The Build-vs-Buy Decision
In-house MMM means a dedicated marketing science team building and operating the MMM with open-source frameworks (Robyn, LightweightMMM, PyMC-Marketing) or custom Bayesian code. Vendor MMM means a commercial provider (Recast, Northbeam, Aryma, Mass Analytics, Triple Whale) running the model for the brand. Both are viable; the choice depends on capability, budget, and the role of measurement in competitive strategy.
What In-House MMM Looks Like
Team of 1-3 marketing scientists building and operating MMM in R or Python using open-source frameworks. Refit cadence is whatever the team has capacity for, typically monthly to quarterly. Methodology is fully owned by the brand. Investment is roughly $300K-$800K annual for team and tooling.
What Vendor MMM Looks Like
Commercial vendor runs the MMM with their proprietary methodology and tooling. Brand provides data and reviews outputs. Refit cadence is the vendor's standard (typically weekly Bayesian updates with quarterly major refits). Methodology is vendor-owned with varying levels of transparency to the brand. Investment is $100K-$500K annual depending on scope.
Cost Comparison
In-house is cheaper at scale ($300K-$800K annual for team and tooling vs $100K-$500K vendor fee plus $100K-$300K internal coordination overhead). Vendor is cheaper at small scale (no team to hire). The crossover point is typically around $5M-$20M annual marketing spend; below that vendor is more efficient, above that in-house can be cheaper if the team is utilized.
Capability Comparison
Vendor brings depth in the specific MMM methodology they specialize in plus accumulated knowledge from running models for many brands. In-house builds depth in the brand's specific business context and produces a measurement capability that is a competitive asset. Brands where measurement is strategic (CPG, pharma, regulated industries) often build in-house even when vendor would be cheaper.
Control Comparison
In-house provides full methodology control: the team picks the spec, priors, validation approach, and reporting framework. Vendor provides standardized methodology with limited customization. Brands with specific methodology preferences (auditable Bayesian inference, custom hierarchical specifications, regulatory compliance) often need in-house for the control.
Feature Comparison
| Dimension | In-House | Vendor |
|---|---|---|
| Cost (annual) | $300K-$800K (team + tooling) | $100K-$500K (license + coordination) |
| Time to first model | 3-6 months | 6-12 weeks |
| Methodology control | Full | Standardized |
| Capability building | Yes (institutional asset) | Limited |
| Refit cadence | Team capacity dependent | Vendor standard (often weekly) |
| AI search integration | Custom implementation | Standard feature in modern vendors |
| Best brand size | $50M+ marketing spend | $1M-$100M marketing spend |
| Best strategic posture | Measurement as competitive asset | Measurement as operational requirement |
The Hybrid Pattern
Many brands run a hybrid: vendor MMM for production reporting plus in-house marketing science team for methodology oversight, custom analyses, and lift test design. The hybrid combines vendor operational efficiency with in-house methodology depth. It is more expensive than either pure option but produces better measurement outcomes.
How Presenc AI Helps
Presenc AI is vendor-neutral and supports both in-house and vendor MMM workflows. The AI visibility data layer is consistent regardless of who runs the MMM, which lets brands evaluate the build-vs-buy decision on cost and capability fit rather than on AI data integration capability.