Built on our open-source PyMC-Marketing library, fit on shopper panel data.
If you're making portfolio decisions on correlation models alone, you're flying blind on the real source of your growth.
Book a 30-min walkthrough for your portfolio: dub.sh/h0CfdqL
Your new SKU's sales chart is up. Half the volume might be coming from your own flagship.
A Bayesian discrete choice model traces every unit back to its real source: own-portfolio vs. competitor vs. brand-new buyer.
Here's what that picture looks like ↓
#MMM #CPG
Ask Your MMM Anything: How Agentic AI Puts Stakeholders in the Driver's Seat Webinar by PyMC Labs
Most MMMs sit idle because only three people in the org can drive them. The fix isn't a better model. It's a better interface.
Agentic dashboards, live demo: May 7, 11 AM EST.
Signup here: dub.sh/2VOLNC8
#MMM #MarketingAnalytics #AgenticAI
Nürnberger had a classic #MMM problem: lower-funnel capped, upper-funnel invisible, GDPR shortening journeys.
We built a funnel-aware MMM in pymc-marketing with censored demand + dual likelihoods.
Result: 27%+ lower CPL in 6 months.
Read Part I: dub.sh/o690ugv
#Bayesian
An uncalibrated #MMM can get ROAS direction wrong, not just magnitude. We walk through prior predictive checks, ROAS parametrization, saturation likelihoods, and where lift tests break down.
Full recording available on youtube : dub.sh/oAjXCiG
#MMMCalibration #BayesianModeling
Featured case study from the community: a two-pillar Bayesian CLV framework for a nonprofit, built on pymc-marketing.
1M+ records, MCMC vs. MAP tradeoffs, and a full Databricks deployment walkthrough
Read the blog here: dub.link/AO4oazi
#PyMC #BayesianStatistics #CLV
Watched your MCMC sampler fail after 20 min?
INFERLOG HOLMES flags convergence issues in real time, 30 seconds into sampling.
Full webinar recording with the researchers + Chris Fonnesbeck and Oriol Abril Pla now available to watch on YouTube: 👉 dub.link/v7W5hwI
#BayesianInference
Getting an LLM to run an analysis is easy. Getting it to run one you'd stake a decision on? Different problem entirely.
4 live sessions. Spec-driven workflows. Bayesian rigor.
June 2-11. Signup here: dub.link/kcIhjOi
#AgenticAI #DataScience #PyMC
Your model was right. But it was too slow to matter.
AI agents can sit on top of your Bayesian models and give stakeholders answers in seconds, not days.
New from #PyMCLabs on the decision bottleneck: dub.link/odtRwW7
#DataScience #AIAgents #BayesianModeling #AgenticAI
Equity markets cycle through regimes (low-vol trends, selloffs, grinds), each with different return profiles.
Averaging across them fits a market that never existed. Bayesian HMM in PyMC. 94% regime detection accuracy.
full dive: dub.link/uRxiSsY
#PyMC #QuantFinance
Most data scientists learn Bayesian stats from textbooks.
Few get to learn from the people who built the library.
This June, @fonnesbeck.bsky.social Niall Oulton & Robert Zinkov are running a 2.5-day hands-on PyMC workshop in London.
Reserve your spot: dub.link/oaudJAt
Your AI agent recommended shifting 30% of your budget to TikTok.
The code ran, the model converged, and the viz looked clean. The recommendation was wrong.
We built decision-lab to fix that, and we're open-sourcing it:
dub.link/4wNiUdX
#AgenticAI #OpenSource #DataScience
Your optimization model is only as good as the forecast you feed it.
We partnered with FICO to show what happens when you replace point estimates with full distributions. The results changed the decisions, not just the forecasts.
Full technical dive here: dub.link/zrDyPCF
#PyMC #FICO
Your #MMM says paid search delivers 4x ROAS. Your lift test says 1.8x
Which drives your budget?
Stop choosing. Integrate lift tests as likelihoods to calibrate MMM.
More defensible ROAS. Real uncertainty. Better decisions.
Register → dub.link/aehzbmX
Probabilistic Programming and Bayesian Modeling with PyMC
We're bringing Bayesian modeling to London, live and in person!
June 8-10: Learn to build probabilistic models in #PyMC, guided by its creators.
Small cohort, hands-on, walk out with working code. Seats are limited.
👉 Reserve your seat: dub.link/86tcbuP
#BayesianStatistics
Tired of AI confidently making bad analytical decisions?
Meet Decision Lab, our new open-source harness for #agentic data science. It explores multiple analysis paths, uses #Bayesian diagnostics as feedback, and stops when assumptions fail.
🧩Github: dub.link/wKpAWNi
Master Agentic Data Science - A live workshop for data scientists, analysts, and engineers who want to 10x their output with AI agents, without sacrificing statistical rigor, reproducibility, or the credibility of their work.
The Applied Agentic AI Data Science course is here – 12 hours of live, hands-on training to build reproducible AI workflows.
Learn directly from Thomas Wiecki, Hugo Bowne-Anderson, and Luca Fiaschi.
Secure your spot → dub.link/xriAsX6
PyMC-Marketing ROAS Posterior Distribution
An MMM can predict perfectly, and still get causality wrong.
This chart shows it: uncalibrated ROAS posteriors miss reality. Add one lift test → estimates snap back to truth.
Join our MMM Calibration deep dive Webinar (Apr 8): dub.link/Nax7e44
Most #MMMs explain the past but choke on the future; they need variables that haven't happened yet.
Our latest blog by Dr Luca Fiaschi shows how pairing PyMC-Marketing with Chronos2 fixes this: causal clarity + forecasted controls, just +0.34% added error.
👉 dub.link/jsnWOzR
#PyMC
MMM Calibration: Engineering Business Impact through Bayesian Lift Integration Webinar with PyMC Labs
Is your MMM anchored in reality, or just an approximation?
On April 8, four PyMC Labs data scientists share the calibration playbook: lift tests, prior modeling, geographic validation & more.
👉 Register here: dub.link/dB5mPlA
#MMM #MarketingAnalytics
New research proposes debugging #Bayesian inference while it runs, not after. A methodology for live MCMC diagnostics: R-hat, ESS, and trace plots updating in real time instead of post-hoc.
Join our webinar on Mar 25, 11 AM ET.
👉 dub.link/Bwr7kT3
#PyMC #MCMC #DataScience
Most quant models are correlational - they tell you what moved together in the past.
But robust investing needs more than correlation. It needs causal structure + functional form.
Our latest blog explores how the two work together.
👉 Read more: dub.link/Xe9cHWg
#CausalInference #QuantFinance
LLMs give surface-level MMM advice
So we built AI skills for pymc-marketing that know how to set priors, handle adstock carryover, and run budget optimization.
They ship with the repo and work in #Cursor/#Claude
👉Github Repo: dub.link/e5qeoQE
#PyMC #MediaMixModeling
Our Sports Analytics Team is heading to #SSAC26!
Join us for a hands-on workshop on Bayesian Spatial Modeling of #NHL goaltending. From shot difficulty to rink-wide scoring probability, see #PyMC in action!
👇 dub.link/qMEf0Ni
#SportsAnalytics #BayesianModeling #Hockey
We gave Claude a 15-page PyMC best-practices cheat sheet.
Pass rates jumped from 60% → 93%.
Hardest tasks saw the biggest gains:
• Stochastic volatility: 0% → 67%
• Runtime: 19 min → <3 min
and more ..
👉Benchmark: dub.link/KZxxZfQ
👉 Get the skill: hub.decision.ai/skills/pymc-...
#BayesianModeling
Your next focus group might be synthetic🤖
Traditional Research is slow, expensive, and limits testing. Synthetic consumers help you simulate feedback and iterate faster.
We put together a practical guide on #SyntheticConsumers : dub.link/jczwvFL
#MarketResearch #AI
We’ve been building agentic data science systems; the hardest part isn’t execution, it’s knowing if an agent’s conclusions can be trusted.
Join our webinar on Feb 25 with #PyMC Labs to learn how we catch failures & build trust
👉 dub.link/SUHEjct
#AgenticDataScience #MMM
How do #MLB teams evaluate pitchers behind the scenes? ⚾
We use Bayesian Additive Regression Trees to isolate pitcher skill from defense and park effects.
See why BART outperforms XGBoost for building pitch quality metrics 👉 dub.link/McvDt9S
#Baseball #SportsAnalytics
#Bayesian causal inference is about generative mechanisms, not just correlations.
Learn how to encode causal assumptions and simulate counterfactuals in our Applied Bayesian Regression Modeling course.
Registration still open 👇
dub.link/PKrUYFP
#PyMC #CausalInference
Bayesian regression shouldn’t stop at good fit and nice plots.
Our Applied Bayesian Regression Modeling course shows how to build models that drive real decisions using #PyMC & #Bambi
👉 Learn more & enroll: dub.link/x1K1vz4
#AppliedRegression #Analytics #DecisionMaking
