For most advancement shops, annual giving is the black hole of fundraising: a generic ask to a mass audience. But what if you could deliver a meaningful, personalized experience for all of your donors—without increasing the resources needed or time and energy spent?
In this whitepaper, you’ll learn how to segment your constituents to personalize your annual fund outreach in an efficient, scalable way.
Featuring original research from Greta Daniels, Director of Development at the University of Pittsburgh School of Health and Rehabilitation Sciences, the whitepaper will cover:
- Why segmentation needs to be part of your playbook in the noisy charitable marketplace of today
- How to gather the right data, create donor segments, and test their effectiveness
- Three case studies of segmentation in action at nonprofit and for-profit organizations
Get it all for free by filling out the form on the following webpage:
There’s no question that customer experience (CX) is a data-driven discipline. After all, at the foundation of most CX programs are close-ended surveys designed to capture and analyze customer feedback.
Yes, metrics are a crucial element of every successful CX program. With metrics, you can establish a clear performance baseline and track trends based on actions you take over time.
But how do you know in advance if the actions you take will be the right ones? Wouldn’t it be great to have a crystal ball that lets you know exactly what to do to have the biggest impact on your anchor metrics?
Here’s some good news: You don’t need to have psychic powers to excel at CX. Instead, you need to use predictive analytics to clarify expected returns before you take every step—and to ensure you have clean data to power your CX metrics program. Only then can you take meaningful action based on your customer data.
In this blog, Richard Boehmcke shares how predictive analytics can benefit your business and therefore fundraising successes.
Big Data is not just the ability to store large amounts of data, more important is what we can do to the data in that large volume, how we use the data with such large volumes.
One of its uses is for data analysis needs. Big Data Analysis can be done in order to assist the decision making process (Decision Support) and strategy (Strategic Business) of an organization, business institution, or company.
Jeefri A. Moka explains more below.
Traditionally, enterprises have focused their data strategies around business intelligence (BI), but the rise of predictive and prescriptive analytics platforms, in part thanks to machine learning and artificial intelligence, is changing the equation. Even business intelligence itself is evolving, tipping in capabilities previously exclusive to business analytics platforms.
Analysts and consultants agree that understanding the distinctions between business intelligence and other analytics platforms, as well as the value each brings to the enterprise, matters significantly in getting your data strategy right.
Read the blog by Mary Pratt below on how business analytics is evolving.
Utilising data to make better business decisions is on the agenda for the majority of organisations, with almost three-quarters (74%) saying they want to be “data-driven,” according to a study by Forrester. However, data is only valuable if it transpires into meaningful actions – only 29% of organisations said their data efforts have led to actionable insights.
While there are many platforms out there that offer inbuilt analytics and insights, more often than not you’ll end up with a hefty amount of data – very little of which you can actually put to good use. To measure your data, analyse it and produce worthwhile, data-driven actions, you’ll need a team of experts to take the reins.
Generally speaking, there are three functions that fit under the data umbrella; collecting data, analysing it and producing actionable insights.
This blog by Noa Muratsubaki explains the differences between these three functions.
Five key figures in fundraising tech reflect on how technology has changed fundraising and what’s next. With contributions from Mike Gianoni (President and CEO, Blackbaud), Bill Strathmann (CEO, Network for Good), Mike Geiger, M.B.A., C.P.A. (President and CEO, Association of Fundraising Professionals), Steve Spinner (CEO, RevUp Software) and Jean-Paul Guilbault (President and CEO, Community Brands).
It’s important to be aware of data protection legislation across the globe so that non-profits are familiar with requirements. If nothing else, these requirements tend to become the norm and therefore shape the expectations of your donors and supporters.
The CCPA applies to “businesses.” The Act defines that term to include any legal entity (e.g., corporations, associations, partnerships, etc.) that is “organized or operated for the profit or financial benefit of its shareholders or other owners.”1 This accords with the fact that non-profits are exempt from many of the data privacy and security regulations within the United States – in particular, they are largely exempt from enforcement by the Federal Trade Commission, and, therefore, are exempt from compliance with the rules, regulations, and guidance of the Federal Trade Commission to the extent that such rules, regulations, or guidance are not incorporated in state laws that do apply to the non-profit.
In comparison, the European GDPR does not contain any exemptions for non-profit organizations.
So, unless your non-profit has a commercial branch or deals in selling data lists, CCPA does not apply. GDPR, however, does – if you are dealing with citizens of the European Union.
The California Consumer Protection Act requires businesses and charities to make disclosures in their public-facing privacy policies and to update annually such disclosures, starting January 1, 2020.
The California Consumer Privacy Act will effectively be the US national data privacy standard for consumer business and brands when it takes effect on January 1, 2020. (Although enforcement by the California attorney general has been delayed until June 2020, individual and class-action law suits may begin immediately.)
As of this writing, that’s precisely 12 weeks, or no more than 55 working days, allowing for the holidays. Given how many companies were radically unprepared for the GDPR given two years for preparation, this implies that lots of companies need to do lots of work lots of fast.
There are three interrelated and inescapable reasons why CCPA-compliant data practices will quickly become the standard across the US, even for companies that don’t do business in California. Here, Tim Walters, Ph.D. explains more.
The California Consumer Privacy Act could have more repercussions on U.S. companies than the European Union’s General Data Protection Regulation (GDPR) that went into effect in 2018. The California law doesn’t have some of GDPR’s most onerous requirements, such as the narrow 72-hour window in which a company must report a breach. In other respects, however, it goes even farther.
The California Consumer Privacy Act (CCPA) takes a broader view than the GDPR of what constitutes private data. The challenge for security, then, is to locate and secure that private data.
CSO, which serves enterprise security decision-makers and users with the critical information they need to stay ahead of evolving threats and defend against criminal cyberattacks, shares an excellent guide on what CCPA means to you.
On January 1 2020, a landmark new data law comes into effect, subjecting U.S. businesses to a sea change of privacy regulations. After that date, Americans will be able to demand that charities disclose what personal data they have collected about them, and also ask them to delete that data. The California Consumer Protection Act (CCPA) will severely impact tech giants like Google and Facebook, as well as retailers like Macy’s and Walmart.
This heralds the end of an era in which the U.S. defied a shift in global privacy norms, and allowed American companies to commodify consumer data.
There remains, however, considerable confusion over how the law will be enforced, and how much of a burden it will be to U.S. companies. What follows is Forbes’ plain English explanation of the law, the politics surrounding it, and how it will affect businesses and consumers.
Fundraising charities rely on information about their supporters to survive; such as names and addresses, financial information and other private data. Information such as this will always be integral to the fundraising process, and the storage and safety of this information will be too.
GDPR’s rules around proving consent necessitate new processes at the back and front ends of data collection – and it’s going to be hard work. The fundraising sector has a lot of fundamental changes to make in a short amount of time.
Jenny Daw, editor of The Fundraiser, wonders that with so much to learn and do, there may well be a need for organisations to take on new talent and skills to push these changes through.
Ivan Wainewright acknowledges that buying a new CRM system or fundraising database is a daunting challenge for most charities and not-for-profit organisations, so he has written this book to feature issues that smaller not-for-profit organisations need to consider and be aware of.
This free book has been written for people whose day job is not the procurement or implementation of new databases, so it’s extremely helpful for any fundraiser thinking about stepping outside of their comfort zone.
At the end of 2016, when the ICO fined several charities for breaching the Data Protection Act 1998, Ian MacQuillin, wrote a fascinating philosophical piece on how charities are perceived by different types of people.
Even though this feels like a long time ago, it’s still as relevant today as it was back then. Whenever you feel that GDPR and data protection are not your friend, have a read of this.
The Guidance prepared by the Data Protection Network is a practical tool aimed at helping commercial and not-for-profit organisations to assess whether or not they can rely on Legitimate Interests as a lawful basis for processing personal data under the GDPR.
The Guidance covers:
- Understanding what Legitimate Interests are
- Identifying areas of processing where Legitimate Interests may apply
- The Legitimate Interests Assessment (LIA) – the 3 stage test
- Transparency and the consumer
Adrian Beney is back with an update on CASE’s work on providing guidance for charities for adopting GDPR best practise.
This document lays out in detail and with great clarity the circumstances under which these activities, regarded in recent years by some at the Information Commissioner’s Office as very controversial, can be carried out lawfully.
Follow the link below for full details.
Data governance is needed to ensure your organisation can consume data which has integrity and quality.
But how do you focus your efforts so that your governance programme can deliver the results needed?
Toochukwu Philip Ibegbu MBA shares with us how he was able to successfully launch data governance initiatives that made the most impact.
Reinier Spruit discusses how we’re in the relationship building business and how we need to measure and register every response.
Ironically, we must quantify the relations with our donors, so we can improve the quality of the contact we have with them.
There are a ton of metrics we can track, and should track, like email open rates, sign-up rates per hour, one-off cash donations and appeal response rates. But there are 5 that are simply much more important. Mainly because they are the building blocks for making sensible decisions for the longer term.
I call them the Big Five. The Big Five are Volume, Expenditure, Income, Retention and Return on Investment.
Find out more by clicking the link below:
In this technical blog, Suresh Kumar Gorakala explains how to turn written comments into descriptive sentiment. This is extremely helpful when trying to categorise, segment and understand your audiences better.
This example focuses on Twitter comments, but this technique can be applied to any text field, including telephone call notes and emails.
Manually creating reports using Excel can be overwhelming to meet the organisational expectations for quality, insights, and velocity.
Many business intelligence tools exist: Tableau, Microsoft Power BI, Looker, Amazon QuickSight, Google Data Studio. However, moving from Excel to one of these tools can be more difficult than anticipated.
This blog by Thomas Spicer provides tips to help you create a methodology and a process that will help you find success with your new tool as you transition from Excel to a new analytics model.