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This Subcontract opportunity from Ohio was posted on July 28, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Data Analysis & Donor Modeling

Closed
State & Local

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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NAICS: 541690
New
International
Public Art Consulting Services - Collection Assessment
Solicitation # 235817
The City of North Vancouver is seeking a qualified professional to conduct a Public Art Collection Assessment for approximately 100 indoor and outdoor artworks located across parks, plazas, municipal buildings, and commercial developments. The scope of work includes providing individual condition reports for each piece—categorized by ratings such as Excellent, Good, Fair, Poor, or Deaccession—along with photographs, treatment recommendations based on best practices, and cost estimates for repairs. Additionally, the consultant will provide guidance on cultural protocol and safety regarding Indigenous artworks and develop a documentation framework for future additions to the collection. Proposals will be evaluated by a selection committee based on the qualifications of key personnel (30%), previous projects and references (20%), fees and disbursements (15%), project plan and methodology (15%), cultural competency (15%), and sustainability (5%). Applicants must submit a single PDF file by December 3, 2026, and must include a signed Proponent Commitment Form to avoid rejection. The successful contractor is required to maintain a Commercial General Liability policy of at least 5 million Canadian dollars and comply with various Canadian and British Columbia labor and human rights legislations. All financial transactions will be conducted in Canadian dollars, with invoicing requiring a detailed breakdown of hours per team member.
City of North Vancouver

POSTED

1 day ago

DEADLINE

in 27 days

AI Contract Overview

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The contract seeks to leverage historical giving data through advanced analytical methods and predictive modeling to identify and segment donor populations, enabling more strategic and targeted fundraising campaigns. The primary objective is to enhance donor engagement by providing actionable insights that guide gift officer assignments and optimize campaign planning based on predictive outcomes. This work will support Northeast Ohio Medical University’s fundraising efforts by transforming data into strategic tools that improve donor retention, acquisition, and gift size forecasting. The solicitation is classified as a subcontract under NAICS code 541690, which covers other scientific and technical consulting services, and is open for responses until August 11, 2026. The contract is issued by Northeast Ohio Medical University in Ohio, with no specific place of performance or point of contact provided. The award will likely go to a vendor with demonstrated expertise in donor analytics, statistical modeling, and nonprofit fundraising optimization, with the expectation that deliverables will directly influence institutional fundraising priorities and operational efficiency.

General Info

Leverage donor data via predictive modeling to boost fundraising, retention, and gift forecasting for Northeast Ohio Medical University.

Documents

This scope was carved out of 20260728.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Live–Learn–Innovate Philanthropic Campaign Consulting Services

AI Contract Breakdown

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyNortheast Ohio Medical University
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Analyze historical giving data and conduct predictive modeling to segment donors and inform campaign strategies and gift officer assignments.

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