Arymalabs https://validator.w3.org/feed/docs/rss2.html Home dynamic-content-megamenu-menuitem2162 Decision History Scoreboard – MMM vs Marketers Media Mix is Easy. Marketing Mix is Reality. Why Average Video Views > Likes & Comments There is One MMM Truth. But Infinite Budget Optimization Answers. The Organizational Memory Problem Solved – MMM Synapse Still Hesitating to Adopt Marketing Mix Model (MMM)? Don’t. From Excel Add-ins to Gen AI: Aryma Labs Is Building Both Ends of the Future Why we built a Product for each failure mode of MMM? Why OOH is not direct response and how it manifests in the form of interaction effects Good MMMs are not built to predict the future, they are built to change the future!! How to validate lift from OOH / DOOH campaigns Brand Building Channels’ Saturation – Diminishing Returns, Not Diminishing Importance !! AI is coming for MMM jobs Getting to 90% accurate MMM Model – Just Crown The Highest Spend Channel as Hero. Your Incrementality Test Is Only As Good As Your Control Market Why add Interaction effects in MMM and How many interaction terms to add? Solving the hard problems in MMM through AI How to Validate The Interaction Terms in MMM MCP (Model Context Protocol) solves the connectivity layer. But MMM adoption problems were never purely about connectivity. MMM is a Game of Subjective Refraction The Future is still Narrow AI Why Synthetic Control Method (SCM) says Yes when the right answer is a Big Fat NO Why MMMs are implicitly causal but yet you still can’t prefix C before MMM When Mathematics Makes Us Forget People: A Blind Spot in Synthetic Control Method (SCM) We need to rethink the concept of Adstock for Gen AI Ads Why SCM analysts deny existence of real control Why timing is crucial for validating MMM through Experiments. Why “Peeking” in Experiments Can Break Your MMM MMM First? Or Experimentation First? Why “Test vs Total” Geo Testing is Misleading and Not Causal. How in-sample MAPE can signal a decline in media effectiveness Why the MMM – Experimentation – MTA Triangle is kinda wrong How we reduced MMM’s In-sample MAPE by 4.6 percentage points through RBF technique. 90% of the clients already know their top marketing / media channels with out MMM. So why MMM? Humans Don’t Think in Probabilities Prior Predictive Check – Checking your Assumptions against your Assumptions !! One of the signs that you should not trust a method or its evangelists is that they actively block you just for disagreeing with them Good Quasi Causal Models Should have high R Squared Value The Prestige-ification of Marketing Measurement – Are you watching closely? Gen AI and The Need for Galapagos Island Is there one true Marketing Mix Model (MMM) model ? Similarities between Decomp RSSD and Bayesian Priors in Marketing Mix Modeling (MMM) How to use Robyn’s Decomp RSSD Metric Effectively Chebyshev’s Inequality for Marketing Mix Model Diagnostics MMM Updates: Why they often happen based on Budget, and not when they are actually needed !! Industry Benchmarks in MMM should not be a North Star Geometric Adstock Simplified in 6 Steps How Do you know your adstock values are accurate?