Machine learning (AI) requires a tremendous volume and depth of data. The phenomenal AI success stories you hear about in the news have a tremendous amount of data to work with, far more than many of the largest nonprofits. However nonprofits are actually generating a tremendous amount of data in their digital footprints and analog activities. Eg. When you send an email you generate numerous data points that aren’t stored in your email system or CRM. You also generate data points in relation to other data points, or what we call meta-data.

At Fundmetric we generate a more robust and relevant data set for your organization.

In machine learning, data labeling is the process of identifying raw data and adding one or more meaningful and informative labels to provide context so that a machine learning model can learn from it.

The structuring and labeling of data is the first crucial step that prevents organizations from truly taking advantage of AI. Labeling is part of the groundwork that must be done correctly and it is usually time consuming and costly.

For those cyberspace cowboys who want to learn more about labeling data, here are some companies in the for-profit space who do it.

Fundmetric custom builds integrations for any of your data sources. Data is very human, therefore we believe that our integrations should not always be mechanical but instead be built to accommodate human inconsistencies. We may build a traditional integration (eg. API), but more often than not we build custom scripts to fit your data exactly.

For example: Some organizations split their donation credits differently between spouses, this can easily paint a misleading picture to machine learning as to who actually makes decisions around giving. This example is why our data science team moves data by hand, and then automates the process. These seemingly small details, have huge human implications and would be missed by mechanical integrations.

We sell software, not shelfware. Without a vendor team that learns the context of your organization, we would produce generic predictions. This leads to a lack of trust among staff in the predictive results. Therefore, when it comes to making artificial intelligence useful, adoption across your organization is critical.

When staff feel they are listened to and their input is incorporated, we are all more successful. This is why we include consulting and there is no additional charge for this. We frequently provide context and briefings to teams at all levels including executives and entire boards. Our collaborative approach and ability to fit the workflow of our clients leads to dramatically different outcomes.

We provide regular one on one meetings with an account manager who will bring specialty teams in as needed. This handles strategic fundraising advice, process and user adoption workflows and technical changes to make Fundmetric fit your organization. We also have live chat in-app and email support.

All support is included in your license.

Support includes:
- Dedicated recorded virtual sessions that will train staff how to use the software
- Training around common misconceptions about machine learning and metrics
- A dedicated point of contact at Fundmetric and access to our support team.
- Training of all new staff during transitions etc.
- Additional Training if needed. Retention of the information requires repetition and so we are happy to walk people through the application during dedicated training meetings.
- Real-time support, if a staff member wants to explore the data or develop a new segment, Fundmetric support staff is available through a - live chat and email function to respond during business hours.
- Access to documentation around how to use the product.
- The ability to schedule full or partial training for existing or new staff members
- Training on how the model(s) was created and how to further segment based on behaviors
- Training will also include best practices and the highlighting of opportunities that may have been historically missed.

Onboarding varies from organization to organization, depending upon size and the state of your data. Below is a sample timeline of onboarding for medium to large size organizations.

Initial data analysis - 1-2 weeks
Data import and mapping - 2-4 weeks
Data Verification and Integrity - 2-3 weeks
Data Modelling - 2-4 weeks
Settings, Orientation and Platform Configuration - 2 weeks

Fundmetric charges one fee based on the size and scale of your organization. Our priority is to make sure Fundmetric is adopted by your organization and therefore there are no additional fees for support, additional users, or access to platform features.

Meet with us to get a quote

Yes, Wealthmetric + is a data augmentation service we offer, and we have the ability to pull in publicly available data from multiple sources. This is on a pay per field basis and we only charge for values that are returned. We will also import any of your existing wealth data into Fundmetric free of charge.

- Examples of fields include:
- Household income
- Home value
- Length of time in the home
- Occupation level
- Gender
- Age
- Martial status
- Presence of children
- Education level
- Charitable donor

Yes, with Wealthmetric + we can also find additional contact information such as :
- Email activity first active data
- Velocity of email
- Longevity of account
- Last active date
- Postal address

We only charge when we return a value for the requested field.

Yes, our social media data is currently included in your licence fee, including information such as:
- Social media
- Social follower count
- Interest data
- Employment history