Cates Auction Real Estate Company
Head of Marketing Intelligence & AI
Cates Auction Real Estate Company, Kansas City, Missouri, United States, 64101
Overview We’re a fast-moving, creativity-first company building products and experiences that punch above our weight. We obsess over customer outcomes, iterate quickly, and rally around experimentation and measurable impact. If you love shipping, learning, and scaling what works, you’ll feel at home here.
Applying for this role is straight forward Scroll down and click on Apply to be considered for this position. Role Overview Own the brain and the engine of our growth. As Head of Marketing Intelligence & AI, you’ll be a hands-on builder and a strategic leader: architecting our marketing data stack, launching automation and AI systems, shaping product direction through insights, and turning experiments into repeatable growth. You’ll be the connective tissue across product, marketing, engineering, sales, and operations—instilling a culture where ideas ship fast, results are measured, and learnings compound. What You’ll Own
Translate market signals into product bets; run a rigorous test-and-learn roadmap (A/B, MVT, bandits). Partner with design/eng to ship features that increase activation, retention, and monetization. Operationalize customer feedback loops (VOC, in-product surveys, NPS, qualitative research) into the roadmap. Stand up a source-of-truth growth analytics layer (from tracking to dashboards). Build multi-touch attribution and MMM-informed planning; create cohort/funnel LTV, CAC, payback models. Forecast demand, budget, and inventory/capacity needs using time-series and causal frameworks. Automation & AI Platform
Design and maintain pipelines that sync ads, CRM, product, and finance data. Deploy AI agents for lead scoring, creative generation, audience building, and lifecycle personalization. Implement retrieval-augmented generation (RAG) where it adds real value; enforce human-in-the-loop safeguards. Own the integrated GTM plan across paid, owned, earned, and lifecycle. Systematize experimentation in search, social, programmatic, partnerships, and SEO. Build creative systems (message maps, modular assets, variant libraries) to scale testing. Team, Culture & Ways of Working
Player-coach a hybrid team of analysts, marketers, and platform engineers. Establish high-tempo rituals: weekly experiment reviews, monthly post-mortems, quarterly OKRs. Champion a psychologically safe, metrics-driven culture where smart risks are rewarded. Governance, Trust & Compliance
Own data quality SLAs, tagging standards, privacy/consent management, and model monitoring. Create red-team/guardrail reviews for AI use; document decision logs and experiment ethics. Key Outcomes & KPIs
By Day 90: 10+ prioritized experiments shipped; >70% of campaigns tracked to CAC/LTV targets. First AI automations in production (e.g., creative variants, lead routing, anomaly alerts). By Day 180: Multi-touch attribution operational; planning shifts to LTV:CAC and payback windows. 2–3 product growth features shipped (activation or expansion) with measurable lift. Automated lifecycle journeys (onboarding → activation → re-engagement) with uplift targets. By Day 365: Marketing mix optimized to a ≤ 6–9 month payback (business dependent). AI/automation removes 20–30% manual toil across growth ops while improving quality. Core Responsibilities (Expanded)
Build and own the modern growth stack (event collection, CDP/warehouse, modeling, BI, activation). Stand up rigorous data contracts, tagging governance, and source-of-truth metrics. Lead quarterly growth planning; align budgets to expected marginal ROI and capacity constraints. Ship product-led growth motions (self-serve, trials, usage-based nudges, paywall/prompting). Orchestrate lifecycle messaging across email, in-app, SMS, and retargeting with real-time triggers. Develop creative testing frameworks (hooks, angles, offers) and maintain a variant library. Mentor talent; hire for T-shaped skills and high learning velocity. Present clear, candid readouts to execs: what we tried, what changed, what we’re doing next. QualificationsMust-Have
7–12+ years across growth/product/marketing analytics with 3–5+ in a lead or player-coach role. Proven record building data-driven growth systems and shipping measurable wins. Comfort across the stack: event tracking/ETL, SQL/Python, experimentation, and BI. Deep fluency in paid channels, SEO/content, and lifecycle; attribution + LTV modeling. Experience deploying practical AI/automation (prompting, APIs, workflows, guardrails). Exceptional communication; turns complexity into decisive plans. Nice-to-Have
Exposure to warehouse-native marketing (e.g., BigQuery/Snowflake + dbt + reverse ETL). Experience with MMM/MTA, causal inference, or time-series forecasting. PLG experience, B2B2C or marketplace dynamics, or small-company “zero-to-one” builds. Familiarity with privacy regimes (GDPR/CCPA) and model monitoring practices. Tooling You’ll Likely Touch
Tracking & Tagging (e.g., GTM/event schema), CDP/ETL, Warehouse & dbt, BI dashboards. Python/SQL; prompt frameworks; orchestration for workflows and alerts. Why This Role Rocks
Scope & Autonomy: You own strategy and the levers to execute. Compound Impact: Every experiment, pipeline, and playbook improves the whole system. Builder’s Playground: Ship quickly, learn faster, and scale what works. How We Work
High trust, high candor, low ego. Default to experiments over opinions. Celebrate wins; document learnings; move on fast. Apply If you’re a systems thinker who ships, measures, and iterates—and you love blending product, data, and storytelling—let’s talk. Send a short note on the biggest growth system you’ve built and the measurable change it drove. Seniority level
Executive Employment type
Full-time Job function
Marketing and Sales
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Applying for this role is straight forward Scroll down and click on Apply to be considered for this position. Role Overview Own the brain and the engine of our growth. As Head of Marketing Intelligence & AI, you’ll be a hands-on builder and a strategic leader: architecting our marketing data stack, launching automation and AI systems, shaping product direction through insights, and turning experiments into repeatable growth. You’ll be the connective tissue across product, marketing, engineering, sales, and operations—instilling a culture where ideas ship fast, results are measured, and learnings compound. What You’ll Own
Translate market signals into product bets; run a rigorous test-and-learn roadmap (A/B, MVT, bandits). Partner with design/eng to ship features that increase activation, retention, and monetization. Operationalize customer feedback loops (VOC, in-product surveys, NPS, qualitative research) into the roadmap. Stand up a source-of-truth growth analytics layer (from tracking to dashboards). Build multi-touch attribution and MMM-informed planning; create cohort/funnel LTV, CAC, payback models. Forecast demand, budget, and inventory/capacity needs using time-series and causal frameworks. Automation & AI Platform
Design and maintain pipelines that sync ads, CRM, product, and finance data. Deploy AI agents for lead scoring, creative generation, audience building, and lifecycle personalization. Implement retrieval-augmented generation (RAG) where it adds real value; enforce human-in-the-loop safeguards. Own the integrated GTM plan across paid, owned, earned, and lifecycle. Systematize experimentation in search, social, programmatic, partnerships, and SEO. Build creative systems (message maps, modular assets, variant libraries) to scale testing. Team, Culture & Ways of Working
Player-coach a hybrid team of analysts, marketers, and platform engineers. Establish high-tempo rituals: weekly experiment reviews, monthly post-mortems, quarterly OKRs. Champion a psychologically safe, metrics-driven culture where smart risks are rewarded. Governance, Trust & Compliance
Own data quality SLAs, tagging standards, privacy/consent management, and model monitoring. Create red-team/guardrail reviews for AI use; document decision logs and experiment ethics. Key Outcomes & KPIs
By Day 90: 10+ prioritized experiments shipped; >70% of campaigns tracked to CAC/LTV targets. First AI automations in production (e.g., creative variants, lead routing, anomaly alerts). By Day 180: Multi-touch attribution operational; planning shifts to LTV:CAC and payback windows. 2–3 product growth features shipped (activation or expansion) with measurable lift. Automated lifecycle journeys (onboarding → activation → re-engagement) with uplift targets. By Day 365: Marketing mix optimized to a ≤ 6–9 month payback (business dependent). AI/automation removes 20–30% manual toil across growth ops while improving quality. Core Responsibilities (Expanded)
Build and own the modern growth stack (event collection, CDP/warehouse, modeling, BI, activation). Stand up rigorous data contracts, tagging governance, and source-of-truth metrics. Lead quarterly growth planning; align budgets to expected marginal ROI and capacity constraints. Ship product-led growth motions (self-serve, trials, usage-based nudges, paywall/prompting). Orchestrate lifecycle messaging across email, in-app, SMS, and retargeting with real-time triggers. Develop creative testing frameworks (hooks, angles, offers) and maintain a variant library. Mentor talent; hire for T-shaped skills and high learning velocity. Present clear, candid readouts to execs: what we tried, what changed, what we’re doing next. QualificationsMust-Have
7–12+ years across growth/product/marketing analytics with 3–5+ in a lead or player-coach role. Proven record building data-driven growth systems and shipping measurable wins. Comfort across the stack: event tracking/ETL, SQL/Python, experimentation, and BI. Deep fluency in paid channels, SEO/content, and lifecycle; attribution + LTV modeling. Experience deploying practical AI/automation (prompting, APIs, workflows, guardrails). Exceptional communication; turns complexity into decisive plans. Nice-to-Have
Exposure to warehouse-native marketing (e.g., BigQuery/Snowflake + dbt + reverse ETL). Experience with MMM/MTA, causal inference, or time-series forecasting. PLG experience, B2B2C or marketplace dynamics, or small-company “zero-to-one” builds. Familiarity with privacy regimes (GDPR/CCPA) and model monitoring practices. Tooling You’ll Likely Touch
Tracking & Tagging (e.g., GTM/event schema), CDP/ETL, Warehouse & dbt, BI dashboards. Python/SQL; prompt frameworks; orchestration for workflows and alerts. Why This Role Rocks
Scope & Autonomy: You own strategy and the levers to execute. Compound Impact: Every experiment, pipeline, and playbook improves the whole system. Builder’s Playground: Ship quickly, learn faster, and scale what works. How We Work
High trust, high candor, low ego. Default to experiments over opinions. Celebrate wins; document learnings; move on fast. Apply If you’re a systems thinker who ships, measures, and iterates—and you love blending product, data, and storytelling—let’s talk. Send a short note on the biggest growth system you’ve built and the measurable change it drove. Seniority level
Executive Employment type
Full-time Job function
Marketing and Sales
#J-18808-Ljbffr