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StatistiqAI
Industry · Marketing

AI built for measurement, lifecycle, and creative work that moves MER and payback.

Agentic media mix modeling. Predictive lead scoring. GenAI creative automation. CDP-driven 1:1 lifecycle. Generative engine optimization. Built in your stack, against your funnel.

The numbers we work against

We work in the buyer’s vocabulary.

CACLTVLTV:CACMERROASPaybackMQL / SQLMMMMTAIncrementalityShare-of-searchGEO
Where we ship

Four marketing AI workflows.

Each is a system we've shipped or have direct shipped credibility for. We don't take engagements outside this surface area unless we can name an adjacent build we've already done.

MK.01 — MEASUREMENT

Agentic MMM & measurement

Agentic media mix modeling, scenario planning, and incrementality measurement built for the post-cookie world. Calibrated to lift tests, not just historical correlations.

PRIMARY KPI · MER · Incrementality

MK.02 — LIFECYCLE

CDP-driven 1:1 lifecycle

Predictive lead scoring, next-best-action modeling, and lifecycle orchestration on top of your CDP. RAG-based recommendation integrated with proprietary client data.

PRIMARY KPI · LTV · Payback

MK.03 — CREATIVE

GenAI creative automation

Brand-grounded creative generation, variant production, and pre-flight quality evaluation. We build the eval before we ship the generator.

PRIMARY KPI · Creative velocity · ROAS

MK.04 — DISCOVERY

Search & GEO

Generative engine optimization (GEO), AI-native search visibility, and conversational acquisition surfaces. Measurement-first, not vanity-impression-first.

PRIMARY KPI · Share-of-search · GEO presence

01

Spend + outcomes

by channel

02

Bayesian MMM

media-mix model

03

Incrementality curves

response curves

04

Agentic scenarios

search budgets

LLM agents
05

Budget reallocation

CAC · MER · ROAS

Incrementality measurement · planner vocabulary (CAC · MER · ROAS) answers a planner can act on, not a black-box score
MK.01 · Agentic media-mix modeling. Bayesian MMM → incrementality curves → agentic scenario search → reallocation.
Stack · Databricks or cloud ML · LLM agent layer
Technology in practice

The stack behind the workflows.

Representative builds — the technology patterns we bring to marketing. Where we cite results, they’re from work our team has shipped; everything else is what we’d build for you.

MK.T1 · Databricks or cloud ML

Agentic media-mix modeling

Bayesian media-mix modeling with agentic scenario exploration — budget reallocation in the planner's vocabulary.

Stack · Databricks or cloud ML · LLM agent layer

MK.T2 · Snowflake

Composable CDP

Composable CDP on the warehouse — identity resolution, reverse-ETL activation, incrementality measurement.

Stack · Snowflake · dbt · Hightouch/Census-class activation

MK.T3 · Warehouse-native ML

Predictive lead scoring

Warehouse-native propensity models with activation into CRM/MAP. Our team shipped forecasting + RAG recommendations that drove a 7% annual TCV increase at a SaaS marketing platform.

Stack · Snowflake or Databricks · reverse ETL

Regulatory frame

Marketing KPIs are the operating frame.

Marketing is less regulated than insurance or healthcare, but operationally unforgiving — and the consumer-privacy frame is tightening. Our governance frame is CAC, LTV, MER, and payback — anchored against a privacy posture.

Where regulation does apply (consumer privacy, generative creative claims, AI-disclosure requirements), we apply the same audit-readiness discipline we use in regulated industries.

GDPR · DPDP · CCPAFTC AI guidanceGenerative ad disclosureConsumer privacyServer-side measurement
Where Statistiq has shipped

Inside a venture-backed SaaS marketing platform.

Our founding team has shipped AI on a venture-backed SaaS marketing platform, including scalable time-series forecasting on AWS and RAG-based recommendation on LangChain integrated with proprietary client data.

7%Annual TCV increase
AWS + LangChainProduction stack
Time-series + RAGHybrid modeling

Have an MMM, lifecycle, or creative problem AI should be solving?

Most first conversations are 30 minutes with a senior partner. We'll tell you whether it's a fit, whether AI is the right answer, and what we'd build first.