Workplace Giving Portals: Claiming the Revenue Sitting in Benevity and YourCause

The Named Platforms, and Who Owns Them Now

This market has consolidated hard, and advice written even two years ago names products that have been renamed, merged, or absorbed. Before you spend an afternoon chasing a platform, confirm it still exists in the form you remember. The pattern to internalize is that each major platform has a separate nonprofit-facing portal with its own registration, its own banking setup, and its own report location, and that portal is where your donor detail lives.

Benevity is the largest employee giving and volunteering platform by corporate footprint, and its nonprofit-facing side is the Benevity Causes Portal. Registration there makes an organization eligible for inclusion in the giving, matching, granting, and volunteering programs of its corporate clients, unlocks disbursement reports, and allows funds to be paid electronically rather than by check. Benevity publishes a nonprofit landing page and a help center for causes, and it is explicit that electronic funds transfer is the preferred payment path. Benevity also deducts a cause support fee from donations, described in its published fee schedule as covering due diligence, processing, disbursement, and donor receipting, so the amount that lands will be slightly less than the amount an employee gave. Ask for the current schedule rather than relying on a number you read in a blog post.

YourCause was acquired by Blackbaud and its nonprofit portal, long known as NPOconnect, has been rebranded as the Blackbaud Verified Network. This is the single most common source of confusion in the sector right now, because a nonprofit that registered with NPOconnect years ago and never logged in again may believe it has no YourCause presence at all. Registration there is also how you reach the donation detail behind a Blackbaud Giving Fund check, which the help documentation states is available only inside your Verified Network account.

CyberGrants is now part of Bonterra, which was formed from the combination of CyberGrants, EveryAction, and Social Solutions. Its nonprofit side has moved too: the old FrontDoor portal has been migrated into the Bonterra Nonprofit Hub, which handles profile data, user access, and disbursement readiness, and which is also where you confirm donations and volunteer hours for matching. Bonterra documents a registration process designed to vet whether the person claiming to represent a nonprofit is actually authorized to do so, which is why claiming a profile is not instant.

Deed was an independent, employee-experience-focused platform until March 2026, when Bonterra announced its acquisition. Expect the nonprofit-facing paths for Deed and CyberGrants to continue converging. Millie is a newer entrant aimed at smaller and mid-market employers, and it runs a straightforward nonprofit claim process: search by EIN at its claim page, submit your affiliation, and a human reviews it before granting dashboard access. Bright Funds is the cautionary example. It merged with WizeHive in 2021, and its current standing is genuinely hard to confirm from public sources, with company databases disagreeing about whether it is still operating independently. Treat any platform you cannot verify as a question for your donor rather than a destination for your time.

Double the Donation belongs in a different category and is frequently miscategorized. It is not a workplace giving portal and no money passes through it to you. It is a match discovery database, embedded in donation forms and CRMs, that tells a donor whether their employer has a match program and what the rules and deadlines are. It is a demand generation tool for matches, not a disbursement channel, and an organization can use it enthusiastically while still having no registration on any of the portals above. For an independent, non-vendor overview of the wider landscape, the Realized Worth Institute technology review hosted by GivingTuesday's workplace giving project compares platforms on their attributes without selling any of them.

Why the Money Goes Unclaimed

Unclaimed workplace giving revenue is usually described as a marketing problem, as though organizations simply failed to ask donors to submit matches. Asking matters, and our article on matching gift revenue deals with it at length. But a large share of the loss happens after the donor has done everything right, inside the mechanics, and those failures are invisible because nothing ever shows up to be missed.

The stale address is the most common and the most ordinary. A check for an aggregated set of gifts goes to the disbursement address on your platform profile, which is the address someone typed in during a staff tenure that ended two reorganizations ago. It is forwarded, or it is not. It is received by a landlord, or returned. Nobody at your organization knows a payment was attempted, because the notification email went to that same departed colleague's inbox. The unregistered EIN is the close relative: an employee designates you, the platform cannot find a verified profile, and the intermediary holds the funds pending verification or applies its own policy. The American Online Giving Foundation states plainly in its FAQ that it cannot guarantee funds reach the originally requested nonprofit, and that where a cause no longer exists or is no longer in good standing with the IRS it will redirect the money to a similar organization. That is a reasonable stewardship policy from the fund's perspective. From yours it is revenue that went to a peer organization because a form was never completed.

Then there are the quieter leaks. Funds below a platform's minimum check threshold sit accumulating rather than being paid, so an organization receiving a handful of $10 payroll gifts may wait a very long time for a disbursement that electronic enrollment would have released immediately. Checks that do arrive sometimes go uncashed because nobody could identify the payer and the finance team was reluctant to deposit an unexplained payment. And on the donor side, the match that was never submitted is still the largest single category of loss: employer windows commonly close at the end of the calendar year, at the end of a corporate fiscal year, or a fixed number of months after the gift, with some companies allowing as little as 30 or 90 days. A donor who gave in November and intended to submit in the new year may already be too late.

None of this is a judgment on under-resourced teams. It is a description of what happens when an organization is the last and least-informed party in a multi-step financial process that nobody designed around its constraints. The useful response is to treat workplace giving as a channel with its own operating procedure rather than a happy accident, which begins with knowing exactly which failure modes you are exposed to.

Volunteer Grants and Dollars for Doers

Running alongside the money is a second, smaller stream that depends on your organization doing something rather than merely receiving something. Volunteer grant programs, often called dollars for doers, pay a charitable grant to an organization in recognition of hours its employees volunteered. Some pay a per-hour rate, others pay a flat amount once a volunteer crosses an hours threshold. Points of Light's guide to dollars for doers programs describes the general shape, and the practical variation between employers is wide enough that generalizing about amounts is unwise.

The operational difference that matters is verification. A matching gift usually needs no action from you, because the platform can confirm the original donation from its own records. A volunteer grant almost always requires someone at your organization to confirm that a named individual actually served the hours claimed. That confirmation arrives as an email asking a staff member to log into a portal, or as a form to sign and return, and it has a deadline. If it lands in a general inbox during a busy week, or goes to a program coordinator who assumes it is spam, the grant quietly expires. Many organizations have lost more revenue to unanswered verification requests than to any other single cause in this channel.

Two habits fix most of it. First, route every verification request to a single named owner with a backup, and treat a request as a revenue item with a due date rather than an administrative email. Second, keep volunteer hour records good enough to answer the question confidently. You cannot verify what you did not record, and a volunteer coordinator being asked in October to confirm hours served in March needs a log rather than a memory. That is partly a systems question, covered in our article on volunteer hours tracking, and partly a cultural one about whether your organization treats hour logging as paperwork or as the basis of a funding claim.

There is a stewardship dimension too. A corporate volunteer who generated a grant for you has demonstrated something more than a donor who clicked a match box, and that person is frequently the bridge to a deeper relationship with the employer: a team volunteer day, a sponsorship conversation, an employee resource group that chooses a nonprofit partner each year. Treating the volunteer grant as a transaction misses the opening. Approaching it as the start of a corporate relationship is the thinking behind our pieces on corporate partnership intelligence and corporate sponsorship research.

Where AI Actually Helps

Notice what the work in this channel consists of. It is parsing inconsistently formatted files, proposing matches between messy name strings and existing records, tying totals to deposits, drafting correspondence under rules, and keeping a calendar of deadlines set by other organizations. That is an unusually good fit for current language models, precisely because almost none of it requires a judgment about a person's capacity or intent. It requires patience, consistency, and literal accuracy, which is where a small team runs out of capacity first.

Parsing remittance files into an importable format. Every platform exports its disbursement detail in its own shape, with different column names, different ways of flagging a match, fee columns that may be gross or net, and dates in different fields. A model handles this transformation well: give it one export and your database's import specification, and ask it to produce a mapping and a converted file, flagging rows it could not confidently map rather than silently dropping them. The real win is building the mapping once per platform as a reusable instruction, so the monthly task becomes running a known recipe rather than re-deciphering a spreadsheet. This is the same discipline as the structured extraction work in automating form filling and data entry.

Proposing identity matches with a confidence score. This is the highest-value and highest-risk application, and the design matters more than the model. Done correctly, you supply the remittance names plus employer and the relevant slice of your constituent list, and ask for candidate matches with an explicit confidence level and the reasoning for each: exact name and known employer, surname plus initial with one plausible household, common surname with three candidates and no distinguishing data. The output is not a decision. It is a triage queue, sorted so a human spends their attention where it changes an outcome. High-confidence matches get a fast human confirmation, ambiguous ones get real review, and the irresolvable ones go to the unattributed bucket without anybody pretending otherwise.

Reconciling statements against deposits. Tying a platform report to a bank line sounds trivial and is not, because fees, timing, partial payments, and held balances make the numbers disagree. Asking a model to compare a disbursement report against your bank and general ledger entries and to explain each variance turns a tedious hunt into a short list of real discrepancies. The explanation is the useful part, since most variances have a mundane cause and the point is to isolate the one that does not. Finance still signs off, and nothing posts because a model said the numbers agreed.

Drafting acknowledgments and the soft credit logic. The rules here are intricate but stable: hard credit the intermediary, soft credit the employee, credit the match to the employer with the employee soft credited, never issue a duplicate tax receipt, respect the anonymity flag. Write those rules down once, as a decision table, and a model can both draft the gift entry instructions for each remittance line and produce acknowledgment letters in the right register for each case. Having the rules written at all is often the improvement, because in many organizations they exist only as one person's habit.

Finding the donors you should be prompting. Working backward is more productive than waiting for portal money to appear. Take the employer field in your own database, which is usually sparse but not empty, and identify which existing donors work at companies with employee giving or volunteer grant programs. A model can help organize and summarize what a match discovery service like Double the Donation reports about those employers, including ratios, caps, and submission windows, and turn it into a prioritized outreach list. Keep this descriptive. You are identifying a documented employer benefit, not scoring a person's likely generosity, and the distinction matters for the reasons set out in our article on donor data guardrails.

Building the deadline calendar and the instructions that work. Employer submission windows vary wildly, from the end of the calendar year to a fixed period after the gift. Collating the windows for the top employers represented among your donors into one calendar, with reminder dates set well before each cutoff, converts a diffuse anxiety into a schedule. The companion task is writing the instructions themselves. Most match requests fail because the ask is generic, so a donor is told that matches exist rather than told which portal to open, what to search for, which EIN to enter, what gift date to use, and what to do when the portal cannot find you. A model drafts those employer-specific, step-by-step instructions quickly, and a tested set of instructions is worth more than another reminder email.

A Ninety-Day Plan for a Small Development Shop

The first month is discovery and registration, and it is almost entirely clerical. Pull every unidentified payment from the last two years of bank records and work out which platform or intermediary each came from. Search for your EIN on Benevity's Causes Portal, the Blackbaud Verified Network, and the Bonterra Nonprofit Hub, and claim or create a profile on each. Complete authorized-representative verification, enroll in electronic disbursement, correct the disbursement address, and register a second administrator with a role-based email. Then download whatever historical disbursement detail each portal will give you, because that is the key to the mystery deposits you just listed.

The second month is the routine. Build the import mapping for each platform's export, once, and save it as a written recipe rather than a one-time conversation. Write the decision table for credit and acknowledgment: who is hard credited, who is soft credited, what the match line does, what happens with an anonymity flag, what an acknowledgment may and may not say. Set up the review queue, however humble, as a spreadsheet with proposed match, confidence, evidence, and a human decision column. Then process one real month end to end and time it, because the measured duration is what tells you whether the routine is sustainable or aspirational.

The third month turns outward. Add an employer field prompt to your donation form and your next newsletter. Build the deadline calendar for the employers that appear most often in your newly readable remittance data. Draft employer-specific submission instructions for the top handful and test them on a cooperative donor before sending them widely. Assign the volunteer grant verification owner and backup. And set a recurring annual reminder to re-check every portal registration, because the most common way organizations lose this revenue a second time is by solving it once and assuming it stays solved.