Long Read: Good asking

The Institute of Fundraising (IoF) recently launched Good Asking – a report on why charities research and process supporter information. They worked with leading academic Dr Beth Breeze from the University of Kent, to survey over 300 fundraisers to understand why they process and research information about their supporters, and what the benefits are for donors, charities and the wider public.

The purpose of this report is to shed light on the importance of fundraisers and their work. If they are to be successful, fundraisers need to conduct research to facilitate the efficient and accurate matching of donors and the causes they might wish to support, and to do so in a way that makes the experience as pleasurable as possible for the generous donor.

THE REPORT FINDINGS INCLUDE:

  • 90% of fundraisers believe that conducting research enables fundraisers to better communicate and tailor their work to the interests and priorities of donors
  • Most (88%) fundraisers believe that conducting research reduces the levels of unwanted or irrelevant mail sent out
  • A representative survey of the general UK population found that almost two-thirds (60%) of those who prefer charities to communicate in a tailored way with them, think that charities should be able to use information that is publicly available, for example doing Google searches or drawing on newspaper articles, in order to tailor their approach to their supporters.

The report also highlights that:

  • Two-thirds of major donors believe that a ‘more professional approach’ by fundraisers has been a key factor in the development of philanthropy in the UK

https://www.institute-of-fundraising.org.uk/library/good-asking-report-2017/

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At last, clarity and sense about wealth screening, prospect research and updating addresses

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.

https://www.linkedin.com/pulse/last-clarity-sense-wealth-screening-prospect-research-adrian-beney

Data Governance: 3 Key areas to focus your efforts

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.

https://www.linkedin.com/pulse/data-governance-3-key-areas-focus-your-efforts-philip-ibegbu/

How to Make Better Decisions with Less Data

Are you drowning in analysis paralysis? Having data to back up your decision making is good, but sometimes there is just too much!

Sometimes people often struggle to convert data into effective solutions to problems. The problem isn’t lack of data; the vast amount of data means managers struggle to prioritise what’s important. In the end, they end up applying arbitrary data toward new problems, reaching a subpar solution.

Here, Tanya Menon and Leigh Thompson discuss how you can make better decisions with less data.

https://hbr.org/2016/11/how-to-make-better-decisions-with-less-data

The BIG 5 in fundraising performance metrics

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:

https://101fundraising.org/2014/05/big-5-fundraising-performance-metrics/

Learn Everything about Sentiment Analysis using R

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.

http://www.dataperspective.info/2013/08/sentiment-analysis-using-r.html?m=1

How to Transition From Excel Reports to Business Intelligence Tools

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.

https://dzone.com/articles/5-steps-to-making-a-transition-from-excel-reports

A simple predictive score you can probably build in Excel

Many smaller fundraising and non-profit teams can’t make the investment to fully utilise analytics.

In this blog, the great Peter Wylie uses data from two schools to demonstrate how to build a very simple predictive score using nothing but Excel.

https://cooldata.wordpress.com/2016/07/05/a-simple-score-you-can-probably-build-in-excel/

The 4 Types Of Data Analytics

So, data analytics can help us to predict the future and find loads of people who will donate to our cause? Well, yes and no. But it’s a bit of a journey.

In this article, Thomas Maydon explains the four different types of data analytics:

  • Descriptive
  • Diagnostic
  • Predictive
  • Prescriptive

Follow the link below for more:

https://insights.principa.co.za/4-types-of-data-analytics-descriptive-diagnostic-predictive-prescriptive