# Helios — Marketing Analytics Platform

Defensible attribution across 15+ channels, with an optimisation agent that turns the model into budget reallocation decisions.

## Key facts

- **Domain:** MARKETING ANALYTICS
- **Status:** In production with one client
- **Use when:** Brands flying blind on cross-channel attribution want a defensible model and a budget reallocator the CFO will defend.
- **Reference engagement:** A national tourism authority in the GCC

## The problem

Marketing leaders allocate spend across more channels than ever, with less ground truth than ever. Last-click attribution understates upper-funnel investment. Multi-touch attribution fragments under platform telemetry changes. The CFO eventually asks for a defensible answer, and the marketing team does not have one.

## The approach

We built a Bayesian marketing mix model that decomposes channel contribution probabilistically, with explicit treatment of adstock and saturation per channel. An optimisation agent reads the posterior and generates budget reallocation recommendations the marketing team can take to the boardroom.

## The architecture

Python and TensorFlow for the Bayesian model. A warehouse-grounded data layer (BigQuery or Snowflake) keeps signals close to source and survives the platform telemetry changes that would break a multi-touch attribution model. Looker dashboards surface the optimisation agent's recommendations to the marketing team. Google Meridian is supported as an alternative implementation when the customer's data shape favours it.

## The outcome

Marketing leaders defend the budget reallocation with a model the CFO can read. Attribution has uncertainty estimates, not point claims. The optimisation cycle runs on a defined cadence, with the agent recommending and the team approving.

## ATI shape

- Predictive intelligence — Bayesian attribution across 15+ channels with adstock and saturation curves
- Agentic execution — Optimisation agent that translates the posterior into budget reallocation recommendations
- Secure data — Warehouse-grounded data, never leaves the customer cloud
- Actionable outcomes — Quarterly budget reallocation decisions with defensible attribution underneath

## Tech stack

- Python
- TensorFlow
- BigQuery
- Snowflake
- Looker
- Google Meridian

## Impact

- 15+ — Channels attributed in a single model
- Bayesian — Posterior with uncertainty, not point estimates
- Adstock — Carryover effects modelled per channel
- Reallocator — Optimisation agent on top of the model

## Related

- [All accelerators](https://levent.ai/accelerators/)
- [Next: Prism](https://levent.ai/accelerators/prism/)

Metrics on this page are estimated and expected improvements describing the design intent of the accelerator. Real-client delivered metrics stay in private decks; see https://levent.ai/ai-content-policy/ for the abstraction policy.

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**Canonical URL:** https://levent.ai/accelerators/helios/