Agentic MMM

Replaced by an Agent.

We're reimagining MMM with supervised Agentic Modeling that cuts modeling cycles from 45 days to 15 days. Stop paying vendors who bill by human hours. Naukr AI agents fully automate the MMM process — so you reclaim your time for data-driven media planning and execution.

3×
Faster than agencies
$0
Data scientists needed
100%
Automated modeling

A model you can act on

No expensive data scientists required. Anyone in your marketing organization can run simulations and optimizations to allocate media spend.

Measure Every Channel

Evaluate every media channel against diminishing return curves. Know exactly where each dollar delivers maximum impact.

Simulate What-If Scenarios

Run budget planning simulations instantly. Test reallocations across channels before committing a single dollar.

Agentic Q&A

Stop calling analysts. Our AI agents let anyone consume insights instantly through natural conversation.

Power Internal Reporting

Feed results directly into complex internal reporting systems — fully automated, no human in the loop.

Why Agentic MMM?

MROI Modeling & Optimization is a continuous close-the-loop process

Supervised Agentic MMM Workflow

A 6-step closed-loop process spanning Marketing Mix Modeling to Media Spend Optimization — fully automated by our agentic platform.

Marketing Mix Modeling
1

INPUTS

Data ingestion across all marketing channels

Media MeasurementTrade MeasurementBase Measurement
2

ALGORITHM

Mixed Effects Model combining Fixed & Random effects

Bayesian & Frequentist ModelsAdstock & SeasonalityMacro-Economic Factors
3

OUTPUTS

Actionable marketing performance metrics

Incremental VolumesPrice ElasticitiesSaturation Curves
Media Spend Optimization
4

SATURATION CURVE INPUTS

ROI curves mapped against spend levels across years

Average ROI by YearWeekly Spend AnalysisIncremental Volume Curves
5

MONTE-CARLO OPTIMIZATION

Budget optimization across countries and portfolios

Planned Budget ChangeAcross / Within CountryCountry Spend Change
6

OPTIMIZED VEHICLE MIX

Final media spend allocation across brands and channels

Traditional & Digital Media SplitChannel-level AllocationPortfolio Optimization
Continuous Close-the-Loop Process

We manage 100% client data burden

Media Data Fragmentation is the #1 reason for inefficient media planning. At Naukr AI, we manage your entire data burden with multi-retailer, multi-publisher, multi-cloud support.

Retailers

  • Scintilla (Walmart)
  • Amazon
  • Costco Wholesale
  • Target

Measurement & Analytics

  • Circana
  • Nielsen ONE
  • SPINS
  • Google Analytics
  • YouTube Analytics

Digital Platforms

  • Meta
  • Amazon Advertising
  • Criteo
  • CitrusAd
  • PromoteIQ

Retail Media Networks

  • Walmart Connect
  • Roundel
  • Tesco Media
  • Wayfair
  • CVS Media Exchange
  • Macy's Media Network
  • Retail Media+

Cloud & Infrastructure

  • Microsoft Azure
  • AWS
  • Google Cloud
  • Snowflake
  • Databricks

Platform capabilities

From battle-tested ML models to conversational simulations — every tool your marketing org needs, in one intelligent platform.

Battle-Tested ML Models for Retail & CPG

Our ML library is purpose-built for marketing mix modeling, extensively validated on Retail and CPG datasets. Choose the methodology that fits your data and business context.

Bayesian Inferential Models

Incorporate prior domain knowledge and produce probability distributions over outcomes.

Frequentist Methods

Ridge, Lasso, and Elastic Net regressions deliver fast, interpretable coefficients.

Mixed Effects Model — Fixed and Random Effects distributions with formula
ROI
3.2x
mROAS
4.7
CPV
$0.12

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