. Data management programs establish data management policies for data handling. Policies include outbound data sharing, compliance and much more.
A data standard provides a framework and approach to ensure compliance with data policy. An example of a data standard would be the use of ISO 3166 to define codes for names of countries, dependent territories, areas of special geographical interest and their main subdivisions.
A data rule controls or restricts behavior to ensure compliance with data standards, which ensures compliance with data policies. An example of a data rule might be an organization that only allows country codes listed in ISO 3166. Typically, organizations will try to create data rules for master and reference data, data definitions and domain development, metadata management, classification, accessibility, and many others.
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Data security involves protecting digital data, for example data in a database, against destructive forces and unwanted actions by authorized and unauthorized users. These unwanted user activities refer to espionage, cyber attacks or data breaches.
Data management communications include
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