To: AVP of Development Operations, Earthjustice From: Senior Revenue Operations Consultant & Salesforce Architect Subject: Analytics Transformation Plan — "Never Rest" Campaign (2025–2029) Date: March 2026 Executive Overview Earthjustice's "Never Rest" campaign must raise $207M over four years — a timeline that makes undetected performance gaps uniquely dangerous. A single missed quarter of mid-level retention or digital acquisition ROI does not simply cost that quarter's shortfall; it compounds. Fewer retained donors in Year 1 means a smaller upgrade pool in Year 2, a weaker sustainer base in Year 3, and a structural revenue deficit by Year 4 that no year-end surge appeal can close. Relying on lagging indicators (historical results reported after the fact) and manual data pulls leaves leadership blind to exactly the early warning signals that separate a recoverable dip from a permanent hole. Earthjustice helped secure 10 air pollution rules in the course of the five-year Never Rest™ campaign, and the fundraising infrastructure powering that campaign must now evolve to match its ambition. Without a dedicated data warehouse, our strategy maximizes the native capabilities of Salesforce Nonprofit Cloud and EveryAction, deploying lightweight, pragmatic bridges only where necessary to ensure development officers and channel leads have uninterrupted visibility into campaign health. This transformation plan architects a shift toward predictive analytics (statistical models that forecast donor behavior) and automated decision workflows (rules that trigger specific actions when thresholds are crossed) across three distinct phases: first, establishing a trusted single source of truth (the one authoritative record for each data point, abbreviated SSOT) and deploying core descriptive dashboards (Months 1–6); second, layering in donor risk and propensity scoring models with workflow triggers (Months 7–14); and third, activating deep cross-channel automation and optimization (Months 15–24). By calibrating data freshness to operational needs — daily for revenue monitoring, weekly batch cycles for predictive scoring — we will equip leadership to anticipate donor behavior rather than simply report on it. This roadmap ensures that Earthjustice's data infrastructure scales at the exact pace of its campaign ambitions, protecting revenue stability through 2029. Real-Time Leadership Questions Development leadership and channel leads must be able to answer the following questions on demand, without submitting a custom report request: [Descriptive] Are we on track to hit this month's blended revenue and campaign milestone targets? [Diagnostic] Which specific direct response channels (email, SMS, mail) or donor segments are driving the variance in our current month-to-date performance? [Predictive ⁱ] Which core mid-level and major donors are exhibiting behavioral signals that indicate they are at risk of lapsing before calendar year-end? [Descriptive] What is the real-time conversion rate of our top-of-funnel advocacy actions (petitions/calls) into first-time financial gifts? [Predictive ⁱ] Which current sustained (monthly) donors possess the highest propensity to upgrade to mid-level or make a restricted campaign major gift? [Diagnostic] Why is our major gift pipeline velocity slowing, and in which specific cultivation stages are prospects stalling? [Predictive ⁱ] Which inactive/lapsed donors on our EveryAction file have the highest statistical likelihood of reactivation if targeted with a "Never Rest" campaign match offer? ⁱ Predictive Score Latency Note: All predictive questions are answered by scores refreshed on a weekly batch cycle (Sundays, 2:00 AM). Scores reflect the most recent full week of data and are strategic planning instruments, not intra-day triggers. See Section 5 for latency architecture and Section 6 for model specifications. Section 3 Transition: The leadership questions above define what we need to know. The KPI framework below translates each question into a precisely defined, measurable signal — assigning ownership, frequency, and a target benchmark so that no metric exists without accountability and no question goes unanswered. KPI Framework Limited to 20 highly actionable signals to prevent metric dilution. Every KPI maps to at least one leadership question from Section 2 and at least one dashboard in Section 4. Category KPI Name Definition Measurement Frequency Owner Target Benchmark Campaign & Revenue Campaign Revenue to Goal Total booked revenue vs. multi-year "Never Rest" campaign target Weekly AVP, Dev Ops 100% of YTD Target Campaign & Revenue Cash in Door (CID) Realized cash receipts (excluding multi-year pledges not yet paid) Daily Sr. Dir, Dev Ops ≥ 108% of Prior YTD Campaign & Revenue Pipeline Coverage Ratio Total weighted value of open asks vs. remaining campaign goal Monthly Dir, Major Gifts ≥ 3.0x Campaign & Revenue Cost to Raise a Dollar (CRD) Total fundraising expense divided by total revenue Quarterly AVP, Dev Ops ≤ $0.18 Campaign & Revenue Average Gift Size Total revenue divided by total number of gifts Monthly Channel Leads ≥ 5% YOY Growth Campaign & Revenue Pledge Fulfillment Rate Percentage of committed major gift pledges realized on schedule Quarterly Dir, Major Gifts ≥ 95% Channel Performance Email/SMS Rev per M (RPM) Revenue generated per 1,000 messages delivered via EveryAction Weekly Dir, Digital ≥ $45 RPM (House) Channel Performance Digital Ad ROAS Return on ad spend for acquisition and retargeting campaigns Weekly Dir, Digital ≥ 1.5x (Blended) Channel Performance Direct Mail Response Rate Percentage of mail recipients completing a gift Post-Campaign Dir, Direct Mail ≥ 4.5% (House File) Channel Performance Telemarketing Conversion Percentage of completed calls resulting in a gift or upgrade Weekly Dir, Outreach ≥ 8% Channel Performance Major Gift Win Rate Percentage of major gift solicitations resulting in a closed-won gift Quarterly Dir, Major Gifts ≥ 60% Channel Performance Advocacy-to-Donor Conv. Percentage of non-donor advocates making a first gift within 90 days Monthly Dir, Digital ≥ 2.5% Channel Performance Landing Page Conv. Rate Percentage of visitors completing a donation on campaign forms Weekly Dir, Digital ≥ 18% Donor Behavior First-Year Retention Percentage of new donors retained in year two Monthly Sr. Dir, Dev Ops ≥ 28% Donor Behavior Multi-Year Retention Percentage of multi-year donors retained YoY Monthly Sr. Dir, Dev Ops ≥ 65% Donor Behavior Monthly Sustainer Growth Net growth of active recurring donors Monthly Dir, Mid-Level ≥ 12% YOY Net Growth Donor Behavior Upgrade Rate Percentage of donors increasing their annual giving total Quarterly Dir, Mid-Level ≥ 10% Donor Behavior Downgrade/Churn Rate Percentage of donors decreasing giving or lapsing Monthly Sr. Dir, Dev Ops ≤ 30% Donor Behavior Reactivation Rate Percentage of previously lapsed donors making a new gift Quarterly Dir, Direct Mail ≥ 5% Donor Behavior Major Donor Velocity Average days a prospect spends in the cultivation stage Monthly Dir, Major Gifts ≤ 180 Days Section 4 Transition: With 20 KPIs defined and owned, the next question is where each signal surfaces for its intended audience. The dashboard framework below maps every KPI to a specific dashboard, assigns audiences and alert thresholds, and flags which dashboards are buildable natively in Salesforce versus those requiring the lightweight Looker Studio bridge described in Section 5. Dashboard Framework Dashboard Name Primary Audience Key Metrics / Views (KPI Names from Section 3) Update Frequency Data Sources Critical Alerts to Surface Native vs. Bridge 1. Exec Campaign Overview C-Suite, VP Dev Campaign Revenue to Goal, Cash in Door (CID), Pipeline Coverage Ratio, First-Year Retention, Multi-Year Retention, Cost to Raise a Dollar (CRD), Average Gift Size, Pledge Fulfillment Rate Daily SF Opportunities, SF Campaigns Campaign trailing >5% behind YTD pacing; CRD exceeding $0.20 threshold Native — SF CRM Analytics (Salesforce's embedded business intelligence layer) 2. Channel Performance & Testing Digital, DM, & Telemarketing Leads Email/SMS Rev per M (RPM), Digital Ad ROAS, Direct Mail Response Rate, Telemarketing Conversion, Landing Page Conv. Rate Daily / Real-Time EveryAction (Digital), SF (DM/TM) Email RPM drops >15% below 30-day rolling avg; Landing Page Conv. Rate falls below 12% Bridge — EA Scheduled Export → Looker Studio (Google's free-tier visualization tool) 3. Donor Health & Retention Mid-Level & Annual Giving Leads First-Year Retention, Multi-Year Retention, Monthly Sustainer Growth, Downgrade/Churn Rate, Upgrade Rate, Reactivation Rate Weekly SF Contacts, SF Opportunities Churn risk segment exceeds 10% of active file; First-Year Retention drops below 25% Native — SF CRM Analytics 4. Major/Mid-Level Pipeline Major Gift Officers (MGOs), Prospect Research Major Donor Velocity, Major Gift Win Rate, Pipeline Coverage Ratio, Pledge Fulfillment Rate, Overdue Asks, Next Best Actions Daily SF Opportunities, SF Tasks Prospect stuck in Cultivation > 180 days (Major Donor Velocity alert); Win Rate drops below 50% Native — SF Lightning Dashboards + Reports 5. Outreach & Audience Engagement Advocacy & Digital Comms Advocacy-to-Donor Conv., Landing Page Conv. Rate, Petition Signatures, Engagement Score Weekly EveryAction (Actions), SF (Gifts) High-engagement advocate has no active cultivation; Advocacy-to-Donor Conv. falls below 1.5% Bridge — EA + SF Scheduled Export → Looker Studio Cross-Reference Verification: Every KPI from Section 3 appears verbatim in at least one dashboard above. Dashboards 1 and 3 share retention KPIs to enable both executive and operational views. Dashboard 4 shares Pipeline Coverage Ratio and Pledge Fulfillment Rate with Dashboard 1 to support drill-down from executive pacing to pipeline detail. Section 5 Transition: The dashboards above are only as reliable as the data flowing into them. This section defines the technical plumbing — system-of-record boundaries, sync frequency, connector limitations, and the explicit latency contracts stakeholders must understand — that makes Dashboards 1–5 trustworthy and sustainable on a lean team. Data and Tool Architecture To execute this without a data warehouse or external transformation layer, we enforce strict system-of-record boundaries and manage API/governor limits (Salesforce's built-in caps on the number and complexity of automated operations that can run simultaneously) pragmatically. System of Record Definitions EveryAction (EA): SSOT for digital engagement (email clicks, petition signatures, SMS interactions) and initial online transaction capture. Salesforce (SF): SSOT for unified donor profiles, aggregated revenue, major gift pipelines, and offline giving (mail/telemarketing). Data Flow Architecture ┌─────────────────────┐ Native Sync (Nightly Batch) ┌──────────────────────────┐ │ │ ──────────────────────────────────────▶ │ │ │ EveryAction │ Hourly Push (High-$ Txns) │ Salesforce │ │ (SSOT: Digital) │ ──────────────────────────────────────▶ │ (SSOT: Donor/Revenue) │ │ │ │ │ │ │ Scheduled CSV Export (Behavioral) │ ┌────────────────────┐ │ │ │ ────────────────┐ │ │ SF CRM Analytics │ │ └─────────────────────┘ │ │ │ (Dashboards 1,3,4) │ │ ▼ │ └────────────────────┘ │ ┌──────────────────┐ │ │ │ Google Sheets │ │ ┌────────────────────┐ │ │ (Staging Layer) │ │ │ Einstein Pred. │ │ └───────┬──────────┘ │ │ Builder (Weekly │ │ │ │ │ Batch Scores) │ │ SF Scheduled CSV ──────────▶ │ │ └─────────┬──────────┘ │ Export (Offline Metrics) │ │ │ │ ▼ │ ▼ │ ┌──────────────────┐ │ Scores written to │ │ Looker Studio │ │ custom Contact fields │ │ (Dashboards 2, 5) │ └──────────────────────────┘ └──────────────────┘ ┌──────────────────────────┐ │ Consultant Models │ │ (Built offline; scores │ │ uploaded monthly via │ │ Data Loader) │ └──────────────────────────┘ The Native Sync (EA → SF) Data flow: EA pushes online gifts, sustained giving schedules, and top-tier advocacy actions to SF via the native integration connector. Frequency: Nightly batch for standard actions; near real-time (hourly) for high-dollar online transactions. Hourly/real-time sync applies exclusively to descriptive revenue data (gift amounts, transaction records), never to predictive scores. Contact matching logic: The native connector matches EA records to SF Contacts primarily via email address and EA Constituent ID mapped to an External ID field on the SF Contact object. When matching fails — due to missing email, email address changes, or household-level giving — the connector creates duplicate Contacts or orphaned Opportunity records. Mitigation: Activate Salesforce Duplicate Rules with fuzzy matching on name + postal code as a secondary key. Schedule a monthly deduplication job (manual review by Salesforce Admin(s) using Duplicate Record Sets) to merge any records that bypass rules. Field-level mapping gaps: The native connector reliably syncs standard gift fields (amount, date, fund code) and basic contact demographics. It does not natively map: Custom EA action fields (e.g., custom survey responses, volunteer shift types, event-specific tags) — no corresponding standard SF field exists. Advocacy engagement scores — EA calculates composite engagement internally; this score has no native SF target field. Granular behavioral data (individual email opens/clicks, petition-specific metadata, click-through URLs) — syncing this volume would breach SF storage limits on a nonprofit-edition org. What the Pragmatic Bridge replaces: For data the native connector cannot push to SF (engagement scores, cross-channel behavioral metrics, digital campaign attribution), scheduled automated exports from EA (CSV via EA's native reporting) flow into Google Sheets and are parsed by Looker Studio. This provides the visualization layer for Dashboard 2 (Channel Performance & Testing) and Dashboard 5 (Outreach & Audience Engagement) without overloading SF storage or requiring middleware. Constraint mitigation summary: We sync to SF only those aggregated conversion events (e.g., "advocate took first financial action") and key engagement tier flags (High/Medium/Low, derived from EA scores and pushed as a picklist value to a custom SF Contact field) that directly feed predictive models or workflow triggers. The BI & Analytics Layer Primary BI — SF CRM Analytics: Used for unified revenue, major gifts, and retention modeling. SF is the presentation layer for MGOs and leadership (Dashboards 1, 3, 4). The Pragmatic Bridge — Looker Studio: For cross-channel marketing attribution (merging EA digital metrics with SF offline metrics and ad spend), scheduled automated reports (CSV via SF/EA scheduled exports) are natively parsed into Google Sheets/Looker Studio. This bypasses the need for any external data warehouse or transformation layer while providing robust visualization for channel teams (Dashboards 2, 5). Latency & Governor Limit Strategy Data Category Refresh Cadence Use Case Governor Limit Impact Descriptive (Revenue / Campaign Pacing) Hourly / Daily Cash in Door (CID) monitoring, campaign pacing Low — standard SF report queries Diagnostic (Channel Performance) Daily / Post-Campaign A/B test analysis, segment response rates Low — Looker Studio reads CSVs outside SF Predictive (AI Scores) Weekly (Sundays, 2:00 AM) Lapse/Churn Risk, Upgrade Propensity, Reactivation Likelihood Managed — batched to avoid governor limit breaches Key Stakeholder Communication: Predictive scores are strategic weekly compasses, not real-time triggers. Leadership must be trained that a "high churn risk" score reflects the prior week's behavioral pattern. Operational workflows requiring same-day responsiveness (e.g., bounce-back on a failed sustainer charge) must rely on descriptive Salesforce Flow (Salesforce's native process automation tool) triggers, not Einstein scores. Section 6 Transition: The architecture above establishes how data moves and refreshes. This section defines the five predictive models that transform that data into forward-looking donor intelligence — specifying exactly where each model lives, how often it scores, what it costs the admin team to maintain, and how feasible it is for a lean operations team to sustain. Predictive Analytics Use Cases ⚠️ LATENCY NOTICE — READ BEFORE OPERATIONALIZING: Einstein Prediction Builder (Salesforce's native machine-learning scoring tool) refreshes scores on a weekly batch cycle. All use cases below that leverage Einstein or consultant-built models produce scores updated once per week (Sundays, 2:00 AM). Operational use cases requiring daily responsiveness (e.g., triggering a same-day stewardship call based on a failed recurring gift) must use Salesforce Flow triggers on descriptive data changes, not predictive scores. Scores drive weekly portfolio prioritization and monthly campaign segmentation, not intra-day task routing. Use Case KPIs Informed (Section 3) Data Inputs Required Model Type Where It Lives Scoring Latency Output Format Dashboard Where Score Surfaces (Section 4) How It Enters Workflow Feasibility Rating Admin Maintenance Burden 1. Lapse/Churn Risk First-Year Retention, Multi-Year Retention, Downgrade/Churn Rate Gift frequency, recency, EA engagement tier flag, pledge status Classification / Probability SF Einstein Prediction Builder (weekly batch refresh) Weekly (Sundays, 2:00 AM) 1–100 Risk Score (Custom Field on Contact) Dashboard 3: Donor Health & Retention Drives dynamic "Save" email journey in EA; creates SF Task for MGOs if score > 80 on managed prospect High — native Einstein tool; requires ≥ 400 historical outcome records for training Admin: field maintenance + Flow updates. Consultant: annual model retrain. 2. Upgrade Propensity Upgrade Rate, Monthly Sustainer Growth Sustainer history, advocacy action count, event attendance, gift recency Propensity / Lookalike Consultant-Built Model (scores loaded to SF via Data Loader monthly) Monthly (scores uploaded first business day of each month) High/Med/Low Tier (Custom Picklist on Contact) Dashboard 3: Donor Health & Retention; Dashboard 4: Major/Mid-Level Pipeline Pulls into monthly telemarketing lead lists; triggers mid-level direct mail track Medium — requires external consultant to build; admin handles recurring Data Loader upload Admin: monthly Data Loader (Salesforce's bulk data import utility) upload + field QA. Consultant: quarterly model retrain. 3. Major Gift Potential Major Gift Win Rate, Pipeline Coverage Ratio Wealth screening overlay, cumulative lifetime value, restricted gift history Scoring SF Einstein Prediction Builder (weekly batch refresh) Weekly (Sundays, 2:00 AM) 1–100 Score + Key Factors (Custom Fields on Contact) Dashboard 4: Major/Mid-Level Pipeline Alerts Prospect Research to qualify; auto-assigns to MGO portfolio if score > 85 High — native Einstein tool; strongest where wealth screening data is already appended to SF Contacts Admin: field maintenance + Flow updates. Consultant: semi-annual validation. 4. Channel Responsiveness Cost to Raise a Dollar (CRD), Email/SMS Rev per M (RPM), Direct Mail Response Rate Past conversion channel, age, email open rate (from EA tier flag), mail response history Clustering Consultant-Built Model (scores loaded to SF via Data Loader quarterly) Quarterly (scores uploaded mid-quarter) Preferred Channel Flag (Custom Text Field on Contact) Dashboard 2: Channel Performance & Testing; Dashboard 1: Exec Campaign Overview (CRD impact) Dictates suppression rules (e.g., suppress mail for "Digital Only" responders to reduce CRD) Medium-Low — requires consultant build + sufficient multi-channel response history; highest ROI once 18+ months of cross-channel data exist Admin: quarterly Data Loader upload. Consultant: semi-annual model retrain. 5. Reactivation Likelihood Reactivation Rate Past lifetime value, recent advocacy action despite $0 giving, tenure, last gift date Propensity EveryAction (native predictive modeling / target scoring) Weekly (EA-native refresh cycle) EA Target Score Dashboard 3: Donor Health & Retention (Reactivation Rate tracking) Determines inclusion in expensive direct mail reactivation packages vs. digital-only reactivation Medium — leverages EA's built-in scoring; no SF maintenance required, but score visibility limited to EA interface + Looker Studio bridge export Admin: EA score export to Looker Studio for monitoring. No SF maintenance required. Decision Workflow Matrix Channel / Function Signal Source (Dashboard or Score) Threshold That Triggers Action Specific Action Who Executes Timing Digital Fundraising Dashboard 1: Exec Campaign Overview Campaign Revenue to Goal < 80% by the 15th of month Deploy corrective surge email & boost paid social spend Dir, Digital Same Day Major Gifts Dashboard 3: Donor Health & Retention Lapse/Churn Risk Score > 80 on managed prospect SF Task created for personal check-in / stewardship call MGO Within 7 Days (next weekly review) Mid-Level / Sustainer Upgrade Propensity Score (Dashboard 3) Score enters "High" Tier Move from standard annual track to mid-level telemarketing list Dir, Mid-Level Next Batch (Monthly) Direct Mail Dashboard 2: Channel Performance & Testing Direct Mail Response Rate drops >15% below historical baseline Flag segment for suppression review or creative A/B test Dir, Direct Mail Pre-Next Drop Outreach / Advocacy Dashboard 5: Outreach & Audience Engagement Advocate takes 3+ actions in 30 days with $0 lifetime giving Auto-enroll in "Never Rest" rapid-response acquisition sequence Digital Comms Real-Time (EA Automation) Prospect Research Major Gift Potential Score (Dashboard 4) Score > 85 for unmanaged donor Conduct manual wealth screening and assign to MGO portfolio Prospect Researcher Weekly Review Operations / Data EA → SF Sync Monitor Native sync error rate > 2% of nightly batch records Pause sync, investigate EA field mapping, notify channel leads Salesforce Admin(s) Immediate Executive Dashboard 1: Exec Campaign Overview Pipeline Coverage Ratio drops below 2.5x Convene MGOs for pipeline generation sprint / event planning VP, Dev Monthly Review Phased Implementation Roadmap Visual Timeline Phase Mo 1–3 Mo 4–6 Mo 7–10 Mo 11–14 Mo 15–19 Mo 20–24 Phase 1: Minimum Viable Analytics ██████ ██████ Phase 2: First Predictive Models ██████ ██████ Phase 3: Deep Automation ██████ ██████ Milestone Map with Owners Milestone Target Month Owner Phase Gate EA → SF sync audit + Duplicate Rules activated Month 2 Salesforce Admin(s) Phase 1 entry Contact matching + field mapping lockdown Month 3 Salesforce Admin(s), Sr. Dir, Dev Ops Phase 1 Dashboard 1 (Exec Campaign Overview) live Month 3 Salesforce Admin(s) Phase 1 Dashboard 2 (Channel Performance & Testing) live Month 4 Shared Data Analyst Phase 1 KPI framework documented + accepted by all Channel Leads Month 4 Sr. Dir, Dev Ops Phase 1 Dashboard 3 (Donor Health & Retention) live Month 6 Salesforce Admin(s) Phase 1 exit gate Data Hygiene Sprint (dedup, field integrity, denormalized data cleanup) Month 8 Salesforce Admin(s), Sr. Dir, Dev Ops Phase 2 — non-negotiable Dashboard 4 (Major/Mid-Level Pipeline) live Month 10 Salesforce Admin(s) Phase 2 Lapse/Churn Risk + Upgrade Propensity scores loaded to SF Month 12 External Consultant, Salesforce Admin(s) Phase 2 Major Gift Potential score active via Einstein Prediction Builder Month 12 Salesforce Admin(s) Phase 2 Predictive scores surfaced in Dashboards 3 and 4 Month 14 Salesforce Admin(s), Sr. Dir, Dev Ops Phase 2 exit gate Dashboard 5 (Outreach & Audience Engagement) live Month 17 Shared Data Analyst Phase 3 Channel Responsiveness model active; suppression rules operationalized Month 19 External Consultant, Dir, Direct Mail Phase 3 Reactivation Likelihood scoring deployed in EA Month 20 Shared Data Analyst Phase 3 90-Day Sunset Rule active; governance enforced Month 22 Sr. Dir, Dev Ops Phase 3 Full documentation + training handoff complete Month 24 Sr. Dir, Dev Ops, AV