“What do you need, and if you don’t have what you need, how can you get there?”
Artificial intelligence is driving change across all aspects of our lives, it’s been all the buzz long before the emergence of GPT.
Though, the idea of using ‘AI’-driven tools in our jobs as fundraisers still sounds a bit daunting. You may think that it’s too technically complex for most not-for-profits to implement, but actually, it’s not at all. While the technology underlying AI-driven tools is very sophisticated, implementing these tools is simple and well within reach even for small organisations!
The key to making AI work for you is going to be in your data. Your data is what’s unique to your organisation, and it’s what products like Dararo Predict use to “get to know” your donors and their behaviour so those powerful, personalised models can be created. The specific data fields and requirements for using these Dataro products are available here.
Most non-profit organisations we work with already use donor management systems, and while they may require some fine-tuning before they can be used with Dataro products, data governance is not a challenge unique to AI. Making sure your data of high quality will reduce waste and improve ROI in other parts of your organisation. There’s truly no need to be more intimidated by AI integrations than by any other.
Insights from the AI experts at Dataro:
Here’s where you can make sacrifices, and here’s where you can’t:
CRM Type
The Dataro system can flexibly adapt to many fundraising CRMs. You are almost certainly capturing the minimum data that we require as part of your fundraising operations (i.e. soliciting and receiving donations).
We offer pre-built integrations with Salesforce NPSP and Raiser’s Edge NXT for free.
For other CRMs like Salesforce CRM, RE7, BBCRM, Microsoft Dynamics, ThankQ and Donorfy, we can easily scope out the integration and work with you to connect.
For all other CRMs, we recommend reaching out to our team to chat further about how we can support you with our new BETA ‘Drag & Drop’ Integration tool!
For AI to work effectively, there are minimum requirements for your database: In order to achieve additional predictive accuracy, the following data requirements apply:
Database Size:
For Dataro Predict, the minimum database size required is 10,000 donor records, whilst for Dataro Fundraising Intelligence, there is actually no minimum database size!
Database Age:
Minimum Data: Transactions (containing at least 2 years of historical financial transactions).
Recommended Data: Transactions (containing at least 5 years of historical financial transactions).
Still unsure if your organisation is ready for AI? Take this 1 minute quiz to help you find out whether you are ready to use AI at your nonprofit!
If you’re not AI-ready, or want to make sure you’re in the best possible position to get started, the data experts at DCA have some tips:
Much of the data required to use products like Dataro is specific to your organisation, and can only be drawn through your own records pertaining to your donors—this includes information like your transaction histories, unique identifiers for contacts or organisations, or how your donors prefer for you to contact them. This is unique to your donors’ experiences with your organisation, and that’s part of what makes AI tools like this so powerful: instead of generalised trends, you can receive recommendations based on your unique interactions with your donors.
But there are some steps that you should certainly take if you’re considering adopting AI tools. The old adage “garbage in, garbage out,” is never more important than when it comes to the donor information you’re feeding your AI. In order to get high-quality recommendations from the product, you’ll need to make sure that the data you use meets a minimum standard of quality as well as content.
Critically, your data should be:
- Free from duplicate records
If there are many duplicate records in your database, they’ll influence the predictions you get out of your data. Those duplicated records will be overrepresented in your analytics, and you’ll get an inaccurate model.
- Correct and verified
DCA’s long experience in the non-profit sector has taught us that there are many, many ways for incorrect or outdated data to end up in a CRM system. This can happen as a result of a lot of manual data entry, confused customer service interactions, or just data degradation over time. But, the more incorrect information there is sitting in your database, the more likely it is that any analysis produced from that information will inaccurate, too. Consider having a look at data verification and validation processes to make sure your data is as accurate as you can make it.
- Consolidated
Some of the information required by these products can seem pretty daunting, on the surface. The minimum data requirements ask for two years of transaction history—but in the world of data, change comes rapidly. Your organisation might not even be using the same systems or data fields now that you were using two years ago. Or maybe, you might be using many, separate systems to do the job of a single CRM. These are common issues we encounter in the non-profit space, and they can be intimidating to address. But taking a good look at the structure of your database and homogenising it into a single source of truth as soon as possible will save you so much time and effort later. It will also make it much easier to meet the data requirements for products like Dataro Fundraising Intelligence or Dataro Predict.
