People Analytics Toolbox

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grounded in this role's JobFrame record + structure

Download this job's description (markdown) → derived live from this record.

Key statistics

The identity block — every fact is canon, none is generated.

3 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

11-0000

sales

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

The top executive accountable for customer success, retention, and lifetime value across the entire organization. At the Vice President (E3) level, the role owns a division, market and competitive strategy, and drives division-wide. Leads a division's leadership team.

What this level does

Leads a large customer/revenue business area (lifecycle marketing, loyalty, customer data, and support) through senior executives, carrying enterprise-level risk on customer retention and lifetime value.
Shapes the corporate customer strategy — how the enterprise engages, retains, and grows revenue through owned channels — as a major strategic pillar.
Represents the customer-data and lifecycle agenda externally, including with strategic clients and partners, and participates in enterprise strategy forums.
Governs enterprise data-privacy and compliance posture (HIPAA, TCPA, CAN-SPAM) across all CRM and lifecycle channels as a company-level risk.
Directs enterprise investment in CDP, predictive intelligence, and cross-channel orchestration as a durable competitive capability.

Knowledge applied: Shapes corporate customer strategy for a large business area, applying enterprise-scale command of lifecycle economics, data-privacy risk, and competitive data capability.
Complexity & problem solving: Manages enterprise-level risk with critical strategic impact — customer retention, LTV, and compliance exposure that affect the corporation's durable revenue base.
Collaboration & interaction: Represents the customer/data agenda externally with strategic clients and partners and participates in enterprise strategy setting.
Typical experience: 15–20+ years, including proven enterprise-impact leadership of large divisions or regional customer businesses.

Skills at this level

Lifecycle Marketing Strategy: — Builds and optimizes an always-on lifecycle strategy across the full customer journey — engagement, retention, and revenue through owned channels — and evolves the CRM approach into true Lifecycle Marketing.
CRM P&L and Financial Ownership: — Owns the full financial picture for CRM including budget management, sales forecasting, and P&L accountability across Email, SMS, Loyalty, and lifecycle automation.
Customer Segmentation: — Divides the customer base into groups for targeted engagement and campaigns, developing segmentation strategies in partnership with Analytics and Research across segments and products.
Predictive Modeling: — Develops propensity models, LTV modeling, and next-best-action decisioning to prioritize customer engagement and drive retention and revenue.
Customer Data Platform (CDP) Ownership: — Owns CDP and predictive intelligence platforms, driving cross-channel segmentation, LTV modeling, and touchpoint orchestration across the enterprise.
Data Privacy Compliance: — Governs adherence to data-privacy laws across CRM channels, including HIPAA, TCPA, and CAN-SPAM, as an enterprise-level risk and compliance obligation.
Marketing Automation: — Configures and directs workflows for email automation, lead nurturing, and lifecycle alerts to execute always-on customer touchpoint orchestration.
Campaign Management: — Plans, executes, and analyzes lifecycle marketing campaigns across owned channels, directing CRM managers and agency partners on results.
Attribution Modeling: — Attributes retention and revenue outcomes across owned channels to inform investment allocation across Email, SMS, Loyalty, and automation.
Executive Communication and Storytelling: — Prepares and presents CRM strategy and recommendations to executive leadership including the CEO, translating customer insight into board-level narrative.
Agency and Partner Management: — Manages agency partners' timelines, deliverables, and budgets and defines team structure to plan, execute, and analyze lifecycle campaigns at scale.
CRM Governance: — Serves as connective tissue between business objectives, customer insights, marketing performance, and lifecycle execution, and participates in a CRM Governance Council setting standards and priorities.
Strategic Account Relationship Leadership: — Maintains and enhances relationships with key and strategic clients to maximize customer lifetime value across the portfolio.

Model-authored from 15 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Customer Relationship Management — median with , by . Real canon data.

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 11-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+50.0%Sales Managers · United States

402,600 → 603,710 jobs

49,000 openings / year, split into:

replacement / exits 46,088

Growth — new jobs (6%)Exits — backfill (94%)

6% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +4.7%
Growth share of hiring: 6%
Exit / retention pressure high: 94%
Openings / year: 49,000

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level E3 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$647k

San Francisco-Oakland-Fremont, CA$580k

Washington-Arlington-Alexandria, DC-VA-MD-WV$536k

Boulder, CO$529k

Seattle-Tacoma-Bellevue, WA$529k

Boston-Cambridge-Newton, MA-NH$507k

Lexington Park, MD$494k

Trenton-Princeton, NJ$491k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $388k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates E3 (E3 — Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A division
Autonomy: Accountable for division strategy and P&L
Complexity: Market and competitive strategy
Impact: Division-wide
Decision rights: Owns division strategy, budget, and org
Leadership: Leads a division's leadership team

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from E3 is E4.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
Customer Success Manager	jf_customer_relationship_management::M3	$132,663	confident0.06
Customer Success Consultant	jf_customer_relationship_management::P3	$90,905	confident0.06
Senior Customer Success Representative	jf_customer_relationship_management::S3	$54,637	confident0.06
SVP of Customer Success	jf_customer_relationship_management::E2	$355,744	confident0.06

Capability cluster

O*NET 11-2022

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

E3

jf_customer_relationship_management::E3

Chief Customer Officer

Customer Relationship Management

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: E
Superfunction: sales
Function: sales
Family: customer_relationship_management
Universal level: 3 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Alliance Partnership · E3review0.17

Applications / Systems Engineering · E3review0.17

Clinical & Technical Sales Support · E3review0.17

Field Sales · E3review0.17

Inside Sales / Telemarketing · E3review0.17

Life Sciences & Medical Device Sales · E3review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 11-2022	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)