Customer Data Platforms

Amperity for Nonprofits: Enterprise AI Customer Data Cloud

Managing donor data across dozens of disconnected systems, donation platforms, CRMs, event software, email tools, and offline sources, creates incomplete profiles that hamper personalization and waste staff time. Amperity's AI-powered Customer Data Cloud unifies fragmented data into complete donor identities using 45 different identity resolution algorithms, helping enterprise nonprofits see the full picture of each supporter's journey and build audiences that drive results.

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What It Does

Struggling to create accurate donor profiles when your data is scattered across 10+ different systems, each with conflicting information and duplicate records? Amperity solves the enterprise nonprofit challenge of data fragmentation by automatically ingesting data from all your sources, using sophisticated AI to determine which records belong to the same person (even when email addresses or names differ), and building unified donor profiles that update in real time across all connected platforms.

Unlike basic CRM features or simple integration tools, Amperity is a dedicated Customer Data Platform (CDP) that serves as the intelligent data layer between your data warehouse and activation tools. It continuously reconciles conflicting information (like different addresses or phone numbers across systems), maintains data quality, and makes enriched donor profiles available to your marketing, fundraising, and analytics teams, all without requiring your data engineer to write complex ETL scripts.

Best For

Organization Size

Large nonprofits with 100+ staff members and complex data infrastructure
National or international organizations with millions of constituent records
Universities, health systems, and enterprise nonprofits with existing data warehouses
Organizations with dedicated data engineering or analytics teams

Best Use Cases

Unifying donor data from 10+ disconnected systems (CRM, events, online giving, offline sources)
Resolving duplicate records and maintaining golden donor profiles across enterprise systems
Building precise audience segments for multichannel fundraising campaigns
Powering advanced analytics and predictive modeling with clean, unified data

Not Ideal For

Small to mid-sized nonprofits (under 50 staff), organizations without data engineering resources, or nonprofits with limited technical budgets. If you're managing fewer than 100,000 donor records or your data primarily lives in 2-3 systems, Amperity's enterprise complexity and pricing will likely outweigh its benefits. Consider simpler alternatives like Segment or RudderStack instead.

Key Features for Nonprofits

Industry-First Identity Resolution Agent

AI-powered matching that connects donor records across systems even when information conflicts or is incomplete

Uses 45 different identity resolution algorithms combining deterministic (exact matches) and probabilistic (pattern-based) approaches to determine when records belong to the same donor. Uncovers hidden connections, like when Jane Smith donating via credit card is the same person as J. Smith who attended your event, even with different email addresses and slight name variations.

Runs multiple identity graphs simultaneously: Growth Graph for maximum reach, Trust Graph for compliance, Opportunity Graph for confidence scoring
Transparent QA environment lets you visually inspect matches and understand why AI linked specific records
Patented Sandbox environment for testing new data sources without breaking production workflows

Lakehouse CDP Architecture

Native integration with modern cloud data warehouses for organizations with existing data infrastructure

Unlike traditional CDPs that require moving all your data into their proprietary system, Amperity works directly with your existing data warehouse (Databricks, Snowflake, BigQuery). Processes data where it lives, reducing data movement costs and security concerns while giving your data team full control over the underlying infrastructure.

Reduces vendor lock-in, your unified donor data stays in your warehouse, accessible to any tool
Leverages existing cloud infrastructure investments instead of requiring separate data storage
Enables composability, easily swap tools in your stack without re-implementing data pipelines

Flexible Data Ingestion & Activation

Connects to virtually any data source and activates unified profiles across hundreds of marketing and fundraising tools

Ingests data from web analytics, CRMs, donation platforms, event software, email marketing tools, direct mail vendors, offline sources, and third-party data providers. Once unified, sends enriched donor profiles and audiences to the specific tools your teams actually use for campaigns and communications.

Pre-built connectors for common nonprofit platforms (Salesforce, Mailchimp, Google Ads, Facebook, and more)
Custom API integrations for proprietary systems or legacy databases unique to your organization
Real-time audience activation, segments update automatically as donor behavior changes

Predictive Analytics & Insights

AI models built on unified data to forecast donor behavior and identify high-value opportunities

Leverages Custora technology (acquired 2019) for predictive modeling on top of unified donor profiles. Identifies patterns invisible in siloed data, like correlations between event attendance, email engagement, and major gift likelihood, to surface actionable insights for fundraising teams.

Churn prediction models identify at-risk donors before they lapse, triggering retention campaigns
Lifetime value scoring helps prioritize major gift prospects and personalize cultivation strategies
Lookalike modeling for paid media, find new supporters who resemble your best existing donors

How This Tool Uses AI

Amperity is built on patented AI and machine learning technology specifically designed for the hardest problem in data management: figuring out which records across disconnected systems belong to the same person. Here's how the AI actually works and where it genuinely adds value.

AI-Powered Identity Resolution

Type of AI: Ensemble Machine Learning (45 algorithms working together)

Amperity doesn't rely on a single AI approach. Instead, it runs 45 different identity resolution algorithms simultaneously, combining deterministic matching (exact matches on email, phone, address) with probabilistic matching (pattern recognition and statistical likelihood). The AI evaluates results from all 45 algorithms and uses confidence scoring to determine the best match.

What it does:

Identifies that "Jane A. Smith" at [email protected] (donation record) is the same person as "J Smith" at [email protected] (event registration), even though email addresses and names differ
Handles address changes, married name changes, typos, and incomplete information across systems
Creates "golden records" that intelligently merge the most accurate information from each source

How it learns:

The AI improves as it processes more of your data, learning patterns specific to your donor base. It continuously evaluates match quality and adjusts algorithm weights based on your feedback when you approve or reject matches in the QA interface. The Identity Resolution Agent (announced April 2025) accelerates this learning process with a natural language interface for data teams.

Practical impact:

Instead of manually deduplicating records or accepting incomplete donor profiles, the AI automatically maintains clean, unified identities. One leading retailer (use case from Amperity) uncovered 3.5 million previously unreachable customer emails, representing potentially millions in recovered revenue. For nonprofits, this means discovering "lost" donors whose records were fragmented across systems.

Predictive Donor Models

Type of AI: Supervised machine learning for classification and regression

Built on Custora's technology (acquired by Amperity in 2019), these models use historical donor behavior to predict future actions. They're trained on patterns in your unified data, like the correlation between event attendance frequency, donation timing, and major gift conversions.

What it does:

Churn prediction: Scores each donor's likelihood of lapsing in the next 3-12 months based on engagement patterns
Lifetime value scoring: Predicts total giving potential over a donor's relationship with your organization
Next best action recommendations: Suggests optimal outreach (appeal, event invitation, stewardship call) for each donor

Practical impact:

Instead of treating all lapsed donors the same, you can prioritize re-engagement efforts based on predicted win-back likelihood. Focus major gift officers on prospects with highest lifetime value scores. One Amperity client saw loyalty conversion increase 3x after merging data from two brands, your nonprofit might see similar results consolidating multiple program or chapter databases.

What's NOT AI (But Still Useful)

Data ingestion connectors: Pre-built integrations with common platforms use standard ETL (Extract, Transform, Load), not AI
Segment building interface: Rule-based audience creation (e.g., "donors who gave $500+ last year") is traditional database querying
Standard analytics dashboards: Basic metrics like donor retention rate and average gift size are traditional calculations
Audience activation: Sending unified profiles to downstream tools is standard data routing, not AI-driven

AI Transparency & Limitations

Data Requirements:

Identity resolution works best with at least 3-5 overlapping data sources containing common identifiers (email, phone, address)
Predictive models require minimum 12-24 months of historical transaction data; accuracy improves with more data
Small donor databases (under 100K records) may not provide sufficient patterns for accurate predictions

Human Oversight Required:

AI identity matches should be reviewed through the QA interface, especially in early implementation, false positives can merge unrelated donor records
Predictive scores are probabilities, not certainties, don't exclusively rely on AI for major gift prioritization without human judgment
Data quality issues upstream (typos, missing fields, inconsistent formatting) reduce AI accuracy, garbage in, garbage out still applies

Known Limitations:

Identity resolution algorithms are optimized for U.S./English data patterns; international organizations may need custom tuning
AI can't account for offline context your staff knows, like a donor's verbal commitment at an event not yet recorded in systems
Predictive models reflect historical patterns; sudden changes in donor behavior (economic shifts, major news events) may not be captured immediately

Bottom Line: Amperity uses AI where it genuinely solves hard problems, matching fragmented donor records and predicting behavior, not just as a marketing buzzword. The identity resolution is legitimately sophisticated, far beyond what you could do manually or with simple deduplication tools. However, it requires substantial data volume and technical expertise to maximize value. If your nonprofit has the scale and resources, the AI delivers measurable ROI. If you're smaller or less technical, the complexity may outweigh the benefits.

Real-World Nonprofit Use Case

A national health advocacy organization with 2.3 million constituents across the U.S. struggled with fragmented donor data living in separate systems: a legacy CRM for major gifts, an online donation platform for digital giving, event management software for walks and galas, an email marketing tool, and offline direct mail vendor data. When development officers looked up a supporter, they only saw partial information from one system, missing critical context about that person's full engagement history.

The organization had tried basic CRM deduplication features, but manual matching couldn't handle the scale or complexity. Donors who moved, changed email addresses, or used different name variations across systems remained fragmented. The data team spent 15+ hours per week creating custom reports to piece together complete donor journeys for major gift research.

After implementing Amperity (6-month project), the AI identity resolution unified records across all systems, revealing that roughly 18% of their "unique donors" were actually duplicate profiles. Amperity uncovered 320,000 previously unidentified email addresses by connecting online and offline records, expanding their reachable audience overnight without acquiring new donors.

With unified donor profiles, the fundraising team could see each supporter's complete engagement history in one view: event attendance, online giving, volunteer hours, email interactions, and advocacy actions. This enabled precise segmentation, like identifying donors who attended local events but never gave online, or major donors with low email engagement who might prefer direct mail or phone outreach.

Results after 12 months: Email campaign performance improved 31% (better segmentation meant more relevant messages), major gift prospect research time dropped from 3 hours per prospect to 20 minutes (complete profiles in one place), and donor retention increased 12% (churn prediction models triggered timely retention campaigns). The data engineering team redirected those weekly reporting hours to building new analytics and predictive models that drive strategic fundraising decisions.

Pricing

Usage-Based "Amps" Model

Specific pricing is not publicly listed and requires a sales consultation. Amperity emphasizes transparency (you can track Amp consumption in real time) and scalability (pricing grows with your data volume and usage, no hidden fees or add-ons).

Enterprise Focus: Amperity is positioned for enterprise organizations with substantial technology budgets. Based on typical CDP market rates for this tier, expect investment in the range of tens of thousands to hundreds of thousands annually, depending on data volume, number of data sources, and feature requirements.

What's Typically Included vs. Additional Costs

Typically Included:

Identity resolution with all 45 algorithms and multiple identity graphs
Data ingestion connectors for common platforms
Audience segmentation and activation capabilities
Ongoing platform support and access to documentation

Potential Additional Costs:

Professional services: Implementation consulting, custom integration development, data architecture design ($20K-100K+ depending on scope)
Cloud data warehouse costs: If using Databricks, Snowflake, or BigQuery, you'll pay separately for compute and storage
Internal staff time: Budget for at least one full-time data engineer/analyst during implementation and ongoing maintenance
Data cleanup: Amperity works best with reasonably clean source data; plan for data quality improvements before or during implementation

💰 Nonprofit Discount

Amperity does not publicly advertise a specific nonprofit discount program. As an enterprise-focused platform, pricing is customized based on data volume, features needed, and implementation scope.

How to Explore Pricing: Contact Amperity's sales team directly to discuss your organization's needs. Be prepared to share:

Number of constituent records (total database size)
Number of data sources to integrate (CRM, email, donation platforms, events, etc.)
Expected usage patterns (monthly audience activations, predictive model runs)
Your existing data infrastructure (do you have a data warehouse? which one?)

While a formal nonprofit discount may not be available, enterprise vendors often have flexibility in pricing for mission-driven organizations. Emphasize your 501(c)(3) status, ask about flexible payment terms, and inquire whether they have prior experience working with nonprofits (which may indicate willingness to accommodate budget constraints).

Note: Prices may be outdated or inaccurate.

Learning Curve

Advanced - Technical Expertise Required

Amperity is an enterprise platform that requires data engineering skills and significant technical resources. This is not a tool that marketing or fundraising teams can implement independently, expect to involve (or hire) data professionals with experience in data warehousing, ETL processes, and data modeling.

Time to First Value

Initial setup: 1-2 months (data warehouse connection, first data sources ingested, identity resolution configured)
First unified profiles: 2-4 weeks after data ingestion begins
Comprehensive implementation: 3-6 months (all data sources integrated, predictive models trained, teams trained on activation)
Full proficiency: 6-12 months of regular use and optimization

Technical Requirements

Data engineering team or dedicated data analyst with SQL expertise
Existing cloud data warehouse (Databricks, Snowflake, BigQuery) or budget to implement one
Understanding of data governance, privacy regulations, and identity resolution concepts
API integration experience for custom data sources
Strong project management to coordinate implementation across technical and business stakeholders

Support & Resources

Professional services team: Amperity offers implementation consulting to accelerate deployment and ensure best practices
Extensive documentation: Technical guides, API references, and best practice documentation for data teams
Dedicated account management: Enterprise customers typically receive dedicated support contacts
Training programs: Technical training for data teams and business user training for marketers using activated audiences

Integration & Compatibility

Connects With

Data Warehouses (Core Infrastructure):

Databricks, Snowflake, Google BigQuery, Amazon Redshift

CRM & Donor Management:

Salesforce (including Nonprofit Cloud), Microsoft Dynamics, HubSpot, custom CRMs via API

Email & Marketing Automation:

Mailchimp, Brevo (Sendinblue), Klaviyo, Marketo, Adobe Campaign, Iterable

Digital Advertising:

Google Ads, Facebook Ads, LinkedIn Ads, The Trade Desk, LiveRamp

Analytics & Business Intelligence:

Google Analytics, Adobe Analytics, Tableau, Looker, Power BI, Mixpanel

E-commerce & Donation Platforms:

Stripe, Classy, Shopify, BigCommerce, WooCommerce (via custom integration)

Event Management:

Eventbrite, Cvent, custom event platforms via API or CSV import

Platform Availability

Web-based platform: Access via modern web browsers (Chrome, Firefox, Safari, Edge)
No mobile app: Amperity is designed for data teams working on desktops; not optimized for mobile use
Cloud-native: Runs entirely in the cloud; no on-premise installation required

Data Portability & Vendor Lock-In

Lakehouse architecture advantage: Your unified donor data lives in YOUR data warehouse (Databricks/Snowflake), not locked in Amperity's proprietary system
Full data export: Can export all unified profiles, identity graphs, and segment definitions as CSV or via SQL queries
API access: Programmatic access to unified data allows integration with any tool that supports APIs
Identity resolution logic is proprietary: While you own the unified data, recreating Amperity's matching algorithms elsewhere would require significant engineering work

Pros & Cons

Pros

Industry-leading identity resolution: 45 AI algorithms and multiple identity graphs solve the hardest data unification problems enterprise nonprofits face
Lakehouse architecture reduces vendor lock-in: Your unified data lives in your warehouse, accessible to any tool, not trapped in a proprietary CDP silo
Transparent QA process: Visual interface shows why AI matched specific records, building confidence in data quality and allowing manual corrections
Patented Sandbox environment: Test new data sources without breaking production, critical for complex nonprofit data ecosystems
Predictive models built on Custora technology: Proven churn prediction, lifetime value scoring, and next-best-action recommendations
Comprehensive integration ecosystem: Pre-built connectors for major platforms plus custom API integrations for unique nonprofit systems

Cons

Enterprise pricing: No public pricing; usage-based model can be expensive at scale, likely tens to hundreds of thousands annually
Requires technical expertise: Not suitable for nonprofits without data engineering teams or cloud data warehouse experience
Long implementation timeline: 3-6 months for comprehensive deployment, not a quick win or easy setup
Overkill for smaller nonprofits: If you have under 100K donor records or fewer than 5 key data sources, simpler (cheaper) solutions will suffice
No advertised nonprofit discount: Unlike some CDPs with explicit nonprofit programs, Amperity pricing is enterprise-negotiated
Ongoing maintenance required: Expect to dedicate ongoing data engineering resources for monitoring, optimization, and adding new data sources

Alternatives to Consider

If Amperity's enterprise focus and technical requirements feel like a mismatch, consider these alternatives better suited to different nonprofit contexts:

Segment

Leading CDP with generous free tier and more accessible pricing

Segment offers similar data unification capabilities with a much lower barrier to entry. The free developer plan includes 1,000 monthly tracked users and 500,000 Reverse ETL records, sufficient for many small to mid-sized nonprofits. Identity resolution is less sophisticated than Amperity (uses deterministic matching primarily), but easier to implement and maintain without dedicated data engineering staff. Best if you need donor data unification but don't have enterprise infrastructure or budgets.

Choose Segment if: You want CDP benefits without enterprise complexity; you have under 100K monthly active supporters; you need faster implementation (weeks vs. months); or your team is comfortable with SaaS tools but lacks data warehouse experience.

RudderStack

Open-source warehouse-native CDP with more affordable pricing

RudderStack shares Amperity's warehouse-first philosophy but with open-source flexibility and lower costs. The free tier supports 1,000 monthly tracked users with unlimited events, ideal for budget-conscious nonprofits with technical teams. Identity resolution is less advanced than Amperity (basic merging vs. 45 AI algorithms), but sufficient for many use cases. Can self-host for complete data control or use managed cloud service.

Choose RudderStack if: You have data engineering skills but tight budgets; you prefer open-source tools with community support; you want warehouse-native CDP benefits without enterprise pricing; or you're comfortable managing infrastructure yourself.

Treasure Data

Enterprise Intelligent CDP with strong AI profile unification

Treasure Data is an enterprise CDP comparable to Amperity in sophistication, with strong AI-powered identity resolution and lakehouse integration. Differentiates with built-in AI/ML modeling studio for predictive analytics without needing separate tools. Like Amperity, it's enterprise-focused with custom pricing. Best for large nonprofits evaluating multiple enterprise CDP vendors.

Choose Treasure Data if: You're already evaluating enterprise CDPs and want a competitive option to Amperity; you need built-in predictive analytics without external data science tools; you value strong compliance certifications (HIPAA, SOC2, ISO); or you're exploring multiple vendors for best pricing.

Native CRM Features (Salesforce, Blackbaud, etc.)

Built-in deduplication and data management within your existing CRM

Before investing in a separate CDP, evaluate your existing CRM's native data unification features. Nonprofit CRM platforms include deduplication, data enrichment, and basic identity resolution capabilities. While less sophisticated than dedicated CDPs, they may be sufficient if your donor data primarily lives within one system.

Choose native CRM features if: Your donor data is mostly centralized in one CRM; you're not dealing with extensive multi-channel data fragmentation; you want to avoid adding another platform; or you're a smaller nonprofit without resources for CDP implementation.

Why you might choose Amperity instead: If you're a large nonprofit (100+ staff, millions of donor records) with existing data warehouse infrastructure and complex data fragmentation across 10+ systems, Amperity's sophisticated AI identity resolution and enterprise-grade features justify the investment. The 45-algorithm approach, transparent QA, and patented Sandbox deliver results that simpler tools can't match, when you have the scale and technical resources to maximize its value.

Getting Started

Amperity is not a tool you can sign up for and start using immediately, it requires strategic planning and enterprise engagement. Here's how to approach the evaluation and implementation process:

Step 1: Assess Your Readiness (Before Contacting Amperity)

Evaluate whether your organization is truly ready for an enterprise CDP before investing time in sales conversations.

Data infrastructure: Do you have (or plan to implement) a cloud data warehouse like Databricks, Snowflake, or BigQuery?
Technical resources: Can you dedicate at least one full-time data engineer/analyst during implementation and ongoing?
Data volume: Do you manage 100K+ constituent records across 5+ disconnected data sources?
Budget: Is there room in your technology budget for enterprise software (typically $50K+ annually)?

If you answered "no" to 2+ of these questions, consider starting with a simpler CDP like Segment or RudderStack to build data unification capabilities before upgrading to enterprise solutions.

Step 2: Contact Amperity for Discovery Call (1-2 hours)

Reach out to Amperity's sales team to discuss your use case and explore whether the platform fits your needs.

Contact Amperity Sales

Prepare to discuss:

Your organization's mission, size, and donor base (number of constituents, annual revenue)
Current data infrastructure (existing data warehouse, CRM, marketing tools, donation platforms)
Specific data challenges you're trying to solve (fragmented profiles, duplicate records, incomplete data)
Use cases you want to enable (audience segmentation, predictive analytics, multichannel activation)
Technical team capabilities and capacity for implementation

Step 3: Proof of Concept / Pilot (2-3 months)

If Amperity seems like a fit, negotiate a pilot or proof-of-concept engagement to validate value before full deployment.

Connect 2-3 key data sources (e.g., CRM, donation platform, email marketing tool) to demonstrate identity resolution
Evaluate match quality through the QA interface, how accurately does the AI unify your donor records?
Build test audience segments and activate to one downstream tool (e.g., send unified profiles to your email platform)
Measure tangible outcomes: How many duplicate records were resolved? How many "new" email addresses were discovered? What's the data quality improvement?

Pro tip: Negotiate clear success criteria before the pilot. Define what "good" looks like (e.g., "resolve 80%+ of known duplicates," "unify 95%+ of donor profiles across 3 sources") so you can objectively evaluate ROI.

Step 4: Full Implementation (3-6 months)

If the pilot demonstrates value, move forward with comprehensive implementation.

Ingest all data sources (expand beyond pilot to include event software, offline data, third-party enrichment)
Tune identity resolution algorithms for your specific data patterns and organizational needs
Build production audience segments for fundraising, marketing, and program teams
Train predictive models (churn prediction, lifetime value scoring) on unified historical data
Activate unified profiles and audiences to all downstream tools in your stack
Train business users (marketers, development officers, analysts) on leveraging unified data

Consider professional services: Amperity offers implementation consulting, or you can engage a systems integrator with CDP expertise. This accelerates deployment and ensures you follow best practices, often worth the investment given the platform's complexity.

Need Help with Implementation?

Evaluating enterprise customer data platforms like Amperity is complex. If you're unsure whether your nonprofit is ready for this level of investment, or need guidance navigating the vendor selection and implementation process, we're here to help.

One Hundred Nights offers data strategy consulting and CDP implementation support, from readiness assessments to hands-on technical implementation and team training.

Schedule a Consultation

Frequently Asked Questions

Does Amperity offer a nonprofit discount?

Amperity does not advertise a specific nonprofit discount program. As an enterprise-focused platform, pricing is customized based on data volume, features needed, and implementation scope. Organizations should contact Amperity's sales team directly to discuss nonprofit pricing options. Given the enterprise focus and usage-based pricing model, Amperity is typically best suited for large nonprofits with substantial budgets (typically $50K+ annually for technology platforms).

What makes Amperity different from other customer data platforms?

Amperity distinguishes itself with its industry-first Identity Resolution Agent that uses 45 different AI/ML algorithms to match donor records across sources. Unlike simpler CDPs, Amperity can run multiple identity graphs simultaneously, a Growth Graph for maximum reach, Trust Graph for compliance, and Opportunity Graph to measure matching confidence. It's built for the lakehouse architecture (Databricks, Snowflake), making it ideal for organizations with data engineering teams. The patented Sandbox environment lets you test new data sources without breaking production workflows, a critical feature for complex nonprofit data environments.

Is Amperity suitable for small to mid-sized nonprofits?

Amperity is generally not the best fit for small to mid-sized nonprofits. It's designed for enterprise organizations with complex data infrastructure, technical teams, and substantial budgets. If your nonprofit has fewer than 50 staff members, limited technical resources, or annual technology budgets under $100K, consider more accessible alternatives like Segment, RudderStack, or native integrations within your existing CRM. Amperity excels when you have millions of donor records across dozens of data sources and need sophisticated identity resolution, scenarios more common in large health systems, universities, or national nonprofit organizations.

How long does it take to implement Amperity?

Amperity implementation is a substantial project typically requiring 3-6 months for comprehensive deployment. Initial setup (data ingestion from key sources, identity resolution configuration, basic integrations) takes 1-2 months with dedicated technical resources. Fully optimizing identity resolution, building automated audience segments, integrating all data sources, and training teams typically extends to 3-6 months. Expect to dedicate at least one full-time technical staff member (data engineer or analyst) during implementation, plus ongoing resources for maintenance. Many organizations engage Amperity's professional services or consulting partners to accelerate implementation and ensure best practices.

What technical requirements does Amperity have?

Amperity requires technical expertise and infrastructure. You'll need: (1) A data engineering or analytics team with experience in data modeling and ETL processes, (2) Existing data infrastructure like a cloud data warehouse (Databricks, Snowflake, BigQuery) or plans to implement one, (3) Clean, structured data sources with consistent identifiers (email, phone, address, donor IDs), (4) Technical resources for API integrations and ongoing maintenance, and (5) Leadership buy-in for a multi-month implementation project. If your nonprofit doesn't have dedicated data engineering staff or a cloud data warehouse, Amperity's complexity may outweigh its benefits, consider starting with simpler CDP solutions or native CRM features first.

What is Amperity's pricing model based on?

Amperity uses a usage-based pricing model measured in "Amps", a standardized unit of consumption that tracks platform usage. Amps are consumed by activities like processing customer records, building segments, running campaigns, and activating insights. The model is designed to be transparent and scale with your organization's growth, with no hidden fees or add-ons. However, specific pricing is not publicly listed and must be obtained through a sales consultation. This approach means costs can scale significantly with data volume and usage, making it critical to understand your data architecture and usage patterns before committing.